Sequence-to-Sequence (seq2seq) & Chatbots 2018


Notes:

In 2018, there was an explosion of papers published on S2S and chatbots.

  • Dialog systems
  • Neural conversation models
  • Question answering systems

Wikipedia:

References:

See also:

100 Best TensorFlow Chatbot Videos100 Best TensorFlow VideosNeural Network & Dialog Systems 2018TensorFlow & Chatbots 2017


Neural Dialogue System with Emotion Embeddings
R Shantala, G Kyselov… – 2018 IEEE First …, 2018 – ieeexplore.ieee.org
… A. Background: sequence-to-sequence models Seq2Seq models are the most commonly used architecture in … of the dialogue system language model compared to the basic seq2seq approach … of this work are also expanding and include the development of chatbots with an …

Lingke: A fine-grained multi-turn chatbot for customer service
P Zhu, Z Zhang, J Li, Y Huang, H Zhao – arXiv preprint arXiv:1808.03430, 2018 – arxiv.org
… The chit-chat model is an attention-based seq2seq model (Sutskever et al., 2014) achieved by a generic deep learning framework … Sequence to sequence learning with neural networks … Docchat: An information retrieval approach for chatbot engines using unstructured documents …

PESUBot: An Empathetic Goal Oriented Chatbot
HV Kumar, J Nagaraj, M Irfan… – … on Advances in …, 2018 – ieeexplore.ieee.org
… Firstly, vanilla sequence-to-sequence neural network is adopted and modification for sentiment level correlation is … The contextual model is architected to be a Seq2Seq Model using RNNs with GRUs as … the HRED model was built for general chatbots while our chatbot was more …

A Survey on Chatbot Implementation in Customer Service Industry through Deep Neural Networks
M Nuruzzaman, OK Hussain – 2018 IEEE 15th International …, 2018 – ieeexplore.ieee.org
… The sequence-to-sequence (seq2seq) model in deep recurrent neural networks (DRNN) with attention mechanism … Cleverbot Cleverbot is one of the most popular entertainment chatbots that implement … IBM Watson Watson is rule-based AI chatbot developed by IBM’s DeepQA …

Empathetic Dialog Systems
P Fung, D Bertero, P Xu, JH Park, CS Wu… – The International …, 2018 – lrec-conf.org
… Figure 6: Seq2Seq + reinforce … We train a hierarchical sequence-to-sequence model in or- der to maximize a reward score based on funniness and rel- evance, and … Finally, we showed how to train an end-to-end chatbot with reinforce- ment deep learning that learns a sense of …

Why are Sequence-to-Sequence Models So Dull? Understanding the Low-Diversity Problem of Chatbots
S Jiang, M de Rijke – arXiv preprint arXiv:1809.01941, 2018 – arxiv.org
… The variability of Seq2Seq models is different from that of retrieval-based chatbots (Fedorenko et al … entropy maximizing methods, the self-repeating problem (Li et al., 2017) of Seq2Seq models may … Abstractive text summariza- tion using sequence-to-sequence rnns and beyond …

DeepPavlov: Open-Source Library for Dialogue Systems
M Burtsev, A Seliverstov, R Airapetyan… – Proceedings of ACL …, 2018 – aclweb.org
… development of production-ready chatbots and complex … There are currently three Skills implemented in the library, namely, modular and sequence-to-sequence goal-oriented skills as well … It can be a dialogue system that contains a goal-oriented and chatbot skills and chooses …

Complex sequential question answering: Towards learning to converse over linked question answer pairs with a knowledge graph
A Saha, V Pahuja, MM Khapra… – Thirty-Second AAAI …, 2018 – aaai.org
… like to focus on such real life settings encountered by chatbots which involve … pairs over a coherent conversation, we also review some related work on dialog systems … Here again, neural network based (hierarchical) sequence to sequence methods (?; ?; have become the de …

Artificial Intelligence for Conversational Robo-Advisor
MY Day, JT Lin, YC Chen – 2018 IEEE/ACM International …, 2018 – ieeexplore.ieee.org
… field of interaction between humans and machines [1]. The utilization of chatbots can be … data of generative model for training the deep learning sequence to sequence chatbot are obtained … Table 3. Parameters of Seq2Seq model Parameter Value Dropout 0.5 Loss Function …

Response selection with topic clues for retrieval-based chatbots
Y Wu, Z Li, W Wu, M Zhou – Neurocomputing, 2018 – Elsevier
… Generation based chatbots employ statistical machine translation techniques [18] or the sequence to sequence (S2S) framework [4], [5], [19 … 3. Retrieval based chatbots overview. In this section, we introduce a general framework of a retrieval based chatbot, as illustrated in Fig …

Creating an Emotion Responsive Dialogue System
A Vadehra – 2018 – uwspace.uwaterloo.ca
… 10 2.3 A Sequence-to-Sequence (Seq2Seq) Network with and without attention … Customer support or food ordering chatbots are examples of task spe- cific conversational agents where the success of the system is determined by the ability of the agent to … 1.2.1 Dialogue System …

Encoding emotional information for sequence-to-sequence response generation
YH Chan, AKF Lui – … on Artificial Intelligence and Big Data …, 2018 – ieeexplore.ieee.org
… An emotional chatbot is a conversational agent that is conditioned to generate emotional responses … [8] I. Sutskever, O. Vinyals, and QV Le, “Sequence to Sequence Learning with … [20] T. Luong, E. Brevdo and R. Zhao, “Neural Machine Translation (seq2seq) Tutorial,” https …

Towards Automated Customer Support
M Hardalov, I Koychev, P Nakov – International Conference on Artificial …, 2018 – Springer
… 4.3 Sequence-to-Sequence … Twitter using two types of models: (i) retrieval-based (IR with BM25), and (ii) based on generative neural networks (seq2seq with attention … Scholar. 4. Cui, L., Huang, S., Wei, F., Tan, C., Duan, C., Zhou, M.: SuperAgent: a customer service chatbot for e …

Multitask learning for neural generative question answering
Y Huang, T Zhong – Machine Vision and Applications, 2018 – Springer
… Building chatbot in human–computer conversation via natural language is one of the most … Sequence-to-sequence learning Seq2Seq model is an end-to-end learning with encoder–decoder framework where the … We define our main task as a generative QA via Seq2Seq learning …

Chitty-Chitty-Chat Bot: Deep Learning for Conversational AI.
R Yan – IJCAI, 2018 – ijcai.org
… We may stand at the entrance of future success in more advanced conversational systems (social chatbots and/or virtual assistants) … Alime chat: A sequence to sequence and rerank based chatbot engine … Sequence to sequence learning with neural networks …

Out-of-domain detection method based on sentence distance for dialogue systems
KJ Oh, DK Lee, C Park, YS Jeong… – … Conference on Big …, 2018 – ieeexplore.ieee.org
… detection(OOD) method, and we apply this method to develop a chatbot system for … For training the encoder, we imple- ment a sequence-to-sequence model based on a bi … only in-domain sentences for out-of-domain sentence detection in dialog systems, Pattern Recognition …

Modern Chatbot Systems: A Technical Review
AS Lokman, MA Ameedeen – Proceedings of the Future Technologies …, 2018 – Springer
… Abbreviated from Sequence-to-Sequence phrase, Seq2Seq encoder takes input sentence as a sequence of … While Seq2Seq model is good for sequential data, LSTM application is more … Lokman, AS, Zain, JM: Chatbot enhanced algorithms: a case study on implementation in …

