Papers by Shuhui Wang

2 papers
CTSM: Combining Trait and State Emotions for Empathetic Response Model (2024.lrec-main)

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Challenge: Empathetic response generation attempts to empower dialogue systems to perceive speakers’ emotions and generate empathetic responses accordingly.
Approach: They propose to combine trait and state emotions for Empathetic Response Model to enable dialogue systems to perceive speakers' emotions and generate empathetic responses accordingly.
Outcome: The proposed model outperforms state-of-the-art models and generates more empathetic responses.
A Category-Theoretic Approach to Neural-Symbolic Task Planning with Bidirectional Search (2025.findings-emnlp)

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Challenge: Empirical evaluations demonstrate that our method improves completion rates by up to 6.6% and action accuracy by 9.1% .
Approach: They propose a Neural-Symbolic Task Planning framework that integrates Large Language Model (LLM) decomposition with category-theoretic verification for resource-aware, temporally consistent planning.
Outcome: The proposed framework improves completion rates and action accuracy by up to 6.6% . it also eliminates resource violations while ensuring resource-awareness and consistency.

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