Papers by Guisong Yang

3 papers
ReflectDiffu: Reflect between Emotion-intent Contagion and Mimicry for Empathetic Response Generation via a RL-Diffusion Framework (2025.acl-long)

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Challenge: Existing models for empathetic dialogue generation neglect the intricate interplay between emotion and intent, leading to suboptimal controllability of empathy.
Approach: They propose a framework that integrates emotion contagion and intent mimicry to enhance empathetic response generation.
Outcome: The proposed framework outperforms existing models in relevance, controllability, and informativeness.
Explainable Text Classification with LLMs: Enhancing Performance through Dialectical Prompting and Explanation-Guided Training (2025.findings-emnlp)

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Challenge: Existing explanation methods that generate keywords may be less effective due to missing critical contextual information.
Approach: They propose a new method to generate explanations for possible labels using LLMs and a dialectical prompt.
Outcome: The proposed method significantly improves accuracy and explanation quality over state-of-the-art methods on multiple datasets from diverse domains.
OASIS: Mitigating Harmful Fine-tuning Attacks on LLMs via Orthogonal and Adaptive Safety Alignment Strategy (2026.acl-long)

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Challenge: Existing methods to decouple safety enforcement from harmful feature acquisition rely on perturbation directions that conflict with harmful gradients . harmful fine-tuning attacks pose a significant challenge for service providers aiming to uphold rigorous safety standards.
Approach: They propose an orthogonal and ad hoc safety alignment strategy to decouple safety enforcement from harmful feature acquisition.
Outcome: Experiments on four large language models show that OASIS reduces the Harmful Score by 60% compared to baselines while maintaining stable task utility.

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