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cs.LG2026
Segment to Focus: Guiding Latent Action Models in the Presence of Distractors
Marcus Fechner, Hamza Adnan, Constantin C. Lüth +3
Latent action models (LAMs) offer a promising path to pre-training embodied agents on large amounts of action-free video. They infer latent actions between consecutive observations…
cs.LG2025
GoalLadder: Incremental Goal Discovery with Vision-Language Models
Alexey Zakharov, Shimon Whiteson
Natural language can offer a concise and human-interpretable means of specifying reinforcement learning (RL) tasks. The ability to extract rewards from a language instruction can e…