Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks
Not on the map. Why?
Abstract (arXiv)
We introduce Dynatask: an open source system for setting up custom NLP tasks that aims to greatly lower the technical knowledge and effort required for hosting and evaluating state-of-the-art NLP models, as well as for conducting model in the loop data collection with crowdworkers. Dynatask is integrated with Dynabench, a research platform for rethinking benchmarking in AI that facilitates human and model in the loop data collection and evaluation. To create a task, users only need to write a short task configuration file from which the relevant web interfaces and model hosting infrastructure are automatically generated. The system is available at https://dynabench.org/ and the full library can be found at https://github.com/facebookresearch/dynabench.
Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 24 of its 34 references that are in the map. First posted on arXiv 5 Apr 2022.
Builds on
24 of 34 references.
References · 24
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
- 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
- 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,665
- 2015A large annotated corpus for learning natural language inferencecited by 1,837
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,718
- 2019Adversarial NLI: A New Benchmark for Natural Language Understandingcited by 798
- 2021The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translationcited by 556
- 2021Datasets: A Community Library for Natural Language Processingcited by 526
- 2021Dynabench: Rethinking Benchmarking in NLPcited by 447
- 2020Data and its (dis)contents: A survey of dataset development and use in machine learning researchcited by 259
- 2020Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detectioncited by 217
- 2020Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehensioncited by 131
12 more
- 2021Improving Question Answering Model Robustness with Synthetic Adversarial Data Generationcited by 77
- 2021Adversarial VQA: A New Benchmark for Evaluating the Robustness of VQA Modelscited by 74
- 2020DynaSent: A Dynamic Benchmark for Sentiment Analysiscited by 63
- 2021Human-Adversarial Visual Question Answeringcited by 57
- 2021Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarkingcited by 53
- 2021Hatemoji: A Test Suite and Adversarially-Generated Dataset for Benchmarking and Detecting Emoji-based Hatecited by 50
- 2020Targeting the Benchmark: On Methodology in Current Natural Language Processing Researchcited by 44
- 2019Quizbowl: The Case for Incremental Question Answeringcited by 36
- 2020ANLIzing the Adversarial Natural Language Inference Datasetcited by 36
- 2021Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistantscited by 31
- 2021On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Studycited by 30
- 2021Analyzing Dynamic Adversarial Training Data in the Limitcited by 24
Built on by
Citing papers per year: 2022: 4; 2023: 5; 2024: 3; 2025: 1; 2026: 3.
16 papers.
Sort:
By area:
- 2023A Survey on Evaluation of Large Language Modelscited by 1,227
- 2022RealTime QA: What's the Answer Right Now?cited by 239
- 2024NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samplescited by 94
- 2022Perturbation Augmentation for Fairer NLPcited by 51
- 2024AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledgecited by 42
- 2024Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generationcited by 20
- 2026Brittlebench: Quantifying LLM robustness via prompt sensitivitycited by 19
- 2023CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verificationcited by 11
- 2023Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Modelscited by 7
- 2022KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Modelscited by 4
- 2025skLEP: A Slovak General Language Understanding Benchmarkcited by 3
- 2023Meta Semantic Template for Evaluation of Large Language Modelscited by 2
4 more
- 2022Fighting FIRe with FIRE: Assessing the Validity of Text-to-Video Retrieval Benchmarkscited by 1
- 2023Leveraging Diffusion Perturbations for Measuring Fairness in Computer Visioncited by 1
- 2026A Theoretical Framework for Adaptive Utility-Weighted Benchmarkingcited by 0
- 2026Hypothesis Testing with Conditional Queries: Learnability and the Value of Interactioncited by 0
- 2026Hypothesis Testing with Conditional Queries: Learnability and the Value of Interaction6 Aug 2026
- 2026Brittlebench: Quantifying LLM robustness via prompt sensitivity27 Feb 2026
- 2026A Theoretical Framework for Adaptive Utility-Weighted Benchmarking12 Feb 2026
- 2025skLEP: A Slovak General Language Understanding Benchmark26 Jun 2025
- 2024AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledge18 Dec 2024
- 2024NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples18 Oct 2024
- 2024Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation14 Feb 2024
- 2023Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision25 Nov 2023
- 2023Meta Semantic Template for Evaluation of Large Language Models1 Oct 2023
- 2023A Survey on Evaluation of Large Language Models6 Jul 2023
- 2023Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Models22 May 2023
- 2023CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification7 Mar 2023
4 more
- 2022Fighting FIRe with FIRE: Assessing the Validity of Text-to-Video Retrieval Benchmarks10 Oct 2022
- 2022KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models23 Aug 2022
- 2022RealTime QA: What's the Answer Right Now?27 Jul 2022
- 2022Perturbation Augmentation for Fairer NLP25 May 2022
- 2023A Survey on Evaluation of Large Language Modelscited by 1,227
- 2022RealTime QA: What's the Answer Right Now?cited by 239
- 2022Perturbation Augmentation for Fairer NLPcited by 51
- 2024AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledgecited by 42
- 2026Brittlebench: Quantifying LLM robustness via prompt sensitivitycited by 19
- 2023Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Modelscited by 7
- 2022KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Modelscited by 4
- 2025skLEP: A Slovak General Language Understanding Benchmarkcited by 3
- 2023Meta Semantic Template for Evaluation of Large Language Modelscited by 2
- 2022Fighting FIRe with FIRE: Assessing the Validity of Text-to-Video Retrieval Benchmarkscited by 1
- 2026A Theoretical Framework for Adaptive Utility-Weighted Benchmarkingcited by 0
- 2026Hypothesis Testing with Conditional Queries: Learnability and the Value of Interactioncited by 0
- 2026Hypothesis Testing with Conditional Queries: Learnability and the Value of Interaction6 Aug 2026
- 2026Brittlebench: Quantifying LLM robustness via prompt sensitivity27 Feb 2026
- 2026A Theoretical Framework for Adaptive Utility-Weighted Benchmarking12 Feb 2026
- 2025skLEP: A Slovak General Language Understanding Benchmark26 Jun 2025
- 2024AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledge18 Dec 2024
- 2023Meta Semantic Template for Evaluation of Large Language Models1 Oct 2023
- 2023A Survey on Evaluation of Large Language Models6 Jul 2023
- 2023Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Models22 May 2023
- 2022Fighting FIRe with FIRE: Assessing the Validity of Text-to-Video Retrieval Benchmarks10 Oct 2022
- 2022KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models23 Aug 2022
- 2022RealTime QA: What's the Answer Right Now?27 Jul 2022
- 2022Perturbation Augmentation for Fairer NLP25 May 2022