general leaderboards: 248 curated resources
general leaderboards
248 resources · page 8 of 8
Cross-Context Verification: Hierarchical Detection of Benchmark Contamination
by Tae-Eun Song
arXiv paper (2026) introducing Cross-Context Verification, a hierarchical method for detecting benchmark contamination.
DuetBench (Decagon)
by Decagon
Decagon post introducing DuetBench, a benchmark for self-improving customer-service agents.
Fairlearn
Fairlearn: open-source toolkit and guides for assessing and mitigating fairness issues in ML models.
FlagEval Findings Report (LRMs)
arXiv paper (2025) FlagEval findings report: BAAI's preliminary evaluation of large reasoning models.
HLE paper
by Long Phan et al. (Center for AI Safety and Scale AI)
arXiv paper (2025) introducing Humanity's Last Exam, a benchmark of expert-written questions across academic fields.
IFEval
by Jeffrey Zhou et al. (Yale University)
arXiv paper (2023) introducing IFEval, instruction-following evaluation with automatically verifiable instructions.
J-AISI annual report 2025
Japan AI Safety Institute 2025 annual activity report (PDF, Japanese).
La Leaderboard paper
by María Grandury et al. (Universidad Politécnica de Madrid)
arXiv paper (2025) introducing La Leaderboard, an LLM leaderboard for Spanish varieties and languages of Spain and Latin America.
METR experienced-developer productivity experiment
by METR
METR study of how early-2025 AI tools affected experienced open-source developers' productivity.
MLflow documentation
by MLflow project (Databricks)
MLflow documentation: experiment tracking, model registry, GenAI tracing, evaluation and deployment.
Model Cards for Model Reporting
Google Research publication page for Model Cards for Model Reporting, a standard for documenting trained models.
Open Ko-LLM Leaderboard2 paper
by Hyeonwoo Kim et al. (Upstage)
arXiv paper (2024) describing Open Ko-LLM Leaderboard2 for evaluating Korean LLMs.
SEA-HELM paper
by Yosephine Susanto et al. (AI Singapore)
arXiv paper (2025) introducing SEA-HELM, holistic evaluation of language models on Southeast Asian languages.
τ-Bench: Benchmarking AI agents for the real-world (Sierra)
by Sierra
Sierra post introducing τ-bench, a benchmark of tool-using agents talking to simulated users, with the pass^k reliability metric.
Tutor CoPilot: a human-AI approach to real-time expertise
by Rose E. Wang et al. (Stanford University)
arXiv paper (2024) reporting a randomized field study of Tutor CoPilot, an AI assistant for human tutors.
UNLP 2026 Ukrainian NLP workshop paper
UNLP 2026 workshop paper (PDF) on Ukrainian NLP evaluation.
BEHAVIOR 2025 1st-place report
by Ilia Larchenko, Gleb Zarin and Akash Karnatak
arXiv PDF (2025) of the first-place report from the NeurIPS 2025 BEHAVIOR household robotics challenge.
A framework for evaluating the chemical knowledge and reasoning abilities of large language models (ChemBench)
by Adrian Mirza et al. (Helmholtz Institute Jena)
ChemBench paper (Nature Chemistry 2025, PMC full text): framework evaluating chemical knowledge and reasoning of LLMs against chemists.
MASK paper
by Richard Ren et al. (Center for AI Safety)
arXiv PDF (2025) of the MASK benchmark paper on measuring honesty separately from accuracy in LLMs.
Music Arena paper
by Yonghyun Kim et al. (Carnegie Mellon University, LMArena and Sony AI)
arXiv paper (2025) introducing Music Arena, live human-preference evaluation for text-to-music models.
RoboArena paper page (Penn)
RoboArena paper page (University of Pennsylvania): distributed real-world evaluation of generalist robot policies.
Frontier AI Risk Management Framework in Practice (Shanghai AI Lab)
by Shanghai AI Lab (Shanghai AI Laboratory)
arXiv paper (2025) by Shanghai AI Laboratory applying its Frontier AI Risk Management Framework to analyse model risks.
TaxPraBen: Chinese real-world tax practice
ACL 2026 paper introducing TaxPraBen, a benchmark of LLMs on Chinese real-world tax practice tasks.
Who Validates the Validators? (Shankar et al.)
by Shreya Shankar et al. (UC Berkeley)
arXiv paper (2024) by Shankar et al. on aligning LLM-assisted evaluators with human preferences and criteria drift.