First Insights on a Passive Major Depressive Disorder Prediction System with Incorporated Conversational Chatbot
F Delahunty, ID Wood – ceur-ws.org
… heuristic that guides the development of neural baseline systems for the extractive conversational chatbot task is … the OpenNMT toolkit [18], which is a generic deep learning framework mainly specialising in sequence-to-sequence … (seq2seq) models and covers a variety of tasks …

A Manually Annotated Chinese Corpus for Non-task-oriented Dialogue Systems
J Li, Y Song, H Zhang, S Shi – arXiv preprint arXiv:1805.05542, 2018 – arxiv.org
… one size fits all” replies, which is a major drawback of the existing chatbots (Li et … reliable than automatic collected data and thus potentially ben- eficial to chatbot training and … Generating High-quality and Informative Conversa- tion Responses with Sequence-to-sequence Models …

Implementing ChatBots using Neural Machine Translation techniques
A Nuez Ezquerra – 2018 – upcommons.upc.edu
… A great step forward to the area of generative-based chatbots was the … an encoder/decoder architecture with recurrent neural networks known as sequence to sequence (Seq2Seq) [12] used … The chatbot uses the Artificial Intelligence Markup Language (AIML) for the definition of …

DeepPavlov: An Open Source Library for Conversational AI
M Burtsev, A Seliverstov, R Airapetyan, M Arkhipov… – 2018 – openreview.net
… Sequence-to-sequence chit-chat, question answering or task-oriented skills can be assembled from components provided in the library … development of production-ready chatbots and complex conversational systems; • NLP and dialog systems research …

Deep Learning in Spoken and Text-Based Dialog Systems
A Celikyilmaz, L Deng, D Hakkani-Tür – Deep Learning in Natural …, 2018 – Springer
… This model is called sequence-to-sequence or seq2seq … 2011), retrieval-based response selection (Banchs and Li 2012), and sequence-to-sequence models with different structures … a conversational dialog engine for creating chat bots, chatbot-rnn, 20 a toy chatbot powered by …

First insights on a passive major depressive disorder prediction system with incorporated conversational chatbot
M Arcan, ID Wood, F Delahunty – Irish Conference on Artificial …, 2018 – library.nuigalway.ie
… of neural baseline systems for the extractive conversational chatbot task is … work has already explored the possibility of building conversational chatbots that emulate … is a generic deep learning framework mainly specialising in sequence-to-sequence (seq2seq) models covering …

A Next Generation Chatbot-Framework for the Public Administration
A Lommatzsch – International Conference on Innovations for Community …, 2018 – Springer
… We have found that currently foreigners seem to prefer this channel; but with the increased popularity of chatbots and the high … F.-L., Wang, S., Gao, X., Chen, Y., Zhao, W., Chen, H., Huang, J., Chu, W.: AliMe chat: a sequence to sequence and rerank based chatbot engine …

A Next Generation Chatbot-Framework for the Public Administration–DRAFT–
A Lommatzsch – dai-labor.de
… We have found that currently foreigners seem to prefer this channel; but with the increased popularity of chatbots and the high quality of the provided answers, the developed digital assistant will attract … Alime chat: A sequence to sequence and rerank based chatbot engine …

Impact of Auxiliary Loss Functions on Dialogue Generation Using Mutual Information
JS Clair, T Conley, J Kalita – cs.uccs.edu
… a chatbot, that learns from a corpus of conversations, using a basic sequence to sequence (Seq2Seq) model with … be to add a reinforcement learning and attention model to the Seq2Seq model from … paper, but it would shed more light on the competency of chatbot dialogue and …

Why are Sequence-to-Sequence Models So Dull?
S Jiang, M de Rijke – EMNLP 2018, 2018 – aclweb.org
… The variability of Seq2Seq models is different from that of retrieval-based chatbots (Fedorenko et al., 2017): in this study, we focus on the lack of variability of … (Li et al., 2017) of Seq2Seq models may … Abstractive text summariza- tion using sequence-to-sequence rnns and beyond …

The Design and Implementation of XiaoIce, an Empathetic Social Chatbot
L Zhou, J Gao, D Li, HY Shum – arXiv preprint arXiv:1812.08989, 2018 – arxiv.org
… The design objective of the chatbot is to find optimal policies and skills to … in the conversational AI community [4]. Its role in developing social chatbots is becoming … The neural response generator in XiaoIce follows the sequence-to-sequence (seq2seq) framework [14, 15] used …

End-to-End Task-Oriented Dialogue System with Distantly Supervised Knowledge Base Retriever
L Qin, Y Liu, W Che, H Wen, T Liu – Chinese Computational Linguistics …, 2018 – Springer
… has also been used in past literature for evaluating dialogue systems both of the chatbot and task … In the future, we would like to jointly model the KB retriever and seq2seq framework in an end … Sutskever, I., Vinyals, O., Le, QV: Sequence to sequence learning with neural networks …

Role play-based question-answering by real users for building chatbots with consistent personalities
R Higashinaka, M Mizukami, H Kawabata… – Proceedings of the 19th …, 2018 – aclweb.org
… char- acters, the next step is to determine if the col- lected pairs can be useful for creating chatbots that exhibit … as a query and the answer part of the most relevant pair is returned as a chatbot’s response … Translation model We trained a translation model by using a seq2seq model …

The First Conversational Intelligence Challenge
M Burtsev, V Logacheva, V Malykh, IV Serban… – The NIPS’17 …, 2018 – Springer
… For the seq2seq models, the team trained diverse neural networks with different data and network … The system uses four strategies to enhance existing sequence-to-sequence conversational models: 1 … defined by user success in the task, in a way that a good chatbot should be …

Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base
D Guo, D Tang, N Duan, M Zhou, J Yin – Advances in Neural …, 2018 – papers.nips.cc
… experiments on a large-scale dataset [17] for conversation question answering, which consists of … HRED+KVmem [17] is a sequence- to-sequence learning method, which uses a hierarchical … which explicitly manipulates the actions/functions and lets the Seq2Seq model learn …

A knowledge-grounded neural conversation model
M Ghazvininejad, C Brockett, MW Chang… – Thirty-Second AAAI …, 2018 – aaai.org
… have been mostly applied to casual scenarios (eg, as “chatbots”) and have … Introduction Recent work has shown that conversational chatbot mod- els can be trained … The dialog encoder and response decoder form together a sequence-to-sequence (SEQ2SEQ model (Hochreiter …

Conversational Modelling for ChatBots: Current Approaches and Future Directions
M McTear – 2018 – spokenlanguagetechnology.com
… Sequence to sequence mapping between an input and a response means that the system does not … the same skill (eg weath- er forecast) may behave differently on the same chatbot … quential mechanics of conversation is essential to make interactions with chatbots intuitive and …

Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation.
Q Qian, M Huang, H Zhao, J Xu, X Zhu – IJCAI, 2018 – ijcai.org
… Conversation Machine (PCCM) and compared it with several baselines: Seq2Seq: a general sequence to sequence model [Sutskever … Nevertheless, our model is still much better than the Seq2Seq model … Our work moves toward endowing a chatbot with control- lable personality …

