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Evidence record 15648 · automatically gathered

FairFund-Bench: Evaluating Distributive Bias in LLM Resource Allocation

arXiv:2607.28934v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly involved in the distribution of scarce resources, raising concerns about biased allocations based on characteristics like race and gender. Recent LLM audits have produced inconsistent results, however, finding evidence of both positive and negative discrimination towards women and ethnic minorities, even for the same models. We show that this disagreement can arise from differences in audit format and

Record details

Published: 3 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Bias & fairness · Transparency
Retrieved: 3 August 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: Transparency

Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges

arXiv cs.CY · 3 August 2026

Shared topic: Bias & fairness · Shared topic: Transparency

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Frontiers in Artificial Intelligence · 3 August 2026

Shared topic: Bias & fairness · Shared topic: Transparency

Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability

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Shared topic: Bias & fairness · Shared topic: Transparency

Who Should Be Generated? Justifying Demographic Targets in Open-Ended Generation

arXiv · 3 August 2026

Shared topic: Bias & fairness · Shared topic: Transparency

GoT-CD: Graph-of-Thoughts Causal Discovery and the Fragility of Post-hoc Path-Specific Fairness Audits

arXiv fairness query · 3 August 2026

Shared topic: Bias & fairness · Shared topic: Transparency

AIDLC–governance indicator framework: a lifecycle-based approach to institutional AI governance

AI & Society · 4 August 2026

How to cite this record

ethics.ai (3 August 2026), “FairFund-Bench: Evaluating Distributive Bias in LLM Resource Allocation,” evidence record 15648, https://ethics.ai/record/15648 (originally published by arXiv cs.CY).

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