--- id: "/evaluation-benchmarks/advanced/page/14/" title: "Evaluation & benchmarks for advanced learners · page 14" url: "https://skillissue.dev/evaluation-benchmarks/advanced/page/14/" --- # Evaluation & benchmarks for advanced learners [Beginner](/evaluation-benchmarks/beginner/index.md) [Intermediate](/evaluation-benchmarks/intermediate/index.md) [Advanced](/evaluation-benchmarks/advanced/index.md) [Expert](/evaluation-benchmarks/expert/index.md) 452 resources · page 14 of 15 - ### [Agentic Benchmark Checklist (ABC)](/evaluation/benchmarks-and-leaderboards/agentic-benchmark-checklist-abc/index.md) by [Yuxuan Zhu et al.](https://orcid.org/0009-0001-6738-8930) arXiv paper (2025) proposing the Agentic Benchmark Checklist, guidelines for building valid agentic benchmarks. Advanced learning_resource paper US (UIUC et al.) en - ### [ARC Prize 2025 Technical Report](/evaluation/benchmarks-and-leaderboards/arc-prize-2025-technical-report/index.md) by [François Chollet et al. (ARC Prize Foundation)](https://arcprize.org/) arXiv paper (2026) ARC Prize 2025 technical report on ARC-AGI-2 results and winning approaches. Advanced learning_resource paper US en - ### [Arize Phoenix docs: Evaluating multi-agent systems](/evaluation/benchmarks-and-leaderboards/arize-phoenix-evaluating-multi-agent-systems/index.md) by [Arize AI](https://www.arize.com) Arize Phoenix documentation on evaluating multi-agent systems using traces of each agent's steps. Advanced learning_resource docs US en - ### [Benchmark-based assessment of Indian foundation models](/evaluation/benchmarks-and-leaderboards/benchmark-based-assessment-of-indian-foundation-models/index.md) by [Avinash Agarwal and Vridhi Jain](https://openalex.org/authors/A5123875505) arXiv paper (2026) comparing publicly benchmarked Indian foundation models across benchmarks. Advanced–Expert learning_resource paper India en - ### [C-Eval paper](/evaluation/benchmarks-and-leaderboards/c-eval-paper/index.md) by [Yuzhen Huang et al. (Shanghai Jiao Tong University)](https://www.sjtu.edu.cn) arXiv paper (2023) introducing C-Eval, a multi-level, multi-discipline Chinese evaluation suite for foundation models. Advanced–Expert learning_resource paper China en - ### [CLARIN-PT-LDB paper](/evaluation/benchmarks-and-leaderboards/clarin-pt-ldb-paper/index.md) by [João Silva et al. (University of Lisbon)](https://www.ulisboa.pt) arXiv paper (2026) introducing CLARIN-PT-LDB, an open LLM leaderboard for European Portuguese. Advanced–Expert learning_resource paper Portugal pt - ### [Coding-agent leaderboard resolution audit](/evaluation/benchmarks-and-leaderboards/coding-agent-leaderboard-resolution-audit/index.md) by [Fengshuo Liu et al. (Imperial College London)](https://www.imperial.ac.uk) arXiv paper (2026) arguing that coding agents have converged so the SWE-bench leaderboard can no longer separate them. Advanced learning_resource paper China / International en - ### [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 - ### [FlagEvalMM](/evaluation/benchmarks-and-leaderboards/flagevalmm/index.md) by [Zheqi He et al. (BAAI)](https://www.baai.ac.cn/) arXiv paper (2025) introducing FlagEvalMM, BAAI's framework for evaluating multimodal models. Advanced–Expert learning_resource paper China en - ### [HAE-RAE Evaluation Toolkit / HRET](/evaluation/benchmarks-and-leaderboards/hae-rae-evaluation-toolkit-hret/index.md) by [Hanwool Lee et al.](https://orcid.org/0000-0001-5565-5184) arXiv paper (2025) introducing the HAE-RAE Evaluation Toolkit (HRET), a unified framework for evaluating Korean LLMs. Advanced learning_resource paper South Korea 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 - ### [Inspect India Evals](/evaluation/benchmarks-and-leaderboards/inspect-india-evals/index.md) by [Abhishek Kumar Singh et al.](https://openalex.org/authors/A5143884522) arXiv paper (2026) introducing Inspect India Evals, an open framework of Indian benchmarks with a fairness index. Advanced–Expert learning_resource paper India mul - ### [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 - ### [Korea AISI 5th AI Safety Forecast Report](/evaluation/benchmarks-and-leaderboards/korea-aisi-5th-ai-safety-forecast-report-2026-09-03/index.md) by [Korea AISI](https://aisi.re.kr/) Korea AI Safety Institute 5th AI Safety Forecast Report covering May–July 2026. Advanced–Expert learning_resource paper Korea ko - ### [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 - ### [LabSafety Bench](/evaluation/benchmarks-and-leaderboards/labsafety-bench/index.md) by [Yujun Zhou et al. (University of Notre Dame)](https://www.nd.edu/) Nature Machine Intelligence paper introducing LabSafety Bench for LLM safety risks in scientific labs. Advanced learning_resource paper International en - ### [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 - ### [MME](/evaluation/benchmarks-and-leaderboards/mme/index.md) by [Chaoyou Fu et al. (Nanjing University)](https://www.nju.edu.cn/) arXiv paper (2023) introducing MME, a benchmark for perception and cognition in multimodal LLMs. Advanced learning_resource paper China 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 - ### [MoleculeNet](/evaluation/benchmarks-and-leaderboards/moleculenet/index.md) by [Zhenqin Wu et al. (Stanford University)](https://www.stanford.edu) arXiv paper (2017) "MoleculeNet: A Benchmark for Molecular Machine Learning", introducing the MoleculeNet benchmark datasets for molecular property prediction. Advanced learning_resource paper US / International 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 - ### [Introducing TRAIL: A Benchmark for Agentic Evaluation (Patronus AI)](/evaluation/benchmarks-and-leaderboards/patronus-trail-benchmark-for-agentic-evaluation-2025-06-05/index.md) by [Patronus AI](https://www.patronus.ai/) Patronus AI post introducing TRAIL, a benchmark of annotated agent traces for detecting reasoning, planning and execution errors. Advanced learning_resource blog US en - ### [Quantifying infrastructure noise in agentic coding evals](/evaluation/benchmarks-and-leaderboards/quantifying-infrastructure-noise-in-agentic-coding-evals/index.md) by [Anthropic](https://anthropic.com/) Anthropic engineering post quantifying how infrastructure noise affects agentic coding evaluation scores. Advanced learning_resource paper US en - ### [Safetywashing](/evaluation/benchmarks-and-leaderboards/safetywashing/index.md) by [Richard Ren et al. (Center for AI Safety)](https://safe.ai/) arXiv paper (2024) "Safetywashing", testing whether AI safety benchmarks measure safety or general capability. Advanced learning_resource paper US / International 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 - ### [SUPERB](/evaluation/benchmarks-and-leaderboards/superb/index.md) by [Shu-wen Yang et al. (National Taiwan University)](https://www.ntu.edu.tw/) arXiv paper (2021) "SUPERB: Speech processing Universal PERformance Benchmark", introducing SUPERB, a benchmark of speech representations across many speech tasks. Advanced learning_resource paper International en [Previous page](/evaluation-benchmarks/advanced/page/13/index.md) [Next page](/evaluation-benchmarks/advanced/page/15/index.md) [Plain-text Markdown copy](/evaluation-benchmarks/advanced/page/14/index.md)