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cs.CL2026
TrustMI: Causally controlling how assistants trust their users
Théo Lasnier, Romain Froger, Maxence Lasbordes +1
Large Language Model (LLM) assistants routinely decide whether they can trust users and third parties whose competence, intentions, and integrity they cannot verify. This uncertain…
cs.CL2026
OmnilingualGAIA2: Evaluating the Multilingual Gap in Frontier AI Agents
Andrea Caciolai, Pere-Lluís Huguet Cabot, Chierh Cheng +11
Agentic benchmarks aim to measure how well AI agents plan, search, execute, and recover within realistic multi-tool environments, but they are almost exclusively in English. As AI…