mlsanityData to 7 Oct 2026

BenchmarkCards: Standardized Documentation for Large Language Model Benchmarks

arXiv 2410.12974 ↗First posted 16 Oct 2024cs.CLcited by 8

Not on the map. Why?

Abstract (arXiv)

Large language models (LLMs) are powerful tools capable of handling diverse tasks. Comparing and selecting appropriate LLMs for specific tasks requires systematic evaluation methods, as models exhibit varying capabilities across different domains. However, finding suitable benchmarks is difficult given the many available options. This complexity not only increases the risk of benchmark misuse and misinterpretation but also demands substantial effort from LLM users, seeking the most suitable benchmarks for their specific needs. To address these issues, we introduce textttBenchmarkCards, an intuitive and validated documentation framework that standardizes critical benchmark attributes such as objectives, methodologies, data sources, and limitations. Through user studies involving benchmark creators and users, we show that textttBenchmarkCards can simplify benchmark selection and enhance transparency, facilitating informed decision-making in evaluating LLMs. Data & Code: https://github.com/SokolAnn/BenchmarkCards

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 34 of its 54 references that are in the map. First posted on arXiv 16 Oct 2024.

Builds on

34 of 54 references.

References · 34

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  3. 2021Program Synthesis with Large Language Modelscited by 3,509
  4. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  5. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  6. 2018Datasheets for Datasetscited by 1,371
  7. 2020RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Modelscited by 1,235
  8. 2018Model Cards for Model Reportingcited by 1,068
  9. 2021Ethical and social risks of harm from Language Modelscited by 957
  10. 2020StereoSet: Measuring stereotypical bias in pretrained language modelscited by 911
  11. 2022CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesiscited by 876
  12. 2020CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Modelscited by 703
22 more
  1. 2021BBQ: A Hand-Built Bias Benchmark for Question Answeringcited by 683
  2. 2018Gender Bias in Coreference Resolution: Evaluation and Debiasing Methodscited by 657
  3. 2023Bias and Fairness in Large Language Models: A Surveycited by 626
  4. 2022Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studiescited by 506
  5. 2023Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyondcited by 409
  6. 2023A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Uglycited by 380
  7. 2021LexGLUE: A Benchmark Dataset for Legal Language Understanding in Englishcited by 302
  8. 2022GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Recordscited by 238
  9. 2022Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AIcited by 169
  10. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 152
  11. 2019On Measuring and Mitigating Biased Inferences of Word Embeddingscited by 112
  12. 2018The Dataset Nutrition Label: A Framework To Drive Higher Data Quality Standardscited by 97
  13. 2023Combating Misinformation in the Age of LLMs: Opportunities and Challengescited by 94
  14. 2024Croissant: A Metadata Format for ML-Ready Datasetscited by 79
  15. 2023TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Modelscited by 56
  16. 2023WinoQueer: A Community-in-the-Loop Benchmark for Anti-LGBTQ+ Bias in Large Language Modelscited by 42
  17. 2023Explaining Legal Concepts with Augmented Large Language Models (GPT-4)cited by 39
  18. 2023Blind Judgement: Agent-Based Supreme Court Modelling With GPTcited by 37
  19. 2023Assessing Language Model Deployment with Risk Cardscited by 30
  20. 2024Do These LLM Benchmarks Agree? Fixing Benchmark Evaluation with BenchBenchcited by 25
  21. 2024Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AIcited by 18
  22. 2024WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical Casecited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 6.

8 papers.