arXiv Computation and Language
MolLean: A Process-Verifiable Language for Chemical Reasoning
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arXiv AI
Jun 3
From Answers to States: Verifiable Process-Level Evaluation of Chemical Reasoning in Large Language Models
arXiv:2606. 03660v1 Announce Type: new Abstract: Large language models are increasingly used as chemistry assistants, yet most chemistry benchmarks still score only final answers.
arXiv AI
Sep 18
oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning
oMeBench is a large-scale, expert-curated benchmark designed to evaluate large language models (LLMs) on organic mechanism reasoning. It contains over 10,000 annotated mechanistic steps, including reaction type labels, intermediate structures, and difficulty ratings, and introduces the oMeS scoring framework to assess logical consistency and chemical structural similarity. Evaluation shows that while current LLMs display promising chemical intuition, they often fail to produce correct and consistent multi-step reasoning, though prompting and fine-tuning can bring smaller models up to the level of closed‑source frontier models.
arXiv Computation and Language
Sep 15
Chemical Chain-of-Thought Functions as a Hallucination-Prone Molecular Scratchpad
Chemical reasoning language models are expected to produce faithful chain-of-thought (CoT) explanations when answering chemistry tasks, but across four model families and twelve tasks, hallucinations are widespread and largely independent of answer correctness. Attribution analyses reveal that these models use a shared scratchpad function: Chem‑R and ether‑0 rely on fragmented SMILES drafts, while ChemDFM‑R emphasizes scaffold, positional, and naming cues. Perturbing Chem‑R’s SMILES sketches degrades generation, indicating that structural drafts can be causally load‑bearing even when verbal structural claims are largely inert.
arXiv AI
Aug 10
CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows
arXiv:2608. 06961v1 Announce Type: new Abstract: Early-stage molecular design is an iterative process, not just a task of generating molecules.
arXiv AI
5d ago
ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning
arXiv:2610.17183v1 Announce Type: new Abstract: Current chemistry benchmarks primarily evaluate outcome prediction or reaction pathway generation, but rarely test whether a model can explain why an o...
arXiv AI
Oct 12
Masked Diffusion Language Agents for Tool-Integrated Chemical Reasoning
The paper introduces ChemDiffAgent, a masked diffusion language agent designed for tool‑integrated chemical reasoning. Unlike traditional autoregressive agents, it treats reasoning as iterative denoising over interleaved reasoning and tool‑use trajectories, allowing joint decision making under full‑trajectory context. A two‑stage post‑training framework further refines tool use and reasoning, and the authors benchmark the model on six chemistry tasks, reporting a ~20% performance gain over autoregressive baselines and competitive results against larger models.