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From the 1 of 16 linked papers with an AI index.

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cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

ReactBench: A Benchmark for Topological Reasoning in MLLMs on Chemical Reaction Diagrams

Qiang Xu, Shengyuan Bai, Yu Wang +6

Multimodal Large Language Models (MLLMs) excel at recognizing individual visual elements and reasoning over simple linear diagrams. However, when faced with complex topological str…

cs.AI20261 cited

Mozi: Governed Autonomy for Drug Discovery LLM Agents

He Cao, Siyu Liu, Fan Zhang +7

Tool-augmented large language model (LLM) agents promise to unify scientific reasoning with computation, yet their deployment in high-stakes domains like drug discovery is bottlene…

cs.AI2026

Beyond Chemical QA: Evaluating LLM's Chemical Reasoning with Modular Chemical Operations

Hao Li, He Cao, Bin Feng +6

While large language models (LLMs) with Chain-of-Thought (CoT) reasoning excel in mathematics and coding, their potential for systematic reasoning in chemistry, a domain demanding…