Papers with ESC task

2 papers
AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation (2023.findings-acl)

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Challenge: Crowdsourced dialogue corpora are limited in scale and topic coverage due to the expensive cost of data curation.
Approach: They construct an augmented dataset for the emotional support conversation task using large language models for dialogue augmentation.
Outcome: The proposed approach outperforms baselines of dialogue augmentation and improves the model's generalization ability to open-domain topics.
DecoupledESC: Enhancing Emotional Support Generation via Strategy-Response Decoupled Preference Optimization (2025.findings-emnlp)

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Challenge: Existing ESC data entangles psychological strategies and response content, making it difficult to construct high-quality preference pairs.
Approach: They propose a Decoupled ESC framework that decomposes the ESC task into two sequential subtasks: strategy planning and empathic response generation.
Outcome: The proposed framework outperforms baselines, reducing preference bias and improving response quality.

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