In preprints posted this week, three groups argue the same thesis from different directions: a robot that can imagine what happens next is worth more than a bigger policy that only reacts.
Three preprints posted this week make video models cheaper to run and harder to fool: agentic evidence grounding, training-free constant-memory frame packing, and 4K super-resolution on a single consumer GPU.
Four preprints posted this week push the same idea: agents that improve themselves inside the terminal — building their own environments, refining their own harnesses, and designing interfaces they can actually use.
In preprints posted this week: a router that picks text vs. visual memory per step, a latent world-action model that cuts inference latency 98.9%, and an evolving evidence interface that shaves 8-15% off input tokens.
In preprints posted this week: a 203-task benchmark where the best agent scores 63.4%, a workspace harness that beats the field by 16 points on BrowseComp-Plus, and a dual-system architecture that trades deliberation for speed.
RSIPO, DeltaTTG, TPPO, Ares and SALD all target sample efficiency. In preprints posted this week, the authors report gains over GRPO and PPO baselines without proportional compute increases.
CineRecon, ExeWorldBench and a psychometric audit of synthetic respondents all point the same way: in preprints posted this week, the authors report that current models stumble on physical and behavioral realism.