Papers by Wenjie Zhuo

3 papers
WhitenedCSE: Whitening-based Contrastive Learning of Sentence Embeddings (2023.acl-long)

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Challenge: Extensive experiments on seven semantic textual similarity tasks show our method achieves consistent improvement over the contrastive learning baseline and sets new states of the art.
Approach: They propose a whitening-based contrastive learning method for sentence embedding learning which combines contrastive and shuffled group whitening.
Outcome: The proposed method achieves better alignment and uniformity on seven semantic textual similarity tasks.
Med-SRAF: A Multi-Agent Framework for Medical Reasoning via Semantic Routing and Agentic Fusion (2026.findings-acl)

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Challenge: Existing RAG methods suffer from a two-part problem: semantic drift and concatenation fallacy . et al.: rapid development of Large Language Models has led to a paradigm shift in artificial intelligence .
Approach: They propose a multi-agent retrieval augmentation framework guided by medical domain knowledge to address these challenges.
Outcome: The proposed framework outperforms existing general RAG baselines on five widely used medical benchmarks.
Self-Improvement Towards Pareto Optimality: Mitigating Preference Conflicts in Multi-Objective Alignment (2025.findings-acl)

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Challenge: Existing approaches to optimize large language models with human preferences suffer from preference conflicts in the data.
Approach: They propose to construct Pareto-optimal responses to resolve preference conflicts by using a self-improving DPO framework that enables LLMs to self-generate and select Paret-optimized responses.
Outcome: The proposed framework achieves superior Pareto Front performance over baselines on two datasets.

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