Papers by Leshu Li

2 papers
LipoAgent: Coordinating Fine-Tuned LLM Agents for Safer Lipid Design (2026.findings-acl)

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Challenge: Lipid nanoparticles (LNPs) are among the most clinically mature platforms for nucleic acid delivery, yet designing lipids that are effective and biologically safe remains a major bottleneck.
Approach: They propose a safety-aware multi-agent LLM framework for lipid discovery that enforces toxicity as a prerequisite for efficiency prediction.
Outcome: The proposed framework achieves an average improvement in mRNA transfection efficiency prediction across multiple foundation models.
LAMB: A Training-Free Method to Enhance the Long-Context Understanding of SSMs via Attention-Guided Token Filtering (2025.acl-short)

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Challenge: Recent work attributes performance degradation to an exponential decay in hidden-state memory.
Approach: They propose a token filtering strategy that is training-free and attention-guided . they propose 'LAMB' to preserve critical tokens during inference .
Outcome: The proposed token filtering improves long-context performance by 30.35% over state-of-the-art methods on benchmarks.

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