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Evidence record 11769 · automatically gathered

AgentFAIR: A Multi-Agent Collaborative Framework for FAIRness Evaluation of Geospatial Datasets

Geospatial datasets support applications from urban planning to climate modeling, yet consistent assessment of FAIR compliance is difficult. Existing evaluators use different rubrics and evidence sources and may fail on JavaScript-rendered pages or repository-specific identifiers. For 50 datasets from 10 repositories, the standard deviation of normalized scores across available tools averages 15.0 percentage points and reaches 30.3 for one dataset. Because these outputs are not equivalent measur

Record details

Published: 17 July 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Regulation · Agents & autonomy · Environment
Retrieved: 20 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness · Shared topic: Regulation

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Shared topic: Regulation · Shared topic: Agents & autonomy

AI-Native Insurance for Agentic AI: Pricing, Underwriting, and End-to-End Automation

arXiv cs.CY · 16 July 2026

Shared topic: Regulation · Shared topic: Agents & autonomy

Multi-Turn On-Policy Distillation with Prefix Replay

HuggingFace Daily Papers · 15 July 2026

Shared topic: Regulation · Shared topic: Agents & autonomy

SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning

HuggingFace Daily Papers · 15 July 2026

Shared topic: Regulation · Shared topic: Agents & autonomy

Counterfactual Shapley Credit Assignment

arXiv cs.LG · 18 July 2026

Shared topic: Regulation · Shared topic: Agents & autonomy

Teach it to stop, not just to click

arXiv cs.HC · 19 July 2026

How to cite this record

ethics.ai (17 July 2026), “AgentFAIR: A Multi-Agent Collaborative Framework for FAIRness Evaluation of Geospatial Datasets,” evidence record 11769, https://ethics.ai/record/11769 (originally published by arXiv).

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