Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)

Judge Arena: Benchmarking LLMs as Evaluators

Rethinking LLM Evaluation with 3C3H: AraGen Benchmark and Leaderboard

Introducing the Open Ko-LLM Leaderboard: Leading the Korean LLM Evaluation Ecosystem

Open LLM Leaderboard: DROP deep dive

LLM-as-a-Verifier: A General-Purpose Verification Framework

Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the ability to determine the correctness of a solution, as a new scaling axis.

When the Judge Changes, So Does the Measurement: Auditing LLM-as-Judge Reliability

arXiv:2607. 08535v1 Announce Type: cross Abstract: An LLM-as-judge score can move even when the candidate responses stay fixed, simply because the evaluator has changed.

LLM-as-a-Verifier: A General-Purpose Verification Framework

arXiv:2607. 05391v1 Announce Type: new Abstract: Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs.

Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks

arXiv:2607. 09739v1 Announce Type: new Abstract: We study LLM benchmark coreset selection: selecting a small subset of prompts over multiple benchmarks whose induced model scores and rankings approximate those obtained from the full benchmark suite.

"LLM Agent Performance" Is Not a Single Evaluation Target

arXiv:2602. 03238v3 Announce Type: replace Abstract: LLM agent benchmark scores are shaped not only by the model but also by the agent harness, environment, evaluator, and inference budget.

Bringing the Artificial Analysis LLM Performance Leaderboard to Hugging Face

Introducing the LiveCodeBench Leaderboard - Holistic and Contamination-Free Evaluation of Code LLMs

📚 3LM: A Benchmark for Arabic LLMs in STEM and Code