Papers by Haiwen Li
EvoMD-LLM: Learning the Language of Species Evolution in Reactive Molecular Dynamics (2026.findings-acl)
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| Challenge: | Existing models operate on static molecular representations or rely on external tools for reasoning. |
| Approach: | They propose a framework that reformulates species-level molecular dynamics as a symbolic temporal language modeling problem. |
| Outcome: | The proposed model outperforms neural networks and language-based baselines on multiple temporal prediction tasks and generates plausible interpretations of reaction dynamics. |
Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts (2026.acl-long)
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Haolei Xu, Haiwen Hong, Hongxing Li, Rui Zhou, Yang Zhang, Longtao Huang, Hui Xue, Yongliang Shen, Weiming Lu, Yueting Zhuang
| Challenge: | Existing multimodal Mixture-of-Experts models accurately perceive image content yet fail in subsequent reasoning . Seeing but not thinking phenomenon is a puzzling phenomenon . |
| Approach: | They propose a routing-guided intervention method that enhances domain expert activation. |
| Outcome: | The proposed method achieves consistent improvements on visual reasoning tasks. |
Can Large Language Models Tackle Graph Partitioning? (2025.emnlp-main)
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| Challenge: | Large language models (LLMs) have remarkable capabilities in understanding complex tasks, but they can only handle graph partitioning tasks that require global perception abilities. |
| Approach: | They propose a pipeline for coarsening, reasoning, and refining to enable LLMs to perform graph partitioning on small-scale graphs. |
| Outcome: | The proposed pipeline can handle graph partitioning tasks on small graphs with coarsening, reasoning, and refining. |