RESEARCHMonitorWATCHLIST
Evaluating Language Model Safety Across Long Adversarial Conversations
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
New research evaluates LLM safety across multi-turn adversarial conversations, exposing vulnerabilities missed by single-prompt testing.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 1 October 2026
- Collected by OneBench
- 2 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2609.38357v1 Announce Type: new Abstract: Conversational safety evaluations often test language models with a single harmful prompt, even though real-world systems interact with users through…
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