collaborators

5 papers

cs.LG2026

LiSA: Lifelong Safety Adaptation via Conservative Policy Induction

Minbeom Kim, Lesly Miculicich, Bhavana Dalvi Mishra +6

As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line of defense against concrete de…

cs.LG2026

Reinforcement Learning with Backtracking Feedback

Bilgehan Sel, Vaishakh Keshava, Phillip Wallis +3

Addressing the critical need for robust safety in Large Language Models (LLMs), particularly against adversarial attacks and in-distribution errors, we introduce Reinforcement Lear…

cs.CR2026

CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution

Minbeom Kim, Mihir Parmar, Phillip Wallis +5

AI agents equipped with tool-calling capabilities are susceptible to Indirect Prompt Injection (IPI) attacks. In this attack scenario, malicious commands hidden within untrusted co…

cs.LG2025

Adversarial Reinforcement Learning for Large Language Model Agent Safety

Zizhao Wang, Dingcheng Li, Vaishakh Keshava +4

Large Language Model (LLM) agents can leverage tools such as Google Search to complete complex tasks. However, this tool usage introduces the risk of indirect prompt injections, wh…

cs.CL2025

Backtracking for Safety

Bilgehan Sel, Dingcheng Li, Phillip Wallis +3

Large language models (LLMs) have demonstrated remarkable capabilities across various tasks, but ensuring their safety and alignment with human values remains crucial. Current safe…