Papers by Wenjin Zheng

2 papers
Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling (2026.acl-long)

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Challenge: Large Language Models (LLMs) evolve into agentic systems capable of autonomous tool invocation and complex reasoning.
Approach: They propose a trajectory-level preference benchmark to evaluate judges' ability to distinguish preferred versus distractor agent trajectories in tool-integrated environments.
Outcome: The proposed benchmark evaluates how well judges distinguish preferred versus distractor agent trajectories in complex tool-using scenarios.
Geneverse: A Collection of Open-source Multimodal Large Language Models for Genomic and Proteomic Research (2024.findings-emnlp)

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Challenge: generative Large Language Models (LLMs) are a promising tool for biomedical and healthcare research.
Approach: They propose to use finetuned LLMs and multimodal LLM for genomic and proteomics tasks.
Outcome: The proposed models outperform closed-source models in genomic and proteomics tasks and are highly accurate.

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