--- id: "/evaluation-benchmarks/general-leaderboards/page/8/" title: "general leaderboards: 248 curated resources · page 8" url: "https://skillissue.dev/evaluation-benchmarks/general-leaderboards/page/8/" --- # general leaderboards: 248 curated resources general leaderboards [Beginner](/evaluation-benchmarks/beginner/index.md) [Intermediate](/evaluation-benchmarks/intermediate/index.md) [Advanced](/evaluation-benchmarks/advanced/index.md) [Expert](/evaluation-benchmarks/expert/index.md) 248 resources · page 8 of 8 - ### [Cross-Context Verification: Hierarchical Detection of Benchmark Contamination](/evaluation/benchmarks-and-leaderboards/cross-context-verification-contamination-detection/index.md) by [Tae-Eun Song](https://openalex.org/authors/A5128671997) arXiv paper (2026) introducing Cross-Context Verification, a hierarchical method for detecting benchmark contamination. Advanced learning_resource paper unstated en - ### [DuetBench (Decagon)](/evaluation/benchmarks-and-leaderboards/decagon-duetbench/index.md) by [Decagon](https://decagon.ai/) Decagon post introducing DuetBench, a benchmark for self-improving customer-service agents. Advanced learning_resource blog US en - ### [Fairlearn](/evaluation/benchmarks-and-leaderboards/fairlearn/index.md) by [Fairlearn project](https://fairlearn.org/) Fairlearn: open-source toolkit and guides for assessing and mitigating fairness issues in ML models. Advanced learning_resource docs International en - ### [FlagEval Findings Report (LRMs)](/evaluation/benchmarks-and-leaderboards/flageval-findings-report-lrms/index.md) by [Bowen Qin et al. (BAAI)](https://www.baai.ac.cn/) arXiv paper (2025) FlagEval findings report: BAAI's preliminary evaluation of large reasoning models. Advanced–Expert learning_resource paper China en - ### [HLE paper](/evaluation/benchmarks-and-leaderboards/hle-paper/index.md) by [Long Phan et al. (Center for AI Safety and Scale AI)](https://safe.ai/) arXiv paper (2025) introducing Humanity's Last Exam, a benchmark of expert-written questions across academic fields. Advanced learning_resource paper US en - ### [IFEval](/evaluation/benchmarks-and-leaderboards/ifeval/index.md) by [Jeffrey Zhou et al. (Yale University)](https://www.yale.edu) arXiv paper (2023) introducing IFEval, instruction-following evaluation with automatically verifiable instructions. Advanced learning_resource paper US en - ### [J-AISI annual report 2025](/evaluation/benchmarks-and-leaderboards/j-aisi-annual-report-2025/index.md) by [Japan AI Safety Institute](https://aisi.go.jp/) Japan AI Safety Institute 2025 annual activity report (PDF, Japanese). Advanced–Expert learning_resource paper Japan ja - ### [La Leaderboard paper](/evaluation/benchmarks-and-leaderboards/la-leaderboard-paper/index.md) by [María Grandury et al. (Universidad Politécnica de Madrid)](https://www.upm.es) arXiv paper (2025) introducing La Leaderboard, an LLM leaderboard for Spanish varieties and languages of Spain and Latin America. Advanced–Expert learning_resource paper Spain/LatAm es|ca|eu|gl - ### [METR experienced-developer productivity experiment](/evaluation/benchmarks-and-leaderboards/metr-experienced-developer-productivity-experiment/index.md) by [METR](https://metr.org/) METR study of how early-2025 AI tools affected experienced open-source developers' productivity. Advanced learning_resource paper US en - ### [MLflow documentation](/evaluation/benchmarks-and-leaderboards/mlflow-documentation/index.md) by [MLflow project (Databricks)](https://mlflow.org/) MLflow documentation: experiment tracking, model registry, GenAI tracing, evaluation and deployment. Advanced learning_resource docs US/global en - ### [Model Cards for Model Reporting](/evaluation/benchmarks-and-leaderboards/model-cards-for-model-reporting/index.md) by [Google Research](https://research.google/) Google Research publication page for Model Cards for Model Reporting, a standard for documenting trained models. Advanced learning_resource paper United States / international collaboration en - ### [Open Ko-LLM Leaderboard2 paper](/evaluation/benchmarks-and-leaderboards/open-ko-llm-leaderboard2-paper/index.md) by [Hyeonwoo Kim et al. (Upstage)](https://www.upstage.ai) arXiv paper (2024) describing Open Ko-LLM Leaderboard2 for evaluating Korean LLMs. Advanced–Expert learning_resource paper Korea ko|en - ### [SEA-HELM paper](/evaluation/benchmarks-and-leaderboards/sea-helm-paper/index.md) by [Yosephine Susanto et al. (AI Singapore)](https://aisingapore.org/) arXiv paper (2025) introducing SEA-HELM, holistic evaluation of language models on Southeast Asian languages. Advanced–Expert learning_resource paper SE Asia en - ### [τ-Bench: Benchmarking AI agents for the real-world (Sierra)](/evaluation/benchmarks-and-leaderboards/sierra-bench-2024-06-20/index.md) by [Sierra](https://sierra.ai/) Sierra post introducing τ-bench, a benchmark of tool-using agents talking to simulated users, with the pass^k reliability metric. Advanced learning_resource blog US en - ### [Tutor CoPilot: a human-AI approach to real-time expertise](/evaluation/benchmarks-and-leaderboards/tutor-copilot-a-human-ai-approach-to-real-time-expertise/index.md) by [Rose E. Wang et al. (Stanford University)](https://www.stanford.edu) arXiv paper (2024) reporting a randomized field study of Tutor CoPilot, an AI assistant for human tutors. Advanced learning_resource paper United States en - ### [UNLP 2026 Ukrainian NLP workshop paper](/evaluation/benchmarks-and-leaderboards/unlp-2026-ukrainian-nlp-workshop-paper/index.md) by [Svitlana Galeshchuk et al.](https://aclanthology.org/people/svitlana-galeshchuk/unverified/) UNLP 2026 workshop paper (PDF) on Ukrainian NLP evaluation. Advanced–Expert learning_resource paper Ukraine uk|en - ### [BEHAVIOR 2025 1st-place report](/evaluation/benchmarks-and-leaderboards/behavior-2025-1st-place-report/index.md) by [Ilia Larchenko, Gleb Zarin and Akash Karnatak](https://ilialarchenko.com/) arXiv PDF (2025) of the first-place report from the NeurIPS 2025 BEHAVIOR household robotics challenge. Expert learning_resource paper unstated en - ### [A framework for evaluating the chemical knowledge and reasoning abilities of large language models (ChemBench)](/evaluation/benchmarks-and-leaderboards/chembench-paper-nature-chemistry-2025/index.md) by [Adrian Mirza et al. (Helmholtz Institute Jena)](https://www.hi-jena.de) ChemBench paper (Nature Chemistry 2025, PMC full text): framework evaluating chemical knowledge and reasoning of LLMs against chemists. Expert learning_resource paper Germany en - ### [MASK paper](/evaluation/benchmarks-and-leaderboards/mask-paper/index.md) by [Richard Ren et al. (Center for AI Safety)](https://safe.ai/) arXiv PDF (2025) of the MASK benchmark paper on measuring honesty separately from accuracy in LLMs. Expert learning_resource paper US en - ### [Music Arena paper](/evaluation/benchmarks-and-leaderboards/music-arena-paper/index.md) by [Yonghyun Kim et al. (Carnegie Mellon University, LMArena and Sony AI)](https://www.cmu.edu/) arXiv paper (2025) introducing Music Arena, live human-preference evaluation for text-to-music models. Expert learning_resource paper US/Japan (CMU and Sony listed in search) en - ### [RoboArena paper page (Penn)](/evaluation/benchmarks-and-leaderboards/roboarena-paper-page-penn/index.md) by [University of Pennsylvania](https://www.upenn.edu/) RoboArena paper page (University of Pennsylvania): distributed real-world evaluation of generalist robot policies. Expert learning_resource paper US en - ### [Frontier AI Risk Management Framework in Practice (Shanghai AI Lab)](/evaluation/benchmarks-and-leaderboards/shanghai-ai-lab-frontier-ai-risk-management-framework-technical-report/index.md) by [Shanghai AI Lab (Shanghai AI Laboratory)](https://www.shlab.org.cn/) arXiv paper (2025) by Shanghai AI Laboratory applying its Frontier AI Risk Management Framework to analyse model risks. Expert learning_resource paper China [STATE] en - ### [TaxPraBen: Chinese real-world tax practice](/evaluation/benchmarks-and-leaderboards/taxpraben-chinese-real-world-tax-practice/index.md) by [Gang Hu et al.](https://aclanthology.org/people/gang-hu/) ACL 2026 paper introducing TaxPraBen, a benchmark of LLMs on Chinese real-world tax practice tasks. Expert learning_resource paper China en - ### [Who Validates the Validators? (Shankar et al.)](/evaluation/benchmarks-and-leaderboards/who-validates-the-validators-shankar-et-al/index.md) by [Shreya Shankar et al. (UC Berkeley)](https://www.berkeley.edu/) arXiv paper (2024) by Shankar et al. on aligning LLM-assisted evaluators with human preferences and criteria drift. Expert learning_resource paper US en [Previous page](/evaluation-benchmarks/general-leaderboards/page/7/index.md) [Plain-text Markdown copy](/evaluation-benchmarks/general-leaderboards/page/8/index.md)