ArticleNature communications2022
Mapping global dynamics of benchmark creation and saturation in artificial intelligence.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed.
- A clinically validated framework for auditing AI chatbot behavior in mental health interactions.Nature medicine · 2026Article
- Artificial intelligence in drug discovery - what it is, where we stand and the path forward.Nature reviews. Drug discovery · 2026Review
- Benchmarking large language models against practicing clinicians on psychopathological assessment.NPJ digital medicine · 2026Article
- Airway segmentation on CT - A systematic review of machine learning tools.European journal of radiology open · 2026Article
- Quantum ensembling methods for healthcare and life science.Briefings in bioinformatics · 2026Article
- It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety.JMIR mental health · 2026Article
- A Benchmark Dataset of Chinese Development Finance with Climate Relevance and SDG Annotations from 2000-2021.Scientific data · 2026Article
- Computational hermeneutics: evaluating generative AI as a cultural technology.Frontiers in artificial intelligence · 2026Article
- AI without representation is just inequity at scale: on the exportation of unrepresentative artificial intelligence models to the Global South.Frontiers in artificial intelligence · 2026Article
- The Future of Artificial Intelligence in Ecosystem Modeling.Bioscience · 2026Article
- Article
- DCEM-TCRCN: an innovative approach to depression detection using wearable IoT devices and deep learning.International journal of computer assisted radiology and surgery · 2025Article
- How good are large language models at product risk assessment?Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- State-of-the-Art: The Temporal Order of Benchmarking Culture.Digital society : ethics, socio-legal and governance of digital technology · 2025Article
- Mapping global dynamics of benchmark creation and saturation in artificial intelligence.Nature communications · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Benchmarks are crucial to measuring and steering progress in artificial intelligence (AI). However, recent studies raised concerns over the state of AI benchmarking, reporting issues such as benchmark overfitting, benchmark saturation and increasing centralization of benchmark dataset creation. To facilitate monitoring of the health of the AI benchmarking ecosystem, we introduce methodologies for creating condensed maps of the global dynamics of benchmark creation and saturation. We curate data for 3765 benchmarks covering the entire domains of computer vision and natural language processing, and show that a large fraction of benchmarks quickly trends towards near-saturation, that many benchmarks fail to find widespread utilization, and that benchmark performance gains for different AI tasks are prone to unforeseen bursts. We analyze attributes associated with benchmark popularity, and conclude that future benchmarks should emphasize versatility, breadth and real-world utility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.