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How Do LLMs Change Predictions Under Negation?
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Researchers find LLMs fail to handle negation in 37-71% of test cases, frequently returning identical answers for negated prompts.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 8 October 2026
- Collected by OneBench
- 9 Oct 2026, 03:01 UK
- Original headline
- How Do LLMs Change Predictions Under Negation? ↗
Stored source excerpt
arXiv:2610.09571v1 Announce Type: new Abstract: Negation is an essential feature of human language, yet large language models (LLMs) remain unreliable in processing it. We evaluate…
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