Category
4,009 papers
A task-oriented framework that bypasses image reconstruction and directly transmits semantic features extracted by a multitask-pretrained backbone is investigated, with the largest improvements in the low-SNR regime.
HyperAMS-Net is proposed, a deep learning framework for brain disorder classification using neuroimaging representations derived from resting-state functional MRI or structural MRI that integrates adaptive multi-scale convolution, hypergraph attention, spatial-channel attention, and adaptive feature fusion.
Recent innovations in deep learning have significantly enhanced the diagnosis of medical images, although they are based on the use of centralized data storage that pose severe threats to patient privacy and medical data security. To address this issue, this research proposes a Federated Learning (FL) model that is cou...
It is suggested that mammography foundation models can recover clinically relevant cardiovascular risk information directly from mammographic pixels and suggest that screening mammography may provide an opportunistic source of cardiovascular risk information to complement conventional clinical assessment without additi...
Reach audiences
Advertise in front of researchers, engineers, and readers.
WorldRoamBench is introduced, an open-world benchmark for long-horizon stability across four dimensions, each with innovations, steps toward IWMs that are stable, physically grounded, memory-faithful, and deployable in real-world applications.
A multi-modal brain age framework to characterize the integrated evolution of brain morphology and white matter organization is developed and analysis of ADNI clinical groups suggests the potential of the predicted brain age gap to characterize Alzheimer's-related brain aging.
This work introduces StarVLA-$\alpha, a simple yet strong baseline designed to study VLA design choices under controlled conditions that deliberately minimizes architectural and pipeline complexity to reduce experimental confounders and enable systematic analysis.
The results show that model size strongly affects generation quality, multimodal training improves the use of individual modalities, and multimodal inference provides a stronger contextual signal than isolated context inputs.
Short-form video moderation is increasingly pushed toward edge and privacy-sensitive settings, where users may intend videos for a limited audience, such as friends or private groups, but sending raw clips to a central server can broaden exposure, consume bandwidth, and add moderation latency. Federated learning can ke...
Across face-manipulated and fully synthetic content, FORGE produces region-referential explanations answering fine-grained attribute queries and substantially outperforms in-domain baselines on cross-domain evaluations; region-specific evaluation and human studies confirm explanation faithfulness.
It is proved that, under a matched fixed-anchor implementation, soft-label cross-entropy and KL divergence differ only by a constant entropy term and therefore induce identical gradients, Hessians, and adversarial optimization trajectories.
Coding agents have emerged as a promising paradigm for robot manipulation: a language model writes the robot controller as a program, and agents built in this way now operate robots without robot-specific training.Whether this paradigm is also safe, however, has not been asked. We evaluate coding agent under a safety c...
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
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.
A Blog post by H company on Hugging Face
A Blog post by Liquid AI on Hugging Face
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
