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20232026
most citedMedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs

2 citations · 2 across the 11 of their papers we have counts for

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cs.CL2026

On Group Relative Policy Optimization Collapse in Agent Search: The Lazy Likelihood-Displacement

Wenlong Deng, Yushu Li, Boying Gong +3

Tool-integrated (TI) reinforcement learning (RL) enables large language models (LLMs) to perform multi-step reasoning by interacting with external tools such as search engines and…

cs.CL2025

For-Value: Efficient Forward-Only Data Valuation for finetuning LLMs and VLMs

Wenlong Deng, Qi Zeng, Jiaming Zhang +5

Data valuation is essential for enhancing the transparency and accountability of large language models (LLMs) and vision-language models (VLMs). However, existing methods typically…

cs.CL2025

Enhancing Clinical Multiple-Choice Questions Benchmarks with Knowledge Graph Guided Distractor Generation

Running Yang, Wenlong Deng, Minghui Chen +2

Clinical tasks such as diagnosis and treatment require strong decision-making abilities, highlighting the importance of rigorous evaluation benchmarks to assess the reliability of…

cs.CL20252 cited

MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs

Juncheng Wu, Wenlong Deng, Xingxuan Li +12

Medical tasks such as diagnosis and treatment planning require precise and complex reasoning, particularly in life-critical domains. Unlike mathematical reasoning, medical reasonin…

cs.CL2024

LLM-Assisted Content Conditional Debiasing for Fair Text Embedding

Wenlong Deng, Blair Chen, Beidi Zhao +3

Mitigating biases in machine learning models has become an increasing concern in Natural Language Processing (NLP), particularly in developing fair text embeddings, which are cruci…