Papers by Sibo Zhu

2 papers
Exploiting Emotion-Semantic Correlations for Empathetic Response Generation (2023.findings-emnlp)

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Challenge: Empathetic response generation aims to generate empathetic responses by understanding the speaker’s emotional feelings from the language of dialogue.
Approach: They propose a dynamical Emotion-Semantic Correlation Model (ESCM) which constructs dynamic emotion-semantics through the interaction of context and emotions.
Outcome: The proposed model understands emotions more accurately and expresses fluent and informative empathetic responses.
Hybrid Self-evolving Structured Memory for Computer-Use Agents (2026.findings-acl)

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Challenge: despite advances in vision–language models, real-world computer-use tasks remain challenging due to long-horizon workflows, diverse interfaces, and frequent intermediate errors.
Approach: They propose a graph-based memory that couples discrete symbolic nodes with continuous trajectory embeddings.
Outcome: The proposed system outperforms closed-source models in Qwen2.5-VL-7B and Gemini2.5-Pro-Vision on desktop and mobile platforms.

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