Dialogue Generation
229 papers with code • 14 benchmarks • 31 datasets
Dialogue generation is the task of "understanding" natural language inputs - within natural language processing in order to produce output. The systems are usually intended for conversing with humans, for instance back and forth dialogue with a conversation agent like a chatbot. Some example benchmarks for this task (see others such as Natural Language Understanding) include FusedChat and Ubuntu DIalogue Corpus (UDC). Models can be evaluated via metrics such as BLEU, ROUGE, and METEOR albeit with challenges in terms of weak correlation with human judgement, that may be addressed by new ones like UnSupervised and Reference-free (USR) and Metric for automatic Unreferenced dialog evaluation (MaUde).
Benchmarks
These leaderboards are used to track progress in Dialogue Generation
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Libraries
Use these libraries to find Dialogue Generation models and implementations
Reddit
MultiWOZ
OpenSubtitles
PG-19
UDC
DialogSum
CPED
Latest papers
Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialogue
iwangjian/trip
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Inspired by decision-making theories in cognitive science, we propose a novel target-constrained bidirectional planning (TRIP) approach, which plans an appropriate dialogue path by looking ahead and looking back.
Exploiting Emotion-Semantic Correlations for Empathetic Response Generation
zhouzhouyang520/empatheticdialoguegeneration_escm
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Based on dynamic emotion-semantic vectors and dependency trees, we propose a dynamic correlation graph convolutional network to guide the model in learning context meanings in dialogue and generating empathetic responses.
Parameter-Efficient Conversational Recommender System as a Language Processing Task
ravoxsg/efficient_unified_crs
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Conversational recommender systems (CRS) aim to recommend relevant items to users by eliciting user preference through natural language conversation.
Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys
The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory.
An EcoSage Assistant: Towards Building A Multimodal Plant Care Dialogue Assistant
mohit2b/ecosage
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In recent times, there has been an increasing awareness about imminent environmental challenges, resulting in people showing a stronger dedication to taking care of the environment and nurturing green life.
CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models
In this paper, we present CharacterGLM, a series of models built upon ChatGLM, with model sizes ranging from 6B to 66B parameters.
Think Before You Speak: Cultivating Communication Skills of Large Language Models via Inner Monologue
The emergence of large language models (LLMs) further improves the capabilities of open-domain dialogue systems and can generate fluent, coherent, and diverse responses.
ChiMed-GPT: A Chinese Medical Large Language Model with Full Training Regime and Better Alignment to Human Preferences
synlp/chimed-gpt
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Recently, the increasing demand for superior medical services has highlighted the discrepancies in the medical infrastructure.
PRODIGy: a PROfile-based DIalogue Generation dataset
Providing dialogue agents with a profile representation can improve their consistency and coherence, leading to better conversations.
NoteChat: A Dataset of Synthetic Doctor-Patient Conversations Conditioned on Clinical Notes
We introduce NoteChat, a novel cooperative multi-agent framework leveraging Large Language Models (LLMs) to generate patient-physician dialogues.
