2 papers
cs.AI2026
Introspection Adapters: Training LLMs to Report Their Learned Behaviors
Keshav Shenoy, Li Yang, Abhay Sheshadri +4
When model developers or users fine-tune an LLM, this can induce behaviors that are unexpected, deliberately harmful, or hard to detect. It would be far easier to audit LLMs if the…
cs.CR2025
MirGuard: Towards a Robust Provenance-based Intrusion Detection System Against Graph Manipulation Attacks
Anyuan Sang, Lu Zhou, Li Yang +4
Learning-based Provenance-based Intrusion Detection Systems (PIDSes) have become essential tools for anomaly detection in host systems due to their ability to capture rich contextu…