ChemLLM: A Chemical Large Language Model
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Cited by 32 in LLM reasoning, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges are two-fold: firstly, most chemical data and scientific knowledge are stored in structured databases, which limits the model's ability to sustain coherent dialogue when used directly. Secondly, there is an absence of objective and fair benchmark that encompass most chemistry tasks. Here, we introduce ChemLLM, a comprehensive framework that features the first LLM dedicated to chemistry. It also includes ChemData, a dataset specifically designed for instruction tuning, and ChemBench, a robust benchmark covering nine essential chemistry tasks. ChemLLM is adept at performing various tasks across chemical disciplines with fluid dialogue interaction. Notably, ChemLLM achieves results comparable to GPT-4 on the core chemical tasks and demonstrates competitive performance with LLMs of similar size in general scenarios. ChemLLM paves a new path for exploration in chemical studies, and our method of incorporating structured chemical knowledge into dialogue systems sets a new standard for developing LLMs in various scientific fields. Codes, Datasets, and Model weights are publicly accessible at https://hf.co/AI4Chem
Key facts. Cited by 106 papers in the map (data through 14 Oct 2026). Builds on 18 of its 47 references that are in the map. First posted on arXiv 10 Feb 2024.
Builds on
18 of 47 references.
References · 18
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
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- 2020Measuring Massive Multitask Language Understandingcited by 7,963
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- 2023Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspectivecited by 92
- 2023Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineeringcited by 86
- 2023GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Textcited by 82
- 2022Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Modelcited by 25
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Citing papers per year: 2024: 23; 2025: 43; 2026: 40.
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- 2026Localize, Then Reason: Visual Latent Structural Reasoning for Molecular Properties and Edits13 Aug 2026
- 2026From Answers to States: Verifiable Process-Level Evaluation of Chemical Reasoning in Large Language Models2 Jun 2026
- 2026Can Agents Price a Reaction? Evaluating LLMs on Chemical Cost Reasoning8 May 2026
- 2026Bolek: A Multimodal Language Model for Molecular Reasoning4 May 2026
- 2026A Multitask Large Reasoning Model for Molecular Science13 Mar 2026
- 2026Logos: An evolvable reasoning engine for rational molecular design10 Mar 2026
- 2026DrugR: Optimizing Molecular Drugs through LLM-based Explicit Reasoning9 Feb 2026
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- 2026CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows7 Aug 2026
- 2026Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination9 Jul 2026
- 2026Heterogeneous Scientific Foundation Model Collaboration30 Apr 2026
- 2026Agentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis25 Jan 2026
- 2026Computer Environments Elicit General Agentic Intelligence in LLMs22 Jan 2026
- 2025MADD: Multi-Agent Drug Discovery Orchestra11 Nov 2025
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- 2026Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding19 Mar 2026
- 2026DeepMoLM: Leveraging Visual and Geometric Structural Information for Molecule-Text Modeling21 Jan 2026
- 2025MolVision: Molecular Property Prediction with Vision Language Models4 Jul 2025
- 2025ChemMLLM: Chemical Multimodal Large Language Model22 May 2025
- 2024Probing the limitations of multimodal language models for chemistry and materials research25 Nov 2024
- 2024LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Datasetcited by 128
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- 2024Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Surveycited by 17
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- 2026ChemDIRT: A Diversified Instruction, Representation, and Task Benchmark for Robust Chemistry-LLM Evaluation21 Aug 2026
- 2026Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery7 Aug 2026
- 2026Back to Basics: Improving Molecular Understanding in LLMs via SMILES-Graph Translation3 Jul 2026
- 2026SciCore-Mol: Augmenting Large Language Models with Pluggable Molecular Cognition Modules21 May 2026
- 2026Reinforcement Learning over Predictive Distributions for LLM Regression20 May 2026
- 2026Perspective: Towards sustainable exploration of chemical spaces with machine learning31 Mar 2026
- 2026Reinforced Reasoning for End-to-End Retrosynthetic Planning31 Mar 2026
- 2026In-Context Molecular Property Prediction with LLMs: A Blinding Study on Memorization and Knowledge Conflicts26 Mar 2026
- 2026Enhanced Drug-drug Interaction Prediction Using Adaptive Knowledge Integration13 Mar 2026
- 2026SciDesignBench: Benchmarking and Improving Language Models for Scientific Inverse Design13 Mar 2026
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