Open-domain neural conversational agents: The step towards artificial general intelligence
S Arsovski, S Wong, AD Cheok – International Journal of …, 2018 – openaccess.city.ac.uk
… Ever since the success of Seq2Seq model in creating state of the art generative neural conversational agent … [10] J. Wakefield, “Microsoft chatbot is taught to … www.bbc.com/news/ technology-35890188 [11] I. Sutskever, O. Vinyals, and QV Le, “Sequence to sequence learning …

Information Discovery in E-commerce: Half-day SIGIR 2018 Tutorial
Z Ren, X He, D Yin, M de Rijke – … ACM SIGIR Conference on Research & …, 2018 – dl.acm.org
… We conclude with a summary of existing chatbots models applied in e-commerce, and outlook to future directions of e-commerce chatbots … Alime chat: A sequence to sequence and rerank based chatbot engine. In ACL, pages 498–503. ACL, 2017 …

Retrieval-Enhanced Adversarial Training for Neural Response Generation
Q Zhu, L Cui, W Zhang, F Wei, Y Chen, T Liu – arXiv preprint arXiv …, 2018 – arxiv.org
… used in real-world applications, including customer service systems, personal assistants, and chatbots. Early dialogue systems are often built using the rule-based method (Weizenbaum, 1966 … of this category in recent years is the sequence to sequence (Seq2Seq) based model …

Knowledge-aware Multimodal Dialogue Systems
L Liao, Y Ma, X He, R Hong, T Chua – 2018 ACM Multimedia Conference …, 2018 – dl.acm.org
… in optimizing for better rewards with the power of hierarchical seq2seq models in … Also known as chat bots, the non-task- oriented systems converse with human typically on … model sequential utterances, we resort to the powerful hierarchi- cal sequence-to-sequence models such …

Tailored Sequence to Sequence Models to Different Conversation Scenarios
H Zhang, Y Lan, J Guo, J Xu, X Cheng – … of the 56th Annual Meeting of …, 2018 – aclweb.org
… While for the diverse- requirement scenario, the experiments on the pub- lic Chinese Weibo dataset (social chatbot) show that optimizing CVaR … 4 Tailored Sequence to Sequence Models … ?r(?) = inf{? ? R|P(?log P(Y |X) ? ?) ? r}, and ? are parameters of the Seq2Seq model …

Dialog generation using multi-turn reasoning neural networks
X Wu, A Martinez, M Klyen – Proceedings of the 2018 Conference of the …, 2018 – aclweb.org
… Dialogue systems such as chatbots are a thriving topic that is attracting increasing attentions from … and i<Td) which ensures the encoding and decoding processes in sequence-to-sequence models … using a reinforcement learning policy to determine when to let the chatbot to give …

Hierarchical hybrid code networks for task-oriented dialogue
W Liang, M Yang – International Conference on Intelligent Computing, 2018 – Springer
… Unlike open-domain chatbot, task-oriented dialogue system mainly focuses on a specific … also achieved quite advanced performance, indicating the effectiveness of the seq2seq model on … Lu, Z., Li, H., Li, VOK: Incorporating copying mechanism in sequence-to-sequence learning …

Improving Dialog Systems Using Knowledge Graph Embeddings
B Carignan – 2018 – curve.carleton.ca
… The four embedding sets were trained with a sequence-to-sequence model from OpenNMT on a dialog dataset from OpenSubtitles … 6 2.1.2 Early Chatbots ELIZA [11] is an early chatbot program which uses a series of scripts to process user inputs and output pre-set responses …

Improving Computer Generated Dialog with Auxiliary Loss Functions and Custom Evaluation Metrics
T Conley, JS Clair, J Kalita – cs.uccs.edu
… the output of the SMT-based response generation system with a Seq2Seq model that … With better evalua- tion models, a neural-network-based chatbot may be enhanced to … Generating high- quality and informative conversation responses with sequence-to-sequence models …

Improving Matching Models with Contextualized Word Representations for Multi-turn Response Selection in Retrieval-based Chatbots
C Tao, W Wu, C Xu, Y Feng, D Zhao, R Yan – arXiv preprint arXiv …, 2018 – arxiv.org
… to im- prove matching models for multi-turn response selection in retrieval-based chatbots … Existing methods on building a chatbot are ei- ther generation-based or retrieval-based. Regard- ing to the former, on top of the basic sequence- to-sequence with attention architecture …

Fantom: A Crowdsourced Social Chatbot using an Evolving Dialog Graph
P Jonell, M Bystedt, FI Dogan, P Fallgren, J Ivarsson… – dex-microsites-prod.s3.amazonaws …
… On the other side of the scalability spectrum, sequence- to-sequence models based on recurrent neural networks have proven to be … Most chatbots of today are trained using example interactions … to the roles the both users had, while in our case, the role of the chatbot is different …

A Virtual Chatbot for ITSM Application
S Raut – Asian Journal For Convergence In Technology …, 2018 – asianssr.org
… Chatbots that are developed using deep learning, mostly use a certain variant of sequence to sequence (Seq2Seq) model … Thus, Seq2Seq model generates the potential response respective to the given input … [6] Bayu Setiaji, Ferry Wahyu Wibowo, “Chatbot Using A Knowledge …

Emotional chatting machine: Emotional conversation generation with internal and external memory
H Zhou, M Huang, T Zhang, X Zhu, B Liu – Thirty-Second AAAI Conference …, 2018 – aaai.org
… To cre- ate a chatbot capable of communicating with a user at the human level … Existing studies show that addressing affect and emo- tion in dialogue systems or conversational … is based on the encoder-decoder framework of the general sequence-to-sequence (seq2seq for short …

Context-Aware Dialog Re-Ranking for Task-Oriented Dialog Systems
J Ohmura, M Eskenazi – 2018 IEEE Spoken Language …, 2018 – ieeexplore.ieee.org
… and Michiel Bacchiani, “State-of-the-art speech recognition with sequence-to-sequence models,” 2018 … taking a spoken dialog system to the real world,” in Ninth Euro- pean … and Hui Xue, “Ranking responses oriented to conversational relevance in chat- bots,” in Proceedings of …

Modeling multi-turn conversation with deep utterance aggregation
Z Zhang, J Li, P Zhu, H Zhao, G Liu – arXiv preprint arXiv:1806.09102, 2018 – arxiv.org
… Lei Cui, Shaohan Huang, Furu Wei, Chuanqi Tan, Chaoqun Duan, and Ming Zhou. 2017. Superagent: A customer service chatbot for e-commerce websites … 2018. Seq2seq dependency parsing … 2017. Alime chat: A sequence to sequence and rerank based chatbot engine …

NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager
I Yusupov, Y Kuratov – Proceedings of the 27th International Conference …, 2018 – aclweb.org
… The Facebook news seq2seq skill, in addition to the dialog context, may use a paragraph as an input … AIML-based Alice chit-chat skill covers a wide range of topics, while sequence-to- sequence based chit-chat skill trained on Open … 2017. A deep reinforcement learning chatbot …

Using Deep Learning and an External Knowledge Base to Develop Human-Robot Dialogues
JY Huang, TA Lin, WP Lee – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… Recently, the demand on chatbots has begun to perform open-domain conversations … These neural systems mainly used sequence to sequence model as a backbone, to perform … In this work, we develop a human-robot dialogue system extended from our previous framework of …

