AdaVSkip is proposed, which equips each layer with two lightweight routers that independently determine whether visual tokens pass through by or skip the self-attention and MLP modules, and maintains strong task performance with substantially less computation.
Yu-Yao Sun, Tao Deng, Shuang-Hua Li et al.· 0 citations
The frozen collection of ChatGPT Images 2.5 supports analysis of reported model use during a product transition, with source and attribution evidence retained for interpretation, and is released at https://scam.ai/research.
A lightweight, prompt-free extractor that decomposes endpoint recovery into an image-like anchor and a noise-oriented residual, which increases the capability of the model to utilize GPU parallel computation, providing an efficient one-step extraction pipeline with a concise theoretical interpretation.
This is the first study to formulate image-grounded review assistance as a multi-agent vision-language reasoning problem, providing a practical step toward AI-assisted review authoring in e-commerce systems.
U. Nareti, Ayush Bansal, Kumari Priya et al.· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
This work proposes a VLM-driven agentic framework for semantic compositional SVG generation that recursively parses visual scenes into semantic and geometric hierarchies via top-down decomposition, visual grounding, and prompt-driven amodal occlusion recovery, ensuring each component is geometrically complete.
Sehwan Park, Taehoon Kim, Geonhee Han et al.· 0 citations
Open-UniMo, a unified Large Motion-Language Model (LMLM) trained on million-scale open-world motion-language data, and Open-MoBench, a VLM-guided benchmark for assessing text-to-motion (T2M) generation, motion-to-text (M2T) understanding, and bidirectional consistency are proposed.
Guo-Cun Wang, Kenkun Liu, Guo-Rui Song et al.· 0 citations
Development and evaluation of computational pathology methods require access to large and diverse datasets. Over the past decade, various initiatives invested significantly into collecting, centralizing, and sharing pathology imaging data. In contrast, sharing of image-derived data such as region-of-interest delineatio...
Daniela P. Schacherer (Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany) et al.· 0 citations
Parkinson's disease (PD) manifests early neuromotor impairments that become observable in controlled hand-drawn patterns such as spirals and meanders, where tremor-induced oscillations, stroke irregularity, and curvature instability reflect underlying motor degradation. In this work, we present an explainable framework...
WAVIE (Wavelet Augmented Vision Intermediate Embeddings) is proposed, an end-to-end architecture that combines complementary spatial and frequency cues on top of a frozen CLIP backbone that outperforms several state-of-the-art generalization baselines for deepfake detection in the wild.
Arya Pulkit, Aditya Ruhela, Akarshan Kapoor et al.· 0 citations
A generative AI integrated multimodal ReID framework designed explicitly for robustness under missing cues and low latency deployment is proposed, with a cost aware early-exit cascade that prioritizes inexpensive, high confidence evidence and only triggers expensive modalities for ambiguous cases.
León Fernando, C. Dombawala, P. Hettigoda et al.· 0 citations
SpermYOLO is an effective and efficient approach for sperm detection in challenging microscopic imaging scenarios and introduces four architectural improvements: C3k2-IDB for channel-wise discriminative feature extraction, D2SEM for spatial--spectral semantic enhancement, MFM for adaptive multi-scale feature fusion, an...
Sheng-Qi Chen, Zi-Lin Wang, Xing-Yu Pan et al.· 0 citations
High-mix low-volume (HMLV) manufacturing requires inspection systems to adapt to changing parts, specifications, and work orders without repeated task-specific programming. Existing inspection automation typically assumes predefined sensing sequences, while general purpose robot agents optimize task completion rather t...
Zhiling Chen, Jingzhan Ge, Ruimin Chen et al.· 0 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.