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

arXiv: https://arxiv.org/abs/2505.21318 · HTML: https://mlsanity.com/paper/2505.21318/

## Key facts

- Cited by 49 papers in the map (data through 14 Oct 2026).
- Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning.
- Builds on 44 of its 76 references that are in the map.
- First posted on arXiv 27 May 2025.

## Placed in

- LLM reasoning / [Clinical and biomedical applications](https://mlsanity.com/lr/clinical-and-biomedical-applications/)

## Builds on (most cited first, 30 of 44)

- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [Training Verifiers to Solve Math Word Problems](https://mlsanity.com/paper/2110.14168/) (2021)
- [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://mlsanity.com/paper/2402.03300/) (2024)
- [DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://mlsanity.com/paper/2501.12948/) (2025)
- [Measuring Mathematical Problem Solving With the MATH Dataset](https://mlsanity.com/paper/2103.03874/) (2021)
- [Qwen2.5 Technical Report](https://mlsanity.com/paper/2412.15115/) (2024)
- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [Gemma 2: Improving Open Language Models at a Practical Size](https://mlsanity.com/paper/2408.00118/) (2024)
- [s1: Simple test-time scaling](https://mlsanity.com/paper/2501.19393/) (2025)
- [Qwen2.5-Coder Technical Report](https://mlsanity.com/paper/2409.12186/) (2024)
- [DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence](https://mlsanity.com/paper/2401.14196/) (2024)
- [OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems](https://mlsanity.com/paper/2402.14008/) (2024)
- [Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement](https://mlsanity.com/paper/2409.12122/) (2024)
- [Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations](https://mlsanity.com/paper/2312.08935/) (2023)
- [Gemini: A Family of Highly Capable Multimodal Models](https://mlsanity.com/paper/2312.11805/) (2023)
- [Phi-4 Technical Report](https://mlsanity.com/paper/2412.08905/) (2024)
- [Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models](https://mlsanity.com/paper/2503.06749/) (2025)
- [A Survey on Large Language Models for Code Generation](https://mlsanity.com/paper/2406.00515/) (2024)
- [ChemCrow: Augmenting large-language models with chemistry tools](https://mlsanity.com/paper/2304.05376/) (2023)
- [VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model](https://mlsanity.com/paper/2504.07615/) (2025)
- [Visual-RFT: Visual Reinforcement Fine-Tuning](https://mlsanity.com/paper/2503.01785/) (2025)
- [LLaVA-CoT: Let Vision Language Models Reason Step-by-Step](https://mlsanity.com/paper/2411.10440/) (2024)
- [2 OLMo 2 Furious](https://mlsanity.com/paper/2501.00656/) (2024)
- [SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models](https://mlsanity.com/paper/2307.10635/) (2023)
- [ReFT: Reasoning with Reinforced Fine-Tuning](https://mlsanity.com/paper/2401.08967/) (2024)
- [Llama-Nemotron: Efficient Reasoning Models](https://mlsanity.com/paper/2505.00949/) (2025)
- [CodeGemma: Open Code Models Based on Gemma](https://mlsanity.com/paper/2406.11409/) (2024)
- [ChemLLM: A Chemical Large Language Model](https://mlsanity.com/paper/2402.06852/) (2024)
- [BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine](https://mlsanity.com/paper/2308.09442/) (2023)
- [EvaGaussians: Event Stream Assisted Gaussian Splatting from Blurry Images](https://mlsanity.com/paper/2405.20224/) (2024)

