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arXiv:2602.12317v1 Announce Type: cross Abstract: Medical image foundation models (MIFMs) have demonstrated remarkable potential for a wide range of clinical tasks, yet their development is …
arXiv:2602.12322v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models convert high-level language instructions into concrete, executable actions, a task that is especially challenging in open-world environments. …
arXiv:2602.12342v1 Announce Type: cross Abstract: How can we train agents to navigate uncertainty over long horizons? In this work, we propose {\Delta}Belief-RL, which leverages a …
arXiv:2602.12373v1 Announce Type: cross Abstract: The opioid epidemic remains one of the most severe public health crises in the United States, yet evaluating policy interventions …
arXiv:2602.12375v1 Announce Type: cross Abstract: Optimistic value estimates provide one mechanism for directed exploration in reinforcement learning (RL). The agent acts greedily with respect to …
arXiv:2602.12384v2 Announce Type: cross Abstract: Understanding why gradient-based training in deep networks exhibits strong implicit bias remains challenging, in part because tractable singular-value dynamics are …
arXiv:2602.12390v1 Announce Type: cross Abstract: We study neural networks with trainable low-degree rational activation functions and show that they are more expressive and parameter-efficient than …
arXiv:2602.12393v1 Announce Type: cross Abstract: DragDiffusion is a diffusion-based method for interactive point-based image editing that enables users to manipulate images by directly dragging selected …
arXiv:2602.12395v1 Announce Type: cross Abstract: Reinforcement learning (RL) with verifiable rewards has become a standard post-training stage for boosting visual reasoning in vision-language models, yet …
arXiv:2602.12402v1 Announce Type: cross Abstract: Analog and mixed-signal (AMS) integrated circuits (ICs) lie at the core of modern computing and communications systems. However, despite the …
arXiv:2602.12413v1 Announce Type: cross Abstract: If LLM training data is polluted with benchmark test data, then benchmark performance gives biased estimates of out-of-distribution (OOD) generalization. …
arXiv:2602.12422v1 Announce Type: cross Abstract: Cache replacement remains a challenging problem in CPU microarchitecture, often addressed using hand-crafted heuristics, limiting cache performance. Cache data analysis …