ChemCoTBench-V2 is a new rule-verifiable benchmark with 5,620 samples across 18 tasks that evaluates LLM chemical reasoning traces using deterministic chemistry rules and reference traces rather than final answers alone.
Preprint, arXiv:2311.16208
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Bolek injects Morgan fingerprint embeddings into an instruction-tuned text model, then fine-tunes on molecular alignment and synthetic chain-of-thought tasks to improve performance and grounding on 15 TDC binary classification endpoints while generalizing to unseen tasks.
LGPT and Early Query Fusion create flexible graph representations for LLMs, achieving 4.13% improvement on GraphQA without training the model.
Position paper claims multimodal LLMs can significantly advance scientific reasoning and proposes a four-stage roadmap plus challenges and suggestions.
citing papers explorer
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From Answers to States: Verifiable Process-Level Evaluation of Chemical Reasoning in Large Language Models
ChemCoTBench-V2 is a new rule-verifiable benchmark with 5,620 samples across 18 tasks that evaluates LLM chemical reasoning traces using deterministic chemistry rules and reference traces rather than final answers alone.
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Bolek: A Multimodal Language Model for Molecular Reasoning
Bolek injects Morgan fingerprint embeddings into an instruction-tuned text model, then fine-tunes on molecular alignment and synthetic chain-of-thought tasks to improve performance and grounding on 15 TDC binary classification endpoints while generalizing to unseen tasks.
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Query-Aware Learnable Graph Pooling Tokens as Prompt for Large Language Models
LGPT and Early Query Fusion create flexible graph representations for LLMs, achieving 4.13% improvement on GraphQA without training the model.
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Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning
Position paper claims multimodal LLMs can significantly advance scientific reasoning and proposes a four-stage roadmap plus challenges and suggestions.