3 papers
cs.CL2026
Evaluating Communicative Belief Updates in Large Language Models via Implicature Recognition and Cancellation
Cesare Spinoso-Di Piano, Verna Dankers, Marius Mosbach +1
Human language is driven by unspoken beliefs and belief updates, making these critical to model for successful communication between large language models (LLMs) and their users. I…
cs.CL2026
LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning
Matteo Boglioni, Thibault Rousset, Siva Reddy +2
LLMs memorize sensitive training data, including personally identifiable information (PII), creating a pressing need for reliable post hoc removal methods. Unlearning has emerged a…
cs.CR2026
Toward Open Weight Models Without Risks: Separating Public and Private Capabilities in LLMs
Charbel El Feghali, Arkil Patel, Nicholas Meade +3
Open-weight Large Language Models (LLMs) enable scientific progress and broad deployment. However, they make it difficult to control access to sensitive capabilities. Current pract…