oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning

arXiv:2510.07731 · cs.AI, cs.CL · Submitted 2025-10-09 · Read on arXiv

cs.AI, cs.CL

Submitted: 2025-10-09

Updated: 2026-09-17

Comments: We have adjusted authorship

Code: https://github.com/skylarkie/oMeBench

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Alignment — 33× in this paper · explained in 1 episode
• Fine-Tuning — 21× in this paper · explained in 5 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• Consistency — 8× in this paper · explained in 3 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• In-Context Learning — 7× in this paper · explained in 4 episodes
• Causal Reasoning — 5× in this paper · explained in 2 episodes
• Benchmarking — 4× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 4× in this paper · explained in 6 episodes
• Foundation Model — 3× in this paper · explained in 3 episodes
• In-Context Learning (ICL) — 3× in this paper · explained in 5 episodes
• One-shot Chain-of-Thought — 3× in this paper
• Trace — 3× in this paper · explained in 2 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Annotator Agreement — 2× in this paper · explained in 1 episode
• Chain-of-Thought (CoT) — 2× in this paper · explained in 4 episodes
• Chain-of-Thought Prompting — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Chain-of-Thought (CoT) Prompting — 1× in this paper · explained in 3 episodes
• Contextual Awareness — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Minimum Edit Distance — 1× in this paper
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Verification — 1× in this paper · explained in 2 episodes

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection