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Progresses of Response Generation (Other (Topic Aware Neural Response…
Progresses of Response Generation
Knowledge
A knowledge-grounded neural conversation model
Incorporating loose-structured knowledge into LSTM with recall gate for conversation modeling
A neural network approach for knowledge-driven response generation
Commonsense Knowledge Aware Conversation Generation with Graph Attention.
Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems
Knowledge diffusion for neural dialogue generation
Augmenting end-to-end dialog systems with commonsense knowledge
Extending Neural Generative Conversational Model using External Knowledge Sources
GAN&RL
Deep reinforcement learning for dialogue generation
Adversarial learning for neural dialogue generation
Hybrid code networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
Investigating Deep Reinforcement Learning Techniques in Personalized Dialogue Generation
Multi-turn Dialogue Response Generation in an Adversarial Learning Framework
Retrieval-Enhanced Adversarial Training for Neural Response Generation
Poor, Just add the retrieval N best to the discriminator of Li et. al REGS
DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text
Adversarial ranking for language generation
Long text generation via adversarial training with leaked information
Texygen: A Benchmarking Platform for Text Generation Models
Adversarially Regularized Autoencoders
Neural response generation via gan with an approximate embedding layer
BootstrappingaNeuralConversationalAgentwithDialogueSelf-Play, CrowdsourcingandOn-LineReinforcementLearning
Classic Models
Neural Responding Machine for Short-Text Conversation
We consider three types of encoding schemes, namely 1) the global scheme, 2) the local scheme, and the hybrid scheme which combines 1) and 2).
attention
A Neural Conversational Model
Dialog-based Language Learning
LSTM based Conversation Models
In this paper, we present a conversational model that incorporates both context and participant role for two-party conversations
Context: a topic vector representing all previous dialog turns. We use Latent Dirichlet Allocation (LDA) to achieve a compact vector-space representation
Role: to capture the variability from different participant roles, we incorporate rolebased information into the generation procedure
Data-driven response generation in social media
Datasets
OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles
A Survey of Available Corpora For Building Data-Driven Dialogue Systems
DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
The Ubuntu Dialogue Corpus: A Large Dataset for Researchin Unstructured Multi-Turn Dialogue Systems
Towards Continuous Dialogue Corpus Creation: writing to corpus and generating from it.
LSDSCC: A Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics
Code
RL
Sentence Modeling
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation
Attention with intention for a neural network conversation model
Multi-view response selection for human-computer conversation
Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots
Ranking responses oriented to conversational relevance in chat-bots
Get The Point of My Utterance! Learning Towards Effective Responses with Multi-Head Attention Mechanism.
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Self-Attention-Based Message-Relevant Response Generation for Neural Conversation Model
A Hybrid-Level Encoder-Decoder for Neural Response Generation
Diversity
A Diversity-Promoting Objective Function for Neural Conversation Models
Why Do Neural Response Generation Models Prefer Universal Replies?
A Simple, Fast Diverse Decoding Algorithm for Neural Generation
Generating Long and Diverse Responses with Neural Conversation Models
Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation
Tailored Sequence to Sequence Models to Different Conversation Scenarios
Diversifying Neural Conversation Model with Maximal Marginal Relevance
Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation
Why are Sequence-to-Sequence Models So Dull? Understanding the Low-Diversity Problem of Chatbots
MEMD: A Diversity-Promoting Learning Framework for Short-Text Conversation
Generating high-quality and informative
conversation responses with sequence-to-sequence models
Diverse beam search: Decoding diverse solutions from neural sequence models
Interpretation
Dialogue-act-driven Conversation Model: An Experimental Study
Towards Interpretable Chit-chat: Open Domain Dialogue Generation with Dialogue Acts
Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation
Towards Explainable and Controllable Open Domain Dialogue Generation with Dialogue Acts
Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation
Global-Locally Self-Attentive Encoder for Dialogue State Tracking
Dialogue-act-driven Conversation Model: An Experimental Study
Evaluation
Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generation
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation
Ruber: An unsupervised method for automatic evaluation of open-domain dialog systems
Adversarial evaluation for open-domain dialogue generation
Towards an automatic Turing test: Learning to evaluate dialogue responses
deltaBLEU: A discriminative metric for generation tasks with intrinsically diverse targets
Other
Topic Aware Neural Response Generation.
Stalematebreaker: A proactive content-introducing approach to automatic human-computer conversation
Coherent Dialogue with Attention-Based Language Models.
Addressee and response selection for multi-party conversation
Smarter Response with Proactive Suggestion: A New Generative Neural Conversation Paradigm.
Modeling situations in neural chat bots
Learning to Converse with Noisy Data: Generation with Calibration.
Affective Neural Response Generation
Neural Response Generation with Dynamic Vocabularies
Chat Response Generation Based on Semantic Prediction Using Distributed Representations of Words
Reinforcing Coherence for Sequence to Sequence Model in Dialogue Generation.
