TMCS: Tool-Grounded Multi-Agent Reasoning for Compositional Chemical Problem Solving
cs.AI, cs.CV
Submitted: 2026-09-28
Updated: 2026-09-28
Terminology
Sources
- ChemBERTa-2: Towards Chemical Foundation Models
- Intern-S1: A Scientific Multimodal Foundation Model
- ChemCrow: Augmenting large-language models with chemistry tools
- ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
- The Llama 3 Herd of Models
- GPT-4o System Card
- Chem3DLLM: 3D Multimodal Large Language Models for Chemistry
- Agentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis
- DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration
- Navigating Chemical-Linguistic Sharing Space with Heterogeneous Molecular Encoding
- LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
- OpenAI GPT-5 System Card
- ChemMLLM: Chemical Multimodal Large Language Model
- ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning
- Chem-R: Learning to Reason as a Chemist
- A Systematic Survey of Chemical Pre-trained Models
- Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
- LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset
- ChemLLM: A Chemical Large Language Model
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