Towards Emotional Support Dialog Systems
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Cited by 31 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Emotional support is a crucial ability for many conversation scenarios, including social interactions, mental health support, and customer service chats. Following reasonable procedures and using various support skills can help to effectively provide support. However, due to the lack of a well-designed task and corpora of effective emotional support conversations, research on building emotional support into dialog systems remains untouched. In this paper, we define the Emotional Support Conversation (ESC) task and propose an ESC Framework, which is grounded on the Helping Skills Theory. We construct an Emotion Support Conversation dataset (ESConv) with rich annotation (especially support strategy) in a help-seeker and supporter mode. To ensure a corpus of high-quality conversations that provide examples of effective emotional support, we take extensive effort to design training tutorials for supporters and several mechanisms for quality control during data collection. Finally, we evaluate state-of-the-art dialog models with respect to the ability to provide emotional support. Our results show the importance of support strategies in providing effective emotional support and the utility of ESConv in training more emotional support systems.
Key facts. Cited by 294 papers in the map (data through 7 Oct 2026). Builds on 18 of its 42 references that are in the map. First posted on arXiv 2 Jun 2021.
Builds on
18 of 42 references.
References · 18
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2019The Curious Case of Neural Text Degenerationcited by 2,881
- 2019DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationcited by 842
- 2017DailyDialog: A Manually Labelled Multi-turn Dialogue Datasetcited by 649
- 2020Recipes for building an open-domain chatbotcited by 593
- 2016How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generationcited by 356
- 2020A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Supportcited by 182
- 2018The Design and Implementation of XiaoIce, an Empathetic Social Chatbotcited by 172
- 2017Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memorycited by 167
- 2019Challenges in Building Intelligent Open-domain Dialog Systemscited by 147
- 2020MIME: MIMicking Emotions for Empathetic Response Generationcited by 114
- 2019MoEL: Mixture of Empathetic Listenerscited by 91
6 more
- 2017MojiTalk: Generating Emotional Responses at Scalecited by 64
- 2017Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generationcited by 61
- 2020Towards Persona-Based Empathetic Conversational Modelscited by 53
- 2021CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generationcited by 42
- 2020EmpTransfo: A Multi-head Transformer Architecture for Creating Empathetic Dialog Systemscited by 19
- 2020Expressive Interviewing: A Conversational System for Coping with COVID-19cited by 10
Built on by
Citing papers per year: 2021: 4; 2022: 24; 2023: 42; 2024: 57; 2025: 68; 2026: 99.
294 papers.
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- 2026Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents21 May 2026
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- 2025MetaMind: Modeling Human Social Thoughts with Metacognitive Multi-Agent Systems25 May 2025
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- 2024Cause-Aware Empathetic Response Generation via Chain-of-Thought Fine-Tuning21 Aug 2024
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- 2021PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Supportcited by 92
- 2022The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systemscited by 92
- 2021CEM: Commonsense-aware Empathetic Response Generationcited by 89
- 2024CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counselingcited by 88
- 2022MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversationcited by 84
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- 2022AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversationcited by 79
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- 2023Building Emotional Support Chatbots in the Era of LLMscited by 62
- 2023Prompt-Based Monte-Carlo Tree Search for Goal-Oriented Dialogue Policy Planningcited by 60
- 2022Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planningcited by 59
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- 2026Evolving Support Priorities in Empathetic Reinforcement Learning28 Sep 2026
- 2026Empath: Tracing Multi-Level Emotion Dynamics in Crisis Counseling Dialogues24 Sep 2026
- 2026From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health21 Sep 2026
- 2026Steering the Compass: Aligning Dynamic Psychological Counseling Conversations with Cognitive Behavioral Therapy Strategies17 Sep 2026
- 2026MOCC-R1: Reinforcing Reasoning-Response Consistency for Multimodal Counselor Response Generation15 Sep 2026
- 2026From Momentary Emotion Inference to Sustained Emotion Support: Evaluating a Companion Agent in a Longitudinal Study14 Sep 2026
- 2026Empathy Is Steerable but Multi-Axial: Mechanism Geometry and Persona Effects in LLMs14 Sep 2026
- 2026Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling27 Aug 2026
- 2026Multi-Expert Conformal Risk Control for Pairwise LLM Judging in Open-Ended Dialogue27 Aug 2026
- 2026ToSCA: Leveraging Hierarchical Reinforcement Learning on Temporal and Strategic Abstractions of Conversational Agents22 Aug 2026
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