Papers by Xv Wang

2 papers
Causal-ESC: Reliable Policy Learning for Emotional Support Conversation via Causal Inference (2026.acl-long)

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Challenge: Existing approaches to Emotional Support Conversation (ESC) are mechanistically opaque and lacks a causal mechanism between dialogue features and effective empathic strategies.
Approach: They propose a framework that uses Doubly Robust learning to model causal effects of utterance features on strategy selection.
Outcome: The proposed framework outperforms state-of-the-art baselines in empathy and helpfulness and provides a theoretically grounded, interpretable solution to the mechanistic interpretability dilemma in affective computing.
DKME: Rethinking Coupled Knowledge Memory for Lifelong Model Editing of Large Language Models (2026.findings-acl)

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Challenge: Existing memory-based editors suffer from catastrophic forgetting as edits accumulate.
Approach: They propose a method which injects factual updates into large language models without retraining or finetuning into existing memory-based editors.
Outcome: Experiments on HalluEditBench, CKnowEdit, and WikiDatacounterfact show that the proposed model achieves a more favorable trade-off between editing success and locality compared to baselines while maintaining more stable performance as the edit scale increases.

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