arXiv:2603.27999v2 Announce Type: replace
Abstract: Personalization in emotion recognition (ER) is essential for an accurate interpretation of subtle and subject-specific expressive patterns. Recent advances in vision-language models (VLMs) such as CL…
arXiv:2603.29176v1 Announce Type: cross
Abstract: Parkinson’s disease (PD) affects over ten million people worldwide. Although temporal interference (TI) and deep brain stimulation (DBS) are promising therapies, inter-individual variability limits emp…
arXiv:2511.08917v3 Announce Type: replace-cross
Abstract: Vision-Language Models (VLMs) are increasingly used by blind and low-vision (BLV) people to identify and understand products in their everyday lives, such as food, personal care items, and hous…
arXiv:2602.14975v2 Announce Type: replace-cross
Abstract: Following our previous work (J. Phys. Chem. Lett., 2026, 17, 5, 1288-1295), we propose the DMTS-NC approach, a distilled multi-time-step (DMTS) strategy using non-conservative (NC) forces to fu…
arXiv:2512.00818v2 Announce Type: replace-cross
Abstract: MLLMs MLLMs are beginning to appear in clinical workflows, but their ability to perform complex medical reasoning remains unclear. We present Med-CMR, a fine-grained Medical Complex Multimodal …
arXiv:2603.29438v1 Announce Type: cross
Abstract: Semantic segmentation and hyperspectral unmixing are two central problems in spectral image analysis. The former assigns each pixel a discrete label corresponding to its material class, whereas the lat…
arXiv:2512.10805v2 Announce Type: replace-cross
Abstract: Sparse autoencoders (SAEs) promise a unified approach for mechanistic interpretability, concept discovery, and model steering in LLMs and LVLMs. However, realizing this potential requires learn…
arXiv:2603.29449v1 Announce Type: new
Abstract: Minimizing invasive diagnostic procedures to reduce the risk of patient injury and infection is a central goal in medical imaging. And yet, noninvasive diagnosis of perineural invasion (PNI), a critical …
arXiv:2603.28768v1 Announce Type: cross
Abstract: Mixture-of-Experts (MoE) has recently emerged as the mainstream architecture for efficiently scaling large language models while maintaining near-constant computational cost. Expert parallelism distrib…
arXiv:2603.29460v1 Announce Type: new
Abstract: Superpixels provide a compact region-based representation that preserves object boundaries and local structures, and have therefore been widely used in a variety of vision tasks to reduce computational c…