mlsanityData to 7 Oct 2026

CauESC: A Causal Aware Model for Emotional Support Conversation

arXiv 2401.17755 ↗First posted 31 Jan 2024cs.CLcited by 4

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Abstract (arXiv)

Emotional Support Conversation aims at reducing the seeker's emotional distress through supportive response. Existing approaches have two limitations: (1) They ignore the emotion causes of the distress, which is important for fine-grained emotion understanding; (2) They focus on the seeker's own mental state rather than the emotional dynamics during interaction between speakers. To address these issues, we propose a novel framework CauESC, which firstly recognizes the emotion causes of the distress, as well as the emotion effects triggered by the causes, and then understands each strategy of verbal grooming independently and integrates them skillfully. Experimental results on the benchmark dataset demonstrate the effectiveness of our approach and show the benefits of emotion understanding from cause to effect and independent-integrated strategy modeling.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 30 of its 66 references that are in the map. First posted on arXiv 31 Jan 2024.

Builds on

30 of 66 references.

References · 30

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18 more
  1. 2020COSMIC: COmmonSense knowledge for eMotion Identification in Conversationscited by 135
  2. 2019Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advancescited by 118
  3. 2020MIME: MIMicking Emotions for Empathetic Response Generationcited by 114
  4. 2015Yara Parser: A Fast and Accurate Dependency Parsercited by 110
  5. 2022MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversationcited by 84
  6. 2019Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Textscited by 82
  7. 2020Recognizing Emotion Cause in Conversationscited by 66
  8. 2022Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planningcited by 59
  9. 2022Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversationcited by 56
  10. 2022A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasetscited by 45
  11. 2021Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causescited by 43
  12. 2022DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generationcited by 35
  13. 2017Hierarchical Recurrent Attention Network for Response Generationcited by 34
  14. 2023TransESC: Smoothing Emotional Support Conversation via Turn-Level State Transitioncited by 30
  15. 2022DxFormer: A Decoupled Automatic Diagnostic System Based on Decoder-Encoder Transformer with Dense Symptom Representationscited by 10
  16. 2021Contextual Fine-to-Coarse Distillation for Coarse-grained Response Selection in Open-Domain Conversationscited by 9
  17. 2021Multi-Task Learning and Adapted Knowledge Models for Emotion-Cause Extractioncited by 8
  18. 2023K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learningcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025IntentionESC: An Intention-Centered Framework for Enhancing Emotional Support in Dialogue Systemscited by 11
  2. 2025Emotional Support with LLM-based Empathetic Dialogue Generationcited by 4
  3. 2026PRCCF: A Persona-guided Retrieval and Causal-aware Cognitive Filtering Framework for Emotional Support Conversationcited by 0
  4. 2026MindTailor: Personalized Emotional Support via Post History-Grounded Case Formulation and Collaborative Refinementcited by 0