arXiv:2604.24191v1 Announce Type: new
Abstract: Omnimodal understanding entails a massive, highly redundant search space of cross-modal interactions, demanding focused and deliberative reasoning. Current reasoning paradigms rely on either sequential s…
arXiv:2604.23623v1 Announce Type: new
Abstract: Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit step-by-step reasoning before generating final answer…
arXiv:2604.24230v1 Announce Type: new
Abstract: Skull-base meningiomas are often characterized by favorable long-term prognosis, yet their anatomical complexity and proximity to critical neurovascular structures make treatment selection challenging. S…
arXiv:2506.11480v4 Announce Type: replace-cross
Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a key technique for enhancing LLMs’ reasoning abilities, yet its data inefficiency remains a major bottleneck. To address this c…
arXiv:2604.24234v1 Announce Type: new
Abstract: The technological maturity of in situ inspection and monitoring methods in additive manufacturing is steadily increasing, enabling more efficient and practical qualification procedures. In this context, …
arXiv:2604.24073v1 Announce Type: cross
Abstract: Modern industrial Deep Learning Recommendation Models typically extract user preferences through the analysis of sequential interaction histories, subsequently generating predictions based on these der…
arXiv:2507.14787v2 Announce Type: replace-cross
Abstract: Hyperspectral imaging (HSI) captures hundreds of narrow, contiguous wavelength bands, making it a powerful tool in biology, agriculture, and environmental monitoring. However, interpreting Visi…
arXiv:2604.23674v1 Announce Type: new
Abstract: With the emergence of large language models (LLMs) and AI agent frameworks, the human-AI co-work paradigm known as Vibe Coding is changing how people code, making it more accessible and productive. In sc…
arXiv:2604.24235v1 Announce Type: new
Abstract: Touchless interaction with medical images is becoming increasingly important in the surgical field, where sterility and continuity of the operational workflow are essential requirements. This work presen…
arXiv:2604.24276v1 Announce Type: new
Abstract: Instance-sensitive losses for semantic segmentation such as blob loss and CC loss were designed to address instance imbalance, ensuring small lesions generate the same gradient as large ones, but operate…