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It is demonstrated that effective world-action modeling does not require predicting native visual futures, and that compact predictive representations provide a strong and substantially more efficient target for policy learning.
Athena-Brain-8B, an 8B LLM designed to serve as an on-device brain for embodied intelligence for embodied intelligence, is presented, demonstrating that compact language models can effectively integrate strong general intelligence with embodied capabilities.
Capek 0.5 is presented, an embodied vision-language model built around an execution-centric capability taxonomy that improves the large majority of matched benchmark rows over its initialization, retains all four specialized capabilities in one checkpoint with quantified losses, and transfers to closed-loop embodied ta...
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