Response Selection and Automatic Message-Response Expansion in Retrieval-Based QA Systems using Semantic Dependency Pair Model
MH Su, CH Wu, KY Huang, WH Lin – ACM Transactions on Asian and …, 2018 – dl.acm.org
… based method, the Okapi BM25 model, and the deep learning-based sequence-to-sequence with attention … alignment between the post and the response [8]. The retrieval-based chatbots choose a … methods, and it is difficult to develop an extensible open-domain chatbot system …

Improving goal-oriented visual dialog agents via advanced recurrent nets with tempered policy gradient
R Zhao, V Tresp – arXiv preprint arXiv:1807.00737, 2018 – arxiv.org
… Das et al. [2017] formulated a visual dialogue system which is about two chatbots asking and answering questions to identify a specific image … We utilize a Seq2Seq model [Sutskever et al., 2014] to process the image along with the historical dialogues for question generation …

Coupled context modeling for deep chit-chat: towards conversations between human and computer
R Yan, D Zhao – Proceedings of the 24th ACM SIGKDD International …, 2018 – dl.acm.org
… social chatbots as real world applications. Since the Web 2.0 is so popular nowadays, people are getting used to having conversations—in public—on a variety of websites, such as forums, social medium (eg, Facebook, Twitter) and com- munity question-answering platforms …

Conversational query understanding using sequence to sequence modeling
G Ren, X Ni, M Malik, Q Ke – Proceedings of the 2018 World Wide Web …, 2018 – dl.acm.org
… Conversational Query Understanding Using Sequence to Sequence Modeling … 1 INTRODUCTION The recent rise of technologies such as chatbots, digital personal … However, information retrieval and question answering systems have traditionally been designed for stateless or …

Personalized response generation by Dual-learning based domain adaptation
M Yang, W Tu, Q Qu, Z Zhao, X Chen, J Zhu – Neural Networks, 2018 – Elsevier
… such as e-commerce, technical support services, entertaining chatbots, information retrieval … translation, most non-goal-oriented conversational systems employ sequence-to-sequence (seq2seq) framework to … individual embeddings and incorporating it into the seq2seq model …

Topic-Based Question Generation
W Hu, B Liu, R Yan, D Zhao, J Ma – 2018 – openreview.net
… Since questioning is an important communication skill, question generation plays an important role in both general-purpose chatbot systems and goal-oriented dialogue systems … Sequence to sequence learning with neural networks. In NIPS, 2014 …

From Eliza to XiaoIce: challenges and opportunities with social chatbots
HY Shum, X He, D Li – Frontiers of Information Technology & Electronic …, 2018 – Springer
… For this purpose, social chatbots must develop a set of skills to accommodate users’ requests … accomplishing tasks and ending the conversation as quickly as possible), social chat- bots take time … XiaoIce has been the most widely deployed so- cial chatbot since it was released …

Aspect-based question generation
W Hu, B Liu, J Ma, D Zhao, R Yan – 2018 – openreview.net
… is an important communication skill, question generation plays an important role in both general-purpose chatbot systems and goal-oriented dialogue systems … Multi-source sequence-to-sequence learning aims to integrate information from multiple sources to boost …

Concorde: Morphological Agreement in Conversational Models
D Polykovskiy, D Soloviev… – Asian Conference on …, 2018 – proceedings.mlr.press
… appear in a wide range of applications, from simple rule-based chatbots to complex … Dialogue and conversation modeling are a characteristic example of sequence-to-sequence problems: given a … model introduced by Vinyals and Le (2015) uses the seq2seq framework from …

Learning goal-oriented visual dialog via tempered policy gradient
R Zhao, V Tresp – 2018 IEEE Spoken Language Technology …, 2018 – ieeexplore.ieee.org
… Index Terms— Goal-Oriented Dialog System, Deep Re- inforcement Learning, Recurrent Neural Network … 7] formulated a visual dialogue system which is about two chatbots asking and … Firstly, by extending existing models with Seq2Seq and Memory Networks we could improve …

An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems.
Y Song, R Yan, CT Li, JY Nie, M Zhang, D Zhao – 2018 – openreview.net
… (2013)). Recently, researchers have paid increasing attention to open-domain, chatbot-style human-computer conversations such as XiaoIce1 and Duer2 due to their important commercial values … We then propose a “multi sequence to sequence” (multi-seq2seq) model to …

MOOC-O-Bot: Using Cognitive Technologies to Extend Knowledge Support in MOOCs
A Mitral, L Vigentini, M Djatmiko… – … , and Learning for …, 2018 – ieeexplore.ieee.org
… These systems are generally modeled using sequence to sequence (seq2seq) models [27] and are based on … [28] proposes an ensemble of retrieval based and generative chatbot systems by … retrieval based and generation based model and uses an attentive Seq2Seq re-ranD …

Proceedings of the 22nd Conference on Computational Natural Language Learning
A Korhonen, I Titov – Proceedings of the 22nd Conference on …, 2018 – aclweb.org
… Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction Maha Elbayad … Churn Intent Detection in Multilingual Chatbot Conversations and Social Media … Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain …

A Trustworthy, Responsible and Interpretable System to Handle Chit-Chat in Conversational Bots
P Agrawal, A Suri, T Menon – arXiv preprint arXiv:1811.07600, 2018 – arxiv.org
… It also provides a signal to seq2seq auto- generation model to ensure that it only generates a … I Am A Sequence- to-Sequence Model trained on Reddit Data, Ask Me Any- thing … Docchat: An information re- trieval approach for chatbot engines using unstructured doc- uments …

Hierarchical variational memory network for dialogue generation
H Chen, Z Ren, J Tang, YE Zhao, D Yin – … of the 2018 World Wide Web …, 2018 – dl.acm.org
… 38, 41] have been proved to be capable in multiple dialogue system applications with … 6]: (1) Meaningless responses: Given a wide range of contexts, dialogue systems trained via … Sequence to Sequence Models Our work is based on sequence-to-sequence (SEQ2SEQ) models …

Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce
M Qiu, L Yang, F Ji, W Zhao, W Zhou, J Huang… – arXiv preprint arXiv …, 2018 – arxiv.org
… To form our data set, we concatenated utterances within three turns 7 to form a query, and used the chat- bot system to call back top 15 most similar candi- date questions as candidate “responses” … Alime chat: A sequence to sequence and rerank based chatbot engine …

Mem2seq: Effectively incorporating knowledge bases into end-to-end task-oriented dialog systems
A Madotto, CS Wu, P Fung – arXiv preprint arXiv:1804.08217, 2018 – arxiv.org
… Figure 1: The proposed Mem2Seq architecture for task-oriented dialog systems … tems (Eric and Manning, 2017; Zhao et al., 2017) and chat-bots (Ritter et … We also implemented the following baseline models: standard sequence-to-sequence (Seq2Seq) models with and without …

Improving Neural Question Generation using Answer Separation
Y Kim, H Lee, J Shin, K Jung – arXiv preprint arXiv:1809.02393, 2018 – arxiv.org
… 2018) or to engage chatbots to start and continue a conversation (Mostafazadeh et al … When we evaluate our answer-separated seq2seq on the SQuAD dataset (Rajpurkar et al … learning with regard to the question generation problem using a sequence-to-sequence model with …

Epilogue: Frontiers of NLP in the Deep Learning Era
L Deng, Y Liu – Deep Learning in Natural Language Processing, 2018 – Springer
… application, document or text summarization, is also well suited to sequence-to-sequence learning and … been applied to all three types of dialogue systems or chatbots (intelligent assistants … progress in this research frontier is gaining greater urgency as chatbot conversations are …

