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Brittlebench: Quantifying LLM robustness via prompt sensitivity
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Researchers introduced Brittlebench, a framework measuring LLM performance degradation caused by noisy or rephrased user prompts.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 23 October 2026
- Collected by OneBench
- 24 Oct 2026, 03:02 UK
- Original headline
- Brittlebench: Quantifying LLM robustness via prompt sensitivity ↗
Stored source excerpt
arXiv:2603.13285v4 Announce Type: replace Abstract: Existing evaluation methods largely rely on clean, static benchmarks, which can overestimate true model performance by failing to capture the…
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