PII-TRACE: A Benchmark for Context-Aware PII Detection in Multi-Turn LLM Conversations
LLM assistants and agentic systems log long multi-turn conversations. AI providers often scan these conversations for Personally Identifiable Information (PII) and mask the PII before storing or processing conversation data. Yet most PII detectors and benchmarks target self-contained records rather than cross-turn evaluation. To evaluate PII detection across turns in multi-turn conversations, we introduce PII-TRACE (Tracing Recurring PII Across Conversational Exchanges), to our knowledge the first PII benchmark to assess whether detectors identify PII in conversational contexts and cover every mention of a recurring identifier across turns. PII-TRACE contains 13,148 synthetic multi-turn d...
| Authors | Kaiyuan Zhang, Chuan Wang, Joey Zhong et al. |
|---|---|
| Primary category | cs.CL |
| Published | 31 August 2026 |
| Last updated at source | 31 August 2026 |
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- perplexity-ai/PII-Tracer-MLXModel · cited by
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