Towards Understanding User Requests in AI Bots
OT Tran, TC Luong – Pacific Rim International Conference on Artificial …, 2018 – Springer
… and improved techniques, chatbots still face various challenges in understanding user requests, processing them to generate an appropriate response, especially in ordering chatbots … Qiu, M., et al.: AliMe chat: a sequence to sequence and rerank based chatbot engine …

Research Challenges in Building a Voice-based Artificial Personal Shopper-Position Paper
N Limsopatham, O Rokhlenko, D Carmel – Proceedings of the 2018 …, 2018 – aclweb.org
… 1998), sequence-to-sequence models (eg Vinyals and Le 2015), reinforcement learning (eg Williams and Young 2007 … cally, in his pioneering work, Weizenbaum (1966) developed the Eliza chatbot agent for … Evaluating quality of chatbots and intelligent con- versational agents …

Alquist: The alexa prize socialbot
J Pichl, P Marek, J Konrád, M Matulík… – arXiv preprint arXiv …, 2018 – arxiv.org
… Eliza [2] is one of the most famous chat-bots from that era … The system combines machine learning (Sequence-to-Sequence Models) and rule based modules (Structured Topic … 10] Williams, JD; Young, S. Partially observable Markov decision processes for spoken dialog systems …

Personalizing Dialogue Agents: I have a dog, do you have pets too?
S Zhang, E Dinan, J Urbanek, A Szlam, D Kiela… – arXiv preprint arXiv …, 2018 – arxiv.org
… Our goal is to enable interesting direc- tions for future research, where chatbots can for instance … Generative PersonaChat Models Seq2Seq None 3.17(1.10) 3.18(1.41) 2.98(1.45) 0.51(0.50) … We also evaluate the scores of hu- man performance by replacing the chatbot with a …

A Goal-oriented Neural Conversation Model by Self-Play
W Wei, QV Le, AM Dai, LJ Li – 2018 – openreview.net
… information, we can potentially leverage knowledge of a much larger scale and train a much more reliable chatbot … The introduction of the seq2seq modeling (Sutskever et al., 2014) and the idea of transforming the dialogue … Sequence to sequence learning with neural networks …

Conversational model adaptation via KL divergence regularization
J Li, P Luo, F Lin, B Chen – Thirty-Second AAAI Conference on Artificial …, 2018 – aaai.org
… Specifically, for the building of a new chatbot, it leverages not only a lim- ited amount of training data from this target domain, but also some existing conversational models … In other words, chat- bot users may ask similar questions to the two chatbots from related vertical …

Conversation Modeling with Neural Network
JY Patil, GP Potdar – Asian Journal of Research in Computer …, 2018 – journalajrcos.com
… seq-2-seq[1] illustrated ability of multi-layer LSTM RNN to achieve good performance on Machine Translation tasks … [h] Fig. 2. Example, use of seq2seq framework for conversational modeling … Sequence- to-Sequence Learning as Beam- Search Optimization …

Response selection from unstructured documents for human-computer conversation systems
Z Yan, N Duan, J Bao, P Chen, M Zhou, Z Li – Knowledge-Based Systems, 2018 – Elsevier
… Side-by-side evaluation between DocChat and a famous chatbot demonstrates that DocChat … Vinyals and Le [18] propose a sequence-to-sequence framework where in the post utterance is … However, Seq2Seq based methods tend to generate safe but trivial responses, such as …

Can You be More Polite and Positive? Infusing Social Language into Task-Oriented Conversational Agents
YC Wang, R Wang, G Tur, H Williams – alborz-geramifard.com
… some researchers have studied how to incorporate social language into chatbots to generate … Among all types of deep learning architectures, a sequence-to-sequence learning approach (seq2seq … by inserting a social language understanding layer into a typical seq2seq model …

Intelligence Is Asking The Right Question: A Study On Japanese Question Generation
L Nio, K Murakami – 2018 IEEE Spoken Language Technology …, 2018 – ieeexplore.ieee.org
… its applications involve a vast amount of domains such as a chatbot component in … And we are among the first to employ a deep sequence-to-sequence learning approach to … NLP tasks, ranging from sequence gen- eration for Twitter2 to chat-oriented dialog system response [38 …

Building Advanced Dialogue Managers for Goal-Oriented Dialogue Systems
V Ilievski – arXiv preprint arXiv:1806.00780, 2018 – arxiv.org
… These models are trained in a sequence-to-sequence fashion [Sutskever et al., 2014], that encode the user … On the other hand, we can model the GO Chatbots as a Partially Observable Markov … Figure 3.2 shows a typical composition of an RL-based GO Chatbot, as well as the …

Emotional Human Machine Conversation Generation Based on SeqGAN
X Sun, X Chen, Z Pei, F Ren – 2018 First Asian Conference on …, 2018 – ieeexplore.ieee.org
… The purpose of our emotional tags is to make the chatbot understood the emotion of the input … Generative Model of our GAN network is a simple Seq2Seq model to generate the response of the post … [3] I. Sutskever, O. Vinyals, and QV Le, “Sequence to sequence learning with …

Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints
A Baheti, A Ritter, J Li, B Dolan – arXiv preprint arXiv:1809.01215, 2018 – arxiv.org
… Such re- sponse generation models could be combined with traditional dialogue systems to enable more natu- ral and adaptive conversation, in addition to new … As a starting point for our approach we leverage the Seq2Seq model (Sutskever et al., 2014; Bah- danau et al., 2014 …

A Knowledge-Grounded Multimodal Search-Based Conversational Agent
S Agarwal, O Dusek, I Konstas, V Rieser – arXiv preprint arXiv:1810.11954, 2018 – arxiv.org
… ubiquitous, with variants ranging from open-domain conversa- tional chit-chat bots (Ram et … Our model belongs to the encoder-decoder paradigm where sequence-to-sequence models (Cho … on the task of textual response generation in multimodal task-oriented dialogue system …

Policy learning for task-oriented dialogue systems via reinforcement learning techniques
C Yin – 2018 – minerva-access.unimelb.edu.au
… Context-Uncertainty- Aware Chatbot Action Selection via Parameterized Auxiliary Reinforcement Learning. In Proc … However, DST plays a determinant role in task-oriented dialogue systems. If dialogue states are not accurately tracked, the dialogue system …

Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize
C Khatri, B Hedayatnia, A Venkatesh, J Nunn… – arXiv preprint arXiv …, 2018 – arxiv.org
… Anaphora and Co-reference Resolution: Multi-turn dialog systems need to resolve ambiguous phrases … to text, is the first component a user interacts with in a spoken dialog system … Evaluation of dialogue systems is a challenging research problem, which despite being studied …

Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications
CR Rao, VN Gudivada – 2018 – books.google.com
… Short-Term Memory and Gated RNNs 6.6 Encoder-Decoder Sequence-to-Sequence Architectures 6.7 … textual entail- ment, language generation, semantic analysis, grammar correction, question- answering systems, spoken dialog systems, chatbots, passage retrieval …

A Study on Dialogue Reward Prediction for Open-Ended Conversational Agents
H Cuayáhuitl, S Ryu, D Lee, J Kim – arXiv preprint arXiv:1812.00350, 2018 – arxiv.org
… 7]. [17] train a neural multiclass classifier and linear regressor from human-chatbot dialogues from … two dialogue turns, r1 and r3 refer to likelihood outputs of Seq2Seq models, r2 … Future conversational agents or chatbots can optimise their behaviour using neural regressors with …

