EBM
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Reward-Decomposed Reinforcement Learning for Immersive Video Role-Playing
arXiv:2605.04733v2 Announce Type: replace Abstract: Text-based role-playing models can imitate character styles, but often fail to capture scene atmosphere and evolving tension, which are crucial for immersive applications such as VR games and interactive narratives. We study video-grounded role-playing dialogue and introduce EBM-RL (Eye--Brain--Mouth Reinforcement Learning), a decoupled GRPO-based framework that separates observation (), reasoning (), and utterance generation (). This...
First Principles Magnetohydrodynamical Theory for the Expanding Box Model
arXiv:2606.10283v1 Announce Type: new Abstract: The Expanding Box Model (EBM) has been widely employed to simulate multiscale plasma phenomena in the expanding solar wind by transforming the MHD equations to a co-moving, non-inertial frame. However, traditional formulations have suffered from historical ambiguity regarding the physical separation between the co-moving and inertial reference frames, primarily arising from a classical approximation of an invariant magnetic field between them....
A faster way to forecast alien weather
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FlagGAM: Rule-Based Generalized Additive Modeling for Explainable Tabular Prediction
arXiv:2605.31189v1 Announce Type: new Abstract: Tabular prediction in high-stakes domains requires models that are accurate, transparent, and robust to imperfect inputs. We propose FlagGAM, a rule-defined basis framework that separates feature-level rule construction from prediction. A Flag Core Module converts numerical and categorical variables into sparse, human-readable univariate bases, including threshold flags, category-level flags, tail-deviation bases, and categorical step...