Aligning Language Model Benchmarks with Pairwise Preferences

arXiv:2602.02898 · cs.AI, cs.CL · Submitted 2026-02-02 · Read on arXiv

cs.AI, cs.CL

Submitted: 2026-02-02

Updated: 2026-10-01

Code: https://github.com/hartvigsen-group/benchalign

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

Terminology

• Benchmark — 291× in this paper · explained in 2 episodes
• Alignment — 135× in this paper · explained in 1 episode
• Accuracy — 99× in this paper · explained in 1 episode
• Distillation — 15× in this paper · explained in 2 episodes
• Core — 6× in this paper · explained in 2 episodes
• Benchmarking — 5× in this paper · explained in 3 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• LLM judge — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 3× in this paper
• Item Response Theory — 3× in this paper
• Loss Function — 3× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Institutional Review Board — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Fisher Information — 1× in this paper · explained in 3 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes

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