Exemplar encoder-decoder for neural conversation generation
G Pandey, D Contractor, V Kumar, S Joshi – Proceedings of the 56th …, 2018 – aclweb.org
… With the availability of large datasets and the recent progress made by neural meth- ods, variants of sequence to sequence learning (seq2seq) (Sutskever et al., 2014) architectures have been successfully applied for building con- versational systems (Serban et al., 2016, 2017b …

Response Generation For An Open-Ended Conversational Agent
N Dziri – 2018 – era.library.ualberta.ca
… 25 2.4.1 Chatbot systems … ground for the data-driven approaches to become feasible and quite promis- ing. In particular, Sequence-to-Sequence (Seq2Seq) neural networks model [105] has witnessed substantial breakthroughs in enhancing the performance …

Natural answer generation with heterogeneous memory
Y Fu, Y Feng – Proceedings of the 2018 Conference of the North …, 2018 – aclweb.org
… In real-world applications like chatbots or personal assistants, users may want to … Natural Answer Generation with Sequence to Sequence Learning: Sequence to sequence mod- els (with attention … Memory is an effective way to equip seq2seq systems with external information …

Building a conversational agent overnight with dialogue self-play
P Shah, D Hakkani-Tür, G Tür, A Rastogi… – arXiv preprint arXiv …, 2018 – arxiv.org
… with just a task schema and an API client from the dialogue system developer, but it … is important when developing datasets to benchmark research aimed towards building human-level dialogue systems. However, we ar- gue that for consumer-facing chatbots, the primary aim is …

The RLLChatbot: a solution to the ConvAI challenge
N Gontier, K Sinha, P Henderson, I Serban… – arXiv preprint arXiv …, 2018 – arxiv.org
… Many chatbots have been proposed for this challenge, overall they all rely on modern deep learning and … column) between a human user (Ui:) and the chatbot (Bi … The second generative sequence-to-sequence model used in the ensemble is the Neural Question Generator (NQG …

Response ranking with deep matching networks and external knowledge in information-seeking conversation systems
L Yang, M Qiu, C Qu, J Guo, Y Zhang… – The 41st International …, 2018 – dl.acm.org
… $15.00 https://doi.org/10.1145/3209978.3210011 used1. These systems, with either text-based or voice-based con- versational interfaces, are capable of voice interaction, information search, question answering and voice control of smart devices …

Emotional dialogue generation using image-grounded language models
B Huber, D McDuff, C Brockett, M Galley… – Proceedings of the 2018 …, 2018 – dl.acm.org
… Visual Question Answering CHI 2018 Paper CHI 2018, April 21–26, 2018, Montréal, QC, Canada … The previous conversation may consist of one or multiple turns. A widely adopted DNN approach to this problem is a sequence-to-sequence architecture (seq2seq) [41, 46, 25] …

Deep Neural Language Generation with Emotional Intelligence and External Feedback
V Srinivasan – 2018 – search.proquest.com
… interpret in more human ways. Ebay has it’s own chatbot that acts as a shopping assistant and helps customers in … which we will use as our final response. One of the most important characteristics of sequence to sequence models is the … Seq2Seq models provide this flexibility …

Analysis, discovery and exploitation of open data for the creation of question-answering systems
G Molina Gallego – 2018 – rua.ua.es
… Chatbots have been become more popular from the last two decades, actually, many companies use these … To better understand the potential of a chatbot, it is needed to know their origin. A Dialogue System or CA aims to create comprehensive systems that can hold a real …

Conversational ai: The science behind the alexa prize
A Ram, R Prasad, C Khatri, A Venkatesh… – arXiv preprint arXiv …, 2018 – arxiv.org
… the goal of a user for a given utterance, and the dialog system needs to … There are four main types of approaches for response generation in dialog systems: template/rule … shown promising results in the past couple of years, usually with sequence-to-sequence approaches with …

Natural Language Generation with Neural Variational Models
H Bahuleyan – arXiv preprint arXiv:1808.09012, 2018 – arxiv.org
… 2.2.9 Dialog Systems … In this research, we work with deep neural network models known as sequence-to-sequence (Seq2Seq) models that take a sentence as input and … Consider a conversational system such as a chatbot, where x is the line input by the user and y is the line …

Polite dialogue generation without parallel data
T Niu, M Bansal – Transactions of the Association of Computational …, 2018 – MIT Press
… Most current chatbots and conversational mod- els lack any such style, which can be a … Our base dialogue model is a simple sequence-to- sequence (Seq2seq) model that consists of a two- layer bi … fusion ratio ? is a hyperparameter that in- dicates how much Seq2seq output will …

Rich short text conversation using semantic-key-controlled sequence generation
K Yu, Z Zhao, X Wu, H Lin, X Liu – IEEE/ACM Transactions on Audio …, 2018 – dl.acm.org
… Index Terms—Question and answer, chatbot, short text conversation (STC), sequence to sequence learning … sequence and ct is final context vector at time t. Sequence-to-sequence learning with … applied to many tasks, such as machine translation [7], question answering [15] and …

Natural language generation for commercial applications
A van de Griend, W OOSTERHEERT, T HESKES – 2018 – ru.nl
… 4.1 The sequence-to-sequence model … of these applications (see section 6.1) and realised that, in terms of NLG, not much has changed since the first chatbot, Eliza (Weizenbaum … (2017) such that it may be used to improve responses from retrieval-based chatbots (section 8.3) …

Improving retrieval modeling using cross convolution networks and multi frequency word embedding
G An, M Shafiee, D Shamsi – arXiv preprint arXiv:1802.05373, 2018 – arxiv.org
… To build a satisfying chatbot that has the abil- ity of managing a goal-oriented multi-turn di- alogue … 2016) found that the automated dialogue systems built using … This confirms that further investigation in re- trieval dialogue system using this dataset is worth- while and motivates us …

Ask No More: Deciding when to guess in referential visual dialogue
R Shekhar, T Baumgartner, A Venkatesh… – arXiv preprint arXiv …, 2018 – arxiv.org
… Vision community exploits encoder- decoder architectures (Sutskever et al., 2014) — which have shown some promise for modelling chatbot- style dialogue … 2014. Sequence to sequence learning with neural networks … POMDP-based statistical spoken dialog systems: A review …

A Neural Generation-based Conversation Model Using Fine-grained Emotion-guide Attention
Z Zhou, M Lan, Y Wu – 2018 International Joint Conference on …, 2018 – ieeexplore.ieee.org
… In recent years, the generation-based systems usu- ally adopt the sequence to sequence (Seq2seq) [3] models … diverse, content correlation and human-like emotion than the baseline Seq2seq model … framework for multi-turn response selection in retrieval-based chatbots,” in ACL …

Jointly Learning to See, Ask, and GuessWhat
A Venkatesh, R Shekhar, T Baumgärtner… – arXiv preprint arXiv …, 2018 – arxiv.org
… Follow- ing approaches to non-goal-oriented chatbots (Vinyals and Le 2015; Sordoni et al … 2016b) that model dialogue as a sequence- to-sequence problem (Sutskever, Vinyals, and Le 2014 … an RNN that is jointly optimised with other components of the dialogue system — in our …

