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:2503.05587v3 Announce Type: replace-cross
Abstract: Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustness to explicit noise (e.g., document semantics) but…
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:2604.23701v1 Announce Type: cross
Abstract: Crop disease diagnosis from field photographs faces two recurring problems: models that score well on benchmarks frequently hallucinate species names, and when predictions are correct, the reasoning be…
arXiv:2604.22758v1 Announce Type: cross
Abstract: Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. To meet this demand, systems typically rely on conve…
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…