Search: “multimodal”

arXiv:2607.17612v2 Announce Type: replace Abstract: Continuous diffusion models have become the dominant paradigm for photo-realistic image Super-Resolution (SR), but they typically formulate reconstr

arXiv:2607.20142v1 Announce Type: new Abstract: We present a two-stage vision system that detects EEG cap electrodes in a live webcam stream and validates their anatomical placement in real time. A si

arXiv:2607.20159v1 Announce Type: new Abstract: Attention Mechanism (AM) selectively focuses on essential information for imaging tasks and captures relationships between distant pixel neighborhoods t

// Global Workspace in LLMs // arXiv paper for the popular J-space work from Anthropic. (bookmark it) The short recap: If you build on chain-of-thought or steering vectors, this work provides a mechan

arXiv:2607.13067v1 Announce Type: new Abstract: Teleoperating remotely operated vehicles (ROVs) in flooded, cluttered infrastructure is fundamentally limited by narrow 2D egocentric views and subsea c

arXiv:2607.13188v1 Announce Type: new Abstract: Human cognition does not separate understanding and generation. A teacher at a whiteboard speaks and draws extit{together}, each modality reshapes the o

arXiv:2603.19063v2 Announce Type: replace Abstract: Most existing robot simulators prioritize rigid-body dynamics and photorealistic rendering, but largely neglect the thermally and optically complex

arXiv:2607.13072v1 Announce Type: cross Abstract: Zero-shot object-goal navigation aims to enable an intelligent agent to explore and navigate to objects of unknown categories in an unfamiliar environ

arXiv:2607.13618v1 Announce Type: new Abstract: LLM agents are increasingly evaluated on multi-week decision tasks in which the state that drives cost is never directly observed. On such tasks the fin

arXiv:2607.13660v1 Announce Type: new Abstract: Contrastive Language-Image Pretraining (CLIP) representations form a semantic embedding space governed by cosine similarity, reflecting an intrinsic hyp

arXiv:2607.13506v1 Announce Type: new Abstract: Active surveillance (AS) is the preferred strategy for favorable-risk prostate cancer, yet current protocols rely on scheduled repeat biopsies, most of

arXiv:2607.09807v2 Announce Type: replace Abstract: This paper presents the design and evaluation of a myoelectric tentacle-shaped prosthesis integrating electromyographic (EMG) control, sensorless ob

arXiv:2607.12358v1 Announce Type: new Abstract: Video diffusion models produce high-quality generations but remain slow at inference due to their sequential denoising procedure. Caching-based accelera

arXiv:2607.12293v1 Announce Type: new Abstract: Predicting pedestrian crossing intention is a safety-critical task for autonomous driving, yet existing approaches often rely on single-modal inputs or

arXiv:2607.12051v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical decision support, but their reliability in complex oncology treatment planning

arXiv:2607.12048v1 Announce Type: cross Abstract: Deploying medical visual question answering (MedVQA) systems in real-world clinical settings requires models that adapt to new clinical tasks without

arXiv:2607.12181v1 Announce Type: new Abstract: Robot gaze is a major component of human-robot dialogue coordination. Most studies of gaze in human-robot dialogue focus on face-to-face social conversa

arXiv:2607.12750v1 Announce Type: new Abstract: Colorectal cancer (CRC) is the third most common cancer worldwide and the second leading cause of cancer-related deaths globally, with approximately 1,9

arXiv:2607.11638v2 Announce Type: replace Abstract: City-scale outdoor navigation is currently hindered by the heavy reliance on dense maps or costly navigation supervision. In this work, we introduce

arXiv:2509.15120v2 Announce Type: replace Abstract: In high-stakes scenarios, such as medical imaging applications, it is critical to equip the predictions of a regression model with reliable confiden

arXiv:2607.12454v1 Announce Type: new Abstract: Multivariate Time Series Anomaly Detection (MTSAD) is essential for reliability and safety in domains such as industrial process monitoring and financia

arXiv:2607.12785v1 Announce Type: new Abstract: Robot-assisted minimally invasive surgery (MIS) critically depends on reliable endoscopic perception for navigation and safety. However, conventional en

arXiv:2607.11464v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) addresses the limitations of Large Language Models (LLMs) when providing responses to domain-specific questions.