A Bi-Encoder LSTM Model for Learning Unstructured Dialogs
D Shekhar – 2018 – digitalcommons.du.edu
… growing rapidly. A Dialog System can communicate with human in text, speech or both and can be classified into – Task-oriented Systems and Chatbot Systems. Task-oriented systems are designed for a particular task and set up to have short con …

Alexa Prize-State of the Art in Conversational AI
C Khatri, A Venkatesh, B Hedayatnia, A Ram… – AI …, 2018 – search.proquest.com
… the goal of a user for a given utter- ance, and the dialogue system needs to … WiseMacaw developed a two-layer chatbot framework that can be described as a metagame … have shown promising results in the past couple of years, usually with sequence-to-sequence approach- es …

Beyond” How may I help you?”: Assisting Customer Service Agents with Proactive Responses
M Wan, X Chen – arXiv preprint arXiv:1811.10686, 2018 – arxiv.org
… study the problem of providing recommended responses to customer service agents in live-chat dialogue systems … Most existing methods of ‘smart replies’ seek to build a sequence-to-sequence or a … task as a candidate ranking problem; 2) different from the chatbot system (Cui …

Gunrock: Building A Human-Like Social Bot By Leveraging Large Scale Real User Data
CY Chen, D Yu, W Wen, YM Yang, J Zhang, M Zhou… – m.media-amazon.com
… In comparison, social chatbots require in-depth communication skills with emotional support[21] … We trained a sequence to sequence model [24] using the Cornell Movie-Quotes Corpus [5 … Backstory and EVI to answer general facts and background questions about our chatbot …

Efficient Visual Dialog Policy Learning via Positive Memory Retention
R Zhao, V Tresp – nips2018vigil.github.io
… The training of chat-bots using on-policy policy gradient methods requires numerous training samples … End-to-end optimization of goal-driven and visually grounded dialogue systems … Sequence to sequence learning with neural networks …

Multimodal Differential Network for Visual Question Generation
BN Patro, S Kumar, VK Kurmi… – arXiv preprint arXiv …, 2018 – arxiv.org
… Current dialog systems as evaluated in (Chattopadhyay et al., 2017) show that when trained between bots … question is an interesting and challenging task for a smart robot (like chat-bot) … Our method is based on a sequence to sequence network (Sutskever et al., 2014; Vinyals et …

Data Augmentation for Neural Online Chat Response Selection
W Du, AW Black – arXiv preprint arXiv:1809.00428, 2018 – arxiv.org
… (Yang et al., 2017) adopt a seq2seq model (Sutskever … 2014. Sequence to sequence learning with neural net- works … 2016. Sequential matching network: A new architecture for multi-turn response selec- tion in retrieval-based chatbots. arXiv preprint arXiv:1612.01627. Page 7 …

KITE: Building conversational bots from mobile apps
TJJ Li, O Riva – Proceedings of the 16th Annual International …, 2018 – dl.acm.org
… 1 INTRODUCTION The promise and excitement around conversational chatbots, or sim- ply bots, has … During execution the chatbot tries to fill the slots for a target intent by … work has attempted to use neural networks to solve general sequence- to-sequence learning problems in …

Tartan: A retrieval-based socialbot powered by a dynamic finite-state machine architecture
G Larionov, Z Kaden, HV Dureddy… – arXiv preprint arXiv …, 2018 – arxiv.org
… in human-machine spoken language interaction had focused on goal-oriented dialog systems … of a more traditional sequence-to-sequence model was that most sequence-to- sequence models fail to … We picked question-answer pairs as the training dataset and used StarSpace …

Efficient Purely Convolutional Text Encoding
S Malik, A Lancucki, J Chorowski – arXiv preprint arXiv:1808.01160, 2018 – arxiv.org
… Such approaches have been applied by participants of recent chat- bot contests: The 2017 Alexa … assess how the results for those tasks transfer to the actual dialogue system, we have … Wikiquotes, using a method similar to the one used in Poetwannabe chatbot [Chorowski et al …

A Face-to-Face Neural Conversation Model
H Chu, D Li, S Fidler – … of the IEEE Conference on Computer …, 2018 – openaccess.thecvf.com
… Dialogue systems have been explored since the 60′, with systems like ELIZA [34] and PARRY [5] already capable of engaging in relatively … Text(Face): The classic Seq2Seq [12, 27] method that uses single modality only (either text or face) and only the … The NeuralHank Chatbot …

SlugBot: Developing a Computational Model and Framework of a Novel Dialogue Genre
KK Bowden, J Wu, W Cui, J Juraska, V Harrison… – dex-microsites-prod.s3.amazonaws …
… Discourse coherence in SCRIPT MODEL dialogue systems is created by the user interaction designer … Other existing retrieval based chatbots also operate on large existing corpora such as … Negative users, we would suggests some resources in our dialogue system to improve …

Deep Context Resolution
J Chen – 2018 – uwspace.uwaterloo.ca
… To go beyond one-round con- versation, a chatbot must resolve contextual information … It has been applied on Image Generation [18], Sequence-to-Sequence learning [43] and … Language data from Community Question Answering (cQA) websites fit our purpose perfectly since 1 …

Chatbot integration within Sitecore Experience Platform
G Albertengo, R Di Vittorio – webthesis.biblio.polito.it
… 30 2.2 How the chatbots work … 27 2.1 DeepQA Architecture . . . . . 34 2.2 Finite-state machine for task-oriented chatbot . . . . . 39 2.3 Sequence to sequence model for answers generation . . 54 3.1 Azure Bot Service …

Content-Oriented User Modeling for Personalized Response Ranking in Chatbots
B Liu, Z Xu, C Sun, B Wang, X Wang, DF Wong… – IEEE/ACM Transactions …, 2018 – dl.acm.org
… The personalized chat is a newly emerging demand in the research on chatbot; thus, little … For the scenario of chatbots, the situation is even worse: it is impossible to … that the sentence embedding component is fixed and pre-trained by sequence-to-sequence language model …

Selecting and Generating Computational Meaning Representations for Short Texts
C Finegan-Dollak – 2018 – deepblue.lib.umich.edu
… 136 6.2 Accuracy of seq2seq models with and without schema attention and copying. . 138 … of as communicating the most important parts of a text’s meaning. Question answering involves identifying a particular relationship between the meanings of two texts: one an …

Community Regularization of Visually-Grounded Dialog
A Agarwal, S Gurumurthy, V Sharma, M Lewis… – arXiv preprint arXiv …, 2018 – ri.cmu.edu
… 24]), image segmentation ([18], [9], [22]), dialog ([28], [31], [5]), question answering ([38], [27 … different domains, it now seems plausible to build more advanced dialog systems capable of … prob- lem using supervised learning where, conditioned on the question – answer pair dialog …

The bottleneck simulator: a model-based deep reinforcement learning approach
IV Serban, C Sankar, M Pieper, J Pineau… – arXiv preprint arXiv …, 2018 – arxiv.org
Page 1. arXiv:1807.04723v1 [cs.LG] 12 Jul 2018 The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach Iulian Vlad Serban1 Chinnadhurai Sankar 1 Michael Pieper1 Joelle Pineau2 Yoshua Bengio 1 Abstract …

Visual questioning agents
U Jain – 2018 – ideals.illinois.edu
… This helps AI systems such as driving assistants, chatbots, etc., to perform better on Turing tests. An AI sys … question-answer pairs. While this largely resembles the visual question answering task, a variety of different approaches have been proposed recently. 6 Page 13 …

