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ExplorationBench turns the wicked problem of evaluating scientific exploration into a concrete and tractable framework built on verifiable Alien Worlds, and finds that the strongest systems can acquire and apply unfamiliar rules, while performance varies substantially across trajectories and continued exploration can s...
A unified four-step post-training pipeline comprising a learned temporal hand-action codec, supervised fine-tuning, DAgger, and real-world residual reinforcement learning provides a practical path for adapting VLA foundation models to reliable real-world dexterous manipulation.
Atria Dawn Preview is introduced, a foundation agentic language model designed for scientific research and engineering workflows, with the goal of expanding the frontier of agent productivity in the real world.
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