ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning
cs.AI, cs.CV
Submitted: 2026-10-12
Updated: 2026-10-12
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- GPT-4 Technical Report
- ChemQuests: A Curated Chemistry Question-Answer Database Extracted from ChemRxiv papers
- Phi-4-reasoning-vision-15B Technical Report
- Qwen3-VL Technical Report
- Qwen2.5-VL Technical Report
- Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
- ScholarChemQA: Unveiling the Power of Language Models in Chemical Research Question Answering
- SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
- ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language Models
- Counting on Consensus: Selecting the Right Inter-annotator Agreement Metric for NLP Annotation and Evaluation
- Beyond Chemical QA: Evaluating LLM's Chemical Reasoning with Modular Chemical Operations
- Retell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story Retelling
- LLM-as-a-Judge: Rapid Evaluation of Legal Document Recommendation for Retrieval-Augmented Generation
- OpenAI GPT-5 System Card
- JudgeBench: A Benchmark for Evaluating LLM-based Judges
- MinerU: An Open-Source Solution for Precise Document Content Extraction
- SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
- oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning
- SUPERChem: A Multimodal Reasoning Benchmark in Chemistry
- InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
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