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cs.AI2026
You Can't Have It Both Ways: Concept Entanglement Limits Diffusion Model Unlearning
Yian Wang, Ali Ebrahimpour-Boroojeny, Hari Sundaram +1
Concept unlearning in text-to-image diffusion models aims to suppress a target concept (e.g., \texttt{horse}) while preserving related but distinct content (e.g., \texttt{donkey}),…
cs.AI2026
AgentAbstain: Do LLM Agents Know When Not to Act?
Xun Liu, Yi Evie Zhang, Vira Kasprova +5
Agent systems based on large language models (LLMs) are increasingly deployed for autonomous tasks, yet existing evaluations mostly focus on task success rather than whether agents…