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
I Gurevych, Y Miyao – Proceedings of the 56th Annual Meeting of the …, 2018 – aclweb.org
… The application of Deep Neural Networks to Visual Question Answering has achieved results that would have been thought impossible only a few years ago … Graham Neubig Hai Zhao Question Answering Lluís Màrquez Teruko Mitamura Zornitsa Kozareva Richard Socher …

Analysing Seq-to-seq Models in Goal-oriented Dialogue: Generalising to Disfluencies.
S Bouwmeester – 2018 – esc.fnwi.uva.nl
… range of applications, such as technical support services, digital personal assistants, chat bots, and home … A normal sequence to sequence model with attention can be seen as a memory network with … A marked example of this is Microsoft’s AI-based chat-bot named Tay, who …

Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN
P Khurana, P Agarwal, G Shroff, L Vig – Proceedings of the 24th ACM …, 2018 – dl.acm.org
… ABSTRACT Recent proliferation of conversational systems has resulted in an increased demand for more natural dialogue systems, capable of more … Dialogue and Question Answering: Broadly there are six types of conversational systems present in research litera- ture …

Hands-On Natural Language Processing with Python: A practical guide to applying deep learning architectures to your NLP applications
R Arumugam, R Shanmugamani – 2018 – books.google.com
… Chatbot’s are becoming an integrated part of any website; while virtual assistants … 21 Coreference resolution 21 Searching 22 Question answering and chatbots 23 Converting … using GRU Data preparation Encoder network Decoder network Sequence to sequence Building the …

Natural Language Processing and Chinese Computing: 7th CCF International Conference, NLPCC 2018, Hohhot, China, August 26–30, 2018, Proceedings
M Zhang, V Ng, D Zhao, S Li, H Zan – 2018 – books.google.com
… in eight key areas, including NLP Fundamentals (Syntax, Semantics, Discourse), NLP Applications, Text Mining, Machine Translation, Machine Learning for NLP, Information Extraction/Knowledge Graph, Conversational Bot/Question Answering/Information Retrieval, and NLP …

Sentiment classification using N-ary tree-structured gated recurrent unit networks
V Tsakalos, R Henriques – Proceedings of the 10th International Joint …, 2018 – run.unl.pt
… Artificial Neural Networks have achieved state-of-art perfor- mance at Question-Answering tasks (Berant and Li- ang, 2014), Dialogue agents(Chat-bots)(Young et al … Sequence to sequence learning with neural networks … POMDP-based statistical spoken dialog systems: A review …

The Natural Auditor: How To Tell If Someone Used Your Words To Train Their Model
C Song, V Shmatikov – arXiv preprint arXiv:1811.00513, 2018 – arxiv.org
… of chatbots, question-answering services, automated customer service, and other dialog-based systems. The input is a sentence in a conversation, the output is the next sentence in the same conversation. Dialog-generation models typically employ a sequence-to-sequence …

Emory IrisBot: An Open-Domain Conversational Bot for Personalized Information Access
A Ahmadvand, IJ Choi, H Sahijwani, J Schmidt, M Sun… – m.media-amazon.com
… employs proactive recommendation strategies, simulated emotion, and incorporate sequence to sequence learning to … all Chat component, which was based on the ALICE chatbot, implemented in … Candidate question-answer pairs are retrieved and re-ranked by the combination …

Design and development of Rexy: a virtual teaching assistant for on-site and online courses
M PARENTI – 2018 – politesi.polimi.it
… suggests that models based on recurrent neural networks and sequence-to-sequence models … lives. 1.1.2 Application of Current Chatbot Technologies The most popular and pervasive chatbots or digital assistants are the ones em …

Adversarial Over-Sensitivity and Over-Stability Strategies for Dialogue Models
T Niu, M Bansal – arXiv preprint arXiv:1809.02079, 2018 – arxiv.org
… It consists of a dynamic knowledge graph, a graph embedding over the entity nodes, and a Seq2seq-based utterance generator … 1902; Marqués-Aguado, 2014); it is also frequently seen in blog posts.3 Thus, being robust to swapping adjacent words is useful for chatbots that take …

Toward zero-shot entity recognition in task-oriented conversational agents
M Guerini, S Magnolini, V Balaraman… – Proceedings of the 19th …, 2018 – aclweb.org
… recognition. Task-oriented dialogue. E-commerce chat-bots are supposed to carry on a task-oriented dialogue whose goal is helping the user to select products presented in an online shop, and, ultimately, buy them. For the …

Task-Oriented Dialog Agents Using Memory-Networks and Ensemble Learning
RFG Meléndez – 2018 – pdfs.semanticscholar.org
… et al., 2015) make no further classification than task-oriented or non task-oriented chatbots, Jurafsky and Martin (2018) use the term chatbot exclusively for … This is a scenario commonly tackled with sequence-to-sequence models that build an entire phrase word by word …

Alquist 2.0: Alexa Prize Socialbot Based on Sub-Dialogue Models
J Pichl, CTU FEE, P Marek, J Konrád, M Matulík… – dex-microsites-prod.s3.amazonaws …
… This paper presents the second version of the dialogue system named Alquist com- peting in Amazon … It is used to test end-to-end dialog systems in a way that favors reproducibility … is the only task which contains records of real-world conversations between humans and chatbot …

Amanuensis: The Programmer’s Apprentice
T Dean, M Chiang, M Gomez, N Gruver, Y Hindy… – arXiv preprint arXiv …, 2018 – arxiv.org
… Figure 2: The sequence-to-sequence encoder-decoder attentional model shown here uses a specialized mem- ory called a pointer network to construct a short summary of a source document by flexibly combining phrases from the source document with words from its existing …

BYU-EVE: Mixed Initiative Dialog via Structured Knowledge Graph Traversal and Conversational Scaffolding
N Fulda, T Etchart, W Myers, D Ricks, Z Brown… – dex-microsites-prod.s3.amazonaws …
… This type of interaction encompasses, but also goes beyond, database queries and question/answer models … Ultimately, a dialog system exists to generate text … Page 10. sentences. (In theory, this task could also be attempted using a sequence-to-sequence model …

Deep Semantic Learning for Conversational Agents
M Morisio, M Mensio – 2018 – webthesis.biblio.polito.it
… 37 2.2.6 Sequence-to-sequence models for slot tagging … has been conducted, an introduction to the topic of Conversational Agents (also known as Chatbots or Bots … The problem where this approach is applied is Question-Answering on synthesized images [45], and the focus is …

Cognitive architecture of multimodal multidimensional dialogue management
A Malchanau – 2018 – d-nb.info
… designs based on a reactive interlocutor paradigm and calls for dialog systems that can be … template-based Table 1.1: State-of-the-art techniques for task-oriented dialogue system … information-transfer tasks and end-to-end approaches handle well chatbot conversations, they …

Artificial Intelligence for All: An Abiding Destination
V Pathak, P Tiwari – 2018 – books.google.com
Page 1. ARTIFICIAL INTELLIGENCE FOR ALL AN ABIDING DESTINATION º Nº. -º- 2 º nº 2 wº º: DR. PANKAT TIWARI VIKAS PATHAIK Page 2. Artificial Intelligence For All Artificial Intelligence For All i Page 3. Artificial Intelligence …

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