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20242026
most citedAssay2Mol: large language model-based drug design using BioAssay context

1 citations · 1 across the 11 of their papers we have counts for

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cs.LG2026

TRIDENT: Breaking the Hybrid-Safety-Physics Coupling for Provably Safe Multi-Agent Reinforcement Learning

Zijie Meng, Ziwei Li, Yufei Liu +5

Safe coordination in networked cyber-physical systems forces learning algorithms to simultaneously handle hybrid discrete-continuous actions, hard training-time safety constraints,…

cs.LG2026

Future Validity is the Missing Statistic: From Impossibility to -Estimation for Grammar-Faithful Speculative Decoding

Wenhua Nie, Zijie Meng, Kun Zou +5

Grammar-constrained generation is often combined with local vocabulary masking and speculative decoding, but the resulting sampling law is not the grammar-conditional distribution…

cs.LG2026

Gradient Starvation in Binary-Reward GRPO: Why Group-Mean Centering Fails and Why the Simplest Fix Works

Wenhua Nie, Jianan Wu, Junlin Liu +6

Group Relative Policy Optimization (GRPO) is a standard algorithm for reinforcement learning from verifiable rewards, but its group-mean-centered advantage can fail under binary re…

cs.LG2026

SLaB: Sparse-Lowrank-Binary Decomposition for Efficient Large Language Models

Ziwei Li, Yuang Ma, Yi Kang

The rapid growth of large language models (LLMs) presents significant deployment challenges due to their massive computational and memory demands. While model compression, such as…

cs.LG20251 cited

Assay2Mol: large language model-based drug design using BioAssay context

Yifan Deng, Spencer S. Ericksen, Anthony Gitter

Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…