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cs.AI2026
Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers
Giovanni Bonetta, Matteo Merler, Davide Zago +2
Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them directly as policies is expensive and brittle: they must be queried at every ste…
cs.AI2025
ViPlan: A Benchmark for Visual Planning with Symbolic Predicates and Vision-Language Models
Matteo Merler, Nicola Dainese, Minttu Alakuijala +5
Integrating Large Language Models with symbolic planners is a promising direction for obtaining verifiable and grounded plans, with recent works extending this idea to visual domai…