ProvenanceGuard applies a provenance-based framework to detect three types of misalignment in LLM agent tool calls, cutting error rates on misaligned traces from 42.9% to 1.8% on one benchmark while lowering unnecessary interventions.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
representative citing papers
A 3x3 between-subjects experiment finds that risk-contingent autonomy in LLM agents attenuates personalization's negative effects on privacy concerns and trust via increased perceived control.
citing papers explorer
-
Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents
A 3x3 between-subjects experiment finds that risk-contingent autonomy in LLM agents attenuates personalization's negative effects on privacy concerns and trust via increased perceived control.