arXiv:2607.12260v1 Announce Type: new Abstract: Early screening of chronic kidney disease (CKD) is essential for preventing irreversible progression; however, many machine learning (ML)-based screenin

arXiv:2607.11656v2 Announce Type: replace-cross Abstract: Accurate diagnostic classification and disease-severity prediction for Alzheimer's disease are hampered by the incompleteness and heterogeneit

arXiv:2505.22108v4 Announce Type: replace-cross Abstract: Background: Federated learning (FL) enables collaborative training of clinical AI models without centralizing patient data, but adoption is li

arXiv:2607.11875v2 Announce Type: replace-cross Abstract: We present a theoretical framework to explain the emergence of inductive reasoning abilities in Transformer language models. While previous wo

arXiv:2505.15284v2 Announce Type: replace-cross Abstract: Out-of-Distribution (OoD) detection is vital for the reliability of deep neural networks, the key of which lies in effectively characterizing

arXiv:2607.11974v1 Announce Type: cross Abstract: Most neural partial differential equation (PDE) surrogates learn how fields evolve after a grid has already been chosen. However, before any operator

arXiv:2607.12681v1 Announce Type: new Abstract: State space models (SSMs), notably Mamba, have recently emerged as efficient alternatives to self-attention with linear computational complexity. We inv

arXiv:2607.12257v1 Announce Type: new Abstract: On-device research agents search a corpus, read sources, and write a cited brief on a personal laptop. Whether their citations are faithful, and at what

Visual generative models (e.g., diffusion models) typically operate in compressed latent spaces to balance training efficiency and sample quality. In parallel, there has been growing interest in lever

arXiv:2607.12111v1 Announce Type: cross Abstract: Agentic AI systems are reshaping communications and networking by deploying autonomous intelligent agents capable of collaborative learning while main

arXiv:2607.12399v1 Announce Type: new Abstract: Objective: Radiomic texture features are usually computed in voxel-index neighborhoods, implicitly assuming isotropic spatial relationships. In anisotro

arXiv:2607.12292v1 Announce Type: new Abstract: Crack segmentation is essential for infrastructure inspection and structural health assessment, but existing high-performance methods typically require

arXiv:2607.12497v1 Announce Type: new Abstract: Beyond perception, reasoning is essential in remote sensing for advanced interpretation, inference, and decision-making. Recent advances in large langua

arXiv:2607.12447v1 Announce Type: cross Abstract: Reliable confidence -- the probability that a model's own answer is correct -- is essential for the trustworthy deployment of language models. Existin

arXiv:2607.12290v1 Announce Type: cross Abstract: Audio-language embedding models such as CLAP are widely evaluated on matching present sound events, but rarely on negation. We show this affirmation-o

arXiv:2603.04113v2 Announce Type: replace-cross Abstract: Demographic attributes can be predicted from medical images, raising concerns about bias in clinical AI systems. In X-ray imaging, acquisition

The NVIDIA Nemotron Model Reasoning Challenge on Kaggle attracted over 5,000 participants who all began from the same open model, benchmark, and infrastructure. The strongest solutions treated reasoni

New research from Google DeepMind on effective model routing. LLM routers get judged on accuracy and cost. Both can look great while the router is meaningless. If every model in your society responds

Proactive agents that anticipate user needs and autonomously execute tasks hold great promise as digital assistants, yet the lack of realistic user simulation frameworks hinders their development. Exi

In this post, we share how Flo Health’s engineering team turned a proof of concept (PoC) from the AWS Generative AI Innovation Center into a production-grade, AI-powered medical content review and gen

Standard RL benchmarks are episodic and stationary, so they don't capture the the characteristics of real-world deployment. Morpheus is a new benchmark for continual learning that provides persistent

arXiv:2607.08191v1 Announce Type: new Abstract: RGB-Thermal (RGBT) Video Object Detection (VOD) has gained significant traction due to its ability to overcome the limitations of conventional RGB-based

arXiv:2607.06691v1 Announce Type: new Abstract: Human-human collaboration is a fundamental aspect of everyday life, essential to success in a wide range of goal-directed activities from household task