Exemplar Encoder-Decoder for Neural Conversation Generation
Data Distillation for Controlling Specificity in Dialogue Generation
Deep active learning for dialogue generation
A Dual Encoder Sequence to Sequence Model for Open-Domain Dialogue Modeling
Semantically conditioned lstm-based natural language generation for spoken dialogue systems
To plan or not to plan? sequence to sequence generation for language generation in dialogue systems
Towards implicit content-introducing for generative short-text conversation systems
Natural Language Generation by Hierarchical Decoding with Linguistic Patterns
Conversation modeling on reddit using a graph-structured LSTM
Modeling multi-turn conversation with deep utterance aggregation
DialogGenerationUsingMulti-turnReasoningNeuralNetworks
Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints
Topic-enhanced emotional conversation generation with attention mechanism
Simplified Hierarchical Recurrent Encoder-Decoder for Building End-To-End Dialogue Systems
A topic-driven language model for learning to generate diverse sentences
Personality
Conversational contextual cues: The case of personalization and history for response ranking
Neural personalized response generation as domain adaptation
Neural response generation for customer service based on personality traits
Personalized response generation via domain adaptation
Group Linguistic Bias Aware Neural Response Generation
A persona-based neural conversation model
Personalized Review Generation by Expanding Phrases and Attending on Aspect-Aware Representations
Exploring Personalized Neural Conversational Models.
Exploring Personalized Neural Conversational Models.
IR&Generative
Docchat: An information retrieval approach for chatbot engines using unstructured documents
Two are better than one: An ensemble of retrieval-and generation-based dialog systems
Alime chat: A sequence to sequence and rerank based chatbot engine
Neural utterance ranking model for conversational dialogue systems
Emulating human conversations using convolutional neural network-based IR
Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System
Response selection with topic clues for retrieval-based chatbots
Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots
An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems.
Learning to respond with deep neural networks for retrieval-based human-computer conversation system
Retrieve and Refine: Improved Sequence Generation Models For Dialogue
An information retrieval approach to short text conversation
Retrieve and Refine Improved Sequence Generation Models For Dialogue
Generic, Retrieval Response as context
Skeleton-to-Response Dialogue Generation Guided by Retrieval Memory
Response generation by context-aware prototype editing
Emotion
Emotional Human-Machine Conversation Generation Based on Long Short-Term Memory
Emotional Dialogue Generation using Image-Grounded Language Models
Emotional Conversation Generation Orientated Syntactically Constrained Bidirectional-asynchronous Framework
An emotion-based responding model for natural language conversation
Emotional chatting machine: Emotional conversation generation with internal and external memory
MojiTalk: Generating Emotional Responses at Scale
Emotional Conversation Generation Orientated Syntactically Constrained Bidirectional-asynchronous Framework
Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation.
Multi-Media
ChatPainter: Improving Text to Image Generation using Dialogue
GuessWhat?! Visual object discovery through multi-modal dialogue.
Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder
Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems
Image-grounded conversations: Multimodal context for natural question and response generation
VAE
A conditional variational framework for dialog generation
A Hierarchical Latent Structure for Variational Conversation Modeling
Latent variable dialogue models and their diversity
Improving Variational Encoder-Decoders in Dialogue Generation
A Hybrid Convolutional Variational Autoencoder for Text Generation
Generating Sentences from a Continuous Space
Variational lossy autoencoder
Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
Context&Memory
Coupled context modeling for deep chit-chat: towards conversations between human and computer
Detecting Context Dependent Messages in a Conversational Environment
Hierarchical Variational Memory Network for Dialogue Generation
Memory-Based Matching Models for Multi-turn Response Selection in Retrieval-Based Chatbots
How to make context more useful? an empirical study on context-aware neural conversational models
A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
End-to-End Memory Networks for Contextual Language Understanding
Remembering a Conversation–A Conversational Memory Architecture for Embodied Conversational Agents
Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory
Review
Generative deep neural networks for dialogue: A short review
A survey on dialogue systems: Recent advances and new frontiers
Deep Learning Based Chatbot Models
Style
Mechanism-Aware Neural Machine for Dialogue Response Generation.
Generating Stylistically Consistent Dialog Responses with Transfer Learning
Elastic responding machine for dialog generation with dynamically mechanism selecting
Generating Informative Responses with Controlled Sentence Function
Learning to Control the Specificity in Neural Response Generation
Steering output style and topic in neural response generation
Unsupervised Text Style Transfer using Language Models as Discriminators
Break Detection
Find the Conversation Killers: a Predictive Study of Thread-ending Posts
Breakdown Detector for Chat-Oriented Dialogue
Dialogue breakdown detection based on estimating appropriateness of topic transition
Predicting Users' Negative Feedbacks in Multi-Turn Human-Computer Dialogues
Other2
Low Frequency Words Compression in Neural Conversation System
Role Play Dialogue Aware Language Models Based on Conditional Hierarchical Recurrent Encoder-Decoder
A Prospective-Performance Network to Alleviate Myopia in Beam Search for Response Generation
Not all dialogues are created equal: Instance weighting for neural conversational models