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Turns out, telling LLMs *not* to use the answer when generating reverse chain-of-thought reasoning can actually make them *more* reliant on it—but a skeleton-guided approach breaks the cycle.
A 3B parameter model now rivals models 10x its size in reasoning, alignment, and agentic tasks, challenging the assumption that bigger is always better.
Robots can now understand and act on ambiguous instructions like "I'm thirsty" in real-time, thanks to a new framework that combines visual reasoning with interactive exploration.