From the 1 of 16 linked papers with an AI index.
16 papers
Divergence Decoding: Training-Free Capability Fusion
Yimi Wang, Hao Li, Shuo Yang +6
The paper proposes Divergence Decoding, a training‑free method that dynamically routes token generation between a generalist LLM and a domain‑specialist LLM using Jensen‑Shannon di…
Harnessing agent memory to build lifelong AI partners for materials scientists
Siyu Liu, Bo Hu, Beilin Ye +3
Materials research advances through accumulated experience - scripts that work, protocols that are trusted, warnings attached to failed calculations or experiments, and judgement t…
Augmenting Molecular Language Models with Local -gram Memory
Xinni Zhang, Zijing Liu, He Cao +2
Transformer-based language models for SMILES strings suffer from a locality gap: standard character-level tokenization fragments chemically meaningful motifs, forcing models to rep…
Improving Cross-Format Robustness in Language Models with Multi-Format Training
June M. Liu, Shaomian Zheng, He Cao +3
Large language models often remain sensitive to answer format: a question solved correctly in one form may fail in another semantically equivalent form. To study this gap, we defin…
From Answers to States: Verifiable Process-Level Evaluation of Chemical Reasoning in Large Language Models
Hongyu Guo, Hao Li, He Cao +2
Large language models are increasingly used as chemistry assistants, yet most chemistry benchmarks still score only final answers. This masks a critical failure mode: a model may o…
Pushing Biomolecular Utility-Diversity Frontiers with Supergroup Relative Policy Optimization
Xinwu Ye, He Cao, Hao Li +5
Biomolecular generators are often adapted with reward feedback to improve task-specific utility, but pushing utility alone can concentrate generation on a narrow family of candidat…