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Evidence record 4229 · automatically gathered

GPF-LiveNews: A Streaming Evaluation Protocol for Group-Conditioned Framing in Large Language Models

Deployed language models are evaluated in a non-stationary environment: model versions, retrieval layers, safety systems, and real-world inputs all change over time. Static bias benchmarks remain useful, but they do not show how models frame newly emerging events for different prompted audiences. We introduce GPF-LIVENEWS, a streaming evaluation protocol and benchmark snapshot for auditing group-conditioned framing in open-ended LLM outputs. The protocol expands fresh BBC/Reuters news anchors ac

Record details

Published: 16 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Transparency · Environment
Retrieved: 14 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.

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How to cite this record

ethics.ai (16 May 2026), “GPF-LiveNews: A Streaming Evaluation Protocol for Group-Conditioned Framing in Large Language Models,” evidence record 4229, https://ethics.ai/record/4229 (originally published by arXiv).

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