## Built on by (most cited first, 30 of 49)

- [A Survey of Reinforcement Learning for Large Reasoning Models](https://mlsanity.com/paper/2509.08827/) (2025)
- [Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning](https://mlsanity.com/paper/2606.15007/) (2026)
- [InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery](https://mlsanity.com/paper/2602.08990/) (2026)
- [ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge](https://mlsanity.com/paper/2507.21990/) (2025)
- [From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning](https://mlsanity.com/paper/2509.23768/) (2025)
- [Reasoning-Enhanced Large Language Models for Molecular Property Prediction](https://mlsanity.com/paper/2510.10248/) (2025)
- [SUPERChem: A Multimodal Reasoning Benchmark in Chemistry](https://mlsanity.com/paper/2512.01274/) (2025)
- [MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs](https://mlsanity.com/paper/2601.15279/) (2026)
- [LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning](https://mlsanity.com/paper/2602.07075/) (2026)
- [FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents](https://mlsanity.com/paper/2603.01712/) (2026)
- [MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization](https://mlsanity.com/paper/2604.21937/) (2026)
- [Agentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis](https://mlsanity.com/paper/2601.17687/) (2026)
- [CoT-Evo: Evolutionary Distillation of Chain-of-Thought for Scientific Reasoning](https://mlsanity.com/paper/2510.13166/) (2025)
- [oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning](https://mlsanity.com/paper/2510.07731/) (2025)
- [Atom-anchored LLMs speak Chemistry: A Retrosynthesis Demonstration](https://mlsanity.com/paper/2510.16590/) (2025)
- [MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimization](https://mlsanity.com/paper/2603.24382/) (2026)
- [BioMedGPT-Mol: Multi-task Learning for Molecular Understanding and Generation](https://mlsanity.com/paper/2512.04629/) (2025)
- [Breaking the Vicious Cycle: Coherent 3D Gaussian Splatting from Sparse and Motion-Blurred Views](https://mlsanity.com/paper/2512.10369/) (2025)
- [OmniHuman: A Large-scale Dataset and Benchmark for Human-Centric Video Generation](https://mlsanity.com/paper/2604.18326/) (2026)
- [LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents](https://mlsanity.com/paper/2606.18388/) (2026)
- [MolAct: An Agentic RL Framework for Molecular Editing and Property Optimization](https://mlsanity.com/paper/2512.20135/) (2025)
- [MolQuest: A Benchmark for Agentic Evaluation of Abductive Reasoning in Chemical Structure Elucidation](https://mlsanity.com/paper/2603.25253/) (2026)
- [ToxReason: A Benchmark for Mechanistic Chemical Toxicity Reasoning via Adverse Outcome Pathway](https://mlsanity.com/paper/2604.06264/) (2026)
- [Evaluating Relational Reasoning in LLMs with REL](https://mlsanity.com/paper/2604.12176/) (2026)
- [From Answers to States: Verifiable Process-Level Evaluation of Chemical Reasoning in Large Language Models](https://mlsanity.com/paper/2606.03660/) (2026)
- [ChemDIRT: A Diversified Instruction, Representation, and Task Benchmark for Robust Chemistry-LLM Evaluation](https://mlsanity.com/paper/2608.21504/) (2026)
- [Coder as Editor: Code-driven Interpretable Molecular Optimization](https://mlsanity.com/paper/2510.14455/) (2025)
- [MANGO:Natural Multi-speaker 3D Talking Head Generation via 2D-Lifted Enhancement](https://mlsanity.com/paper/2601.01749/) (2026)
- [MolViBench: Evaluating LLMs on Molecular Vibe Coding](https://mlsanity.com/paper/2605.02351/) (2026)
- [Can Agents Price a Reaction? Evaluating LLMs on Chemical Cost Reasoning](https://mlsanity.com/paper/2605.07251/) (2026)

## Abstract (arXiv)

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 rigorous structural analysis for real-world tasks like drug design and reaction engineering, remains untapped. Current benchmarks focus on simple knowledge retrieval, neglecting step-by-step reasoning required for complex tasks such as molecular optimization and reaction prediction. To address this, we introduce ChemCoTBench, a reasoning framework that bridges molecular structure understanding with arithmetic-inspired operations, including addition, deletion, and substitution, to formalize chemical problem-solving into transparent, step-by-step workflows. By treating molecular transformations as modular "chemical operations", the framework enables slow-thinking reasoning, mirroring the logic of mathematical proofs while grounding solutions in real-world chemical constraints. We evaluate models on two high-impact tasks: Molecular Property Optimization and Chemical Reaction Prediction. These tasks mirror real-world challenges while providing structured evaluability. By providing annotated datasets, a reasoning taxonomy, and baseline evaluations, ChemCoTBench bridges the gap between abstract reasoning methods and practical chemical discovery, establishing a foundation for advancing LLMs as tools for AI-driven scientific innovation.