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VLMs can now get a million-scale boost in chart-understanding abilities thanks to a new dataset with paired code, images, data, and reasoning.
Ditch the critic: This new reinforcement learning approach trains feature extractors for human activity recognition without needing a value function, leading to more stable and generalizable performance across diverse users.
Scaling up LLMs boosts combinatorial creativity in code generation, but plateaus on exploratory tasks, revealing a "convergence-by-scaling" effect where larger models become less divergent.
Ditch the pixel-level rendering and external executors: LatentGeo learns continuous latent visual representations to internalize auxiliary geometric constructions for multimodal geometric reasoning, boosting performance on complex geometry problems.
