arXiv:2503.22886v2 Announce Type: replace Abstract: Recent advancements in imitation learning have led to transformer-based behavior foundation models (BFMs) that enable multi-modal, human-like control for humanoid agents. While excelling at zero-shot generation of robust behaviors, BFMs often require meticulous prompt engineering…
arXiv:2603.25901v1 Announce Type: new Abstract: Defensive coverage schemes in the National Football League (NFL) represent complex tactical patterns requiring coordinated assignments among defenders who must react dynamically to the offense’s passing concept. This paper presents a factorized attention-based transformer model…
arXiv:2510.05516v2 Announce Type: replace Abstract: Bayesian optimization (BO) is effective for expensive black-box problems but remains challenging in high dimensions. We propose NeST-BO, a curvature-aware local BO method that targets a (modified) Newton step by jointly learning gradient and Hessian…
arXiv:2603.25916v1 Announce Type: new Abstract: We study dynamic regret minimization in unconstrained adversarial linear bandit problems. In this setting, a learner must minimize the cumulative loss relative to an arbitrary sequence of comparators $boldsymbol{u}_1,ldots,boldsymbol{u}_T$ in $mathbb{R}^d$, but receives only point-evaluation…
arXiv:2601.21419v2 Announce Type: replace Abstract: Recent advances in diffusion and flow matching models have highlighted a shift in the preferred prediction target — moving from noise ($varepsilon$) and velocity (v) to direct data (x) prediction — particularly in high-dimensional settings.…
arXiv:2603.25923v1 Announce Type: new Abstract: Deep learning models have shown promise in EEG-based outcome prediction for comatose patients after cardiac arrest, but their reliability is often compromised by subtle forms of data leakage. In particular, when long EEG recordings are…
arXiv:2603.22885v3 Announce Type: replace Abstract: BACKGROUND: General aviation fleet expansion demands intelligent health monitoring under computational constraints. Real-world aircraft health diagnosis requires balancing accuracy with computational constraints under extreme class imbalance and environmental uncertainty. Existing end-to-end approaches suffer from the…
arXiv:2603.25925v1 Announce Type: new Abstract: Game-based learning (GBL) is widely adopted in mathematics education. It enhances learners’ engagement and critical thinking throughout the mathematics learning process. However, enabling players to learn intrinsically through mathematical games still presents challenges. In particular,…
arXiv:2507.03745v4 Announce Type: replace-cross Abstract: Recently, great progress has been achieved in text-to-video (T2V) generation by scaling transformer-based diffusion models to billions of parameters, which can generate high-quality videos. However, existing models typically produce only short clips offline, restricting their…
arXiv:2603.25954v1 Announce Type: new Abstract: The use of satellite networks has increased significantly in recent years due to their advantages over purely terrestrial systems, such as higher availability and coverage. However, to effectively provide these services, satellite networks must cope…
