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SFT on interleaved plot-solution data *hurts* geometric reasoning in MLLMs, but a novel RL framework called Faire flips the script to achieve state-of-the-art performance by enforcing causal constraints.
A principled framework for General World Models reveals the limitations of current systems and the architectural requirements for future progress.
Visual reasoning gets a boost: forcing models to "draft" their reasoning in code and render visual proofs dramatically improves performance by bridging the gap between perception and logical structure.
