Search: “applications”

Trustworthy Medical Segmentation: Uncertainty-Aware U-Net Evaluation Under Clinical Image Degradation

arXiv:2607.22727v1 Announce Type: new Abstract: Medical image segmentation models often report high benchmark accuracy under ideal imaging conditions, yet their failures under clinical degradation can

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Safety

Unifying Complementarity Constraints and Control Barrier Functions for Safe Whole-Body Robot Control

DGX agent

arXiv:2504.17647v2 Announce Type: replace Abstract: Safety-critical whole-body robot control demands reactive methods that ensure collision avoidance in real-time. Complementarity constraints and cont

safetyarxiv-cs-ro

28 Jul 2026

VIP: Finding Important People in Images

arXiv:1502.05678v3 Announce Type: replace Abstract: People preserve memories of events such as birthdays, weddings, or vacations by capturing photos, often depicting groups of people. Invariably, some

VLASH: Real-Time VLAs via Future-State-Aware Asynchronous Inference

arXiv:2512.01031v2 Announce Type: replace-cross Abstract: Vision-Language-Action models (VLAs) are becoming increasingly capable across diverse robotic tasks. However, these models are typically deplo

When Less Is More: A Controlled Benchmark of Lightweight CNNs for Satellite Land-Cover Segmentation on DeepGlobe

arXiv:2607.23024v1 Announce Type: new Abstract: High-resolution satellite imagery is the backbone of good land-cover classification, and without that, environmental monitoring, urban planning, and sus

Which Workloads Belong in Orbit? A Workload-First Framework for Orbital Data Centers Using Semantic Abstraction

arXiv:2603.20317v2 Announce Type: replace Abstract: Space-based compute is becoming plausible as launch costs fall and data-intensive AI workloads grow. This paper proposes a workload-centric framewor

Analysing Self-Harm Representations in Language Models: a Cross-Architecture Study

model-releasesarxiv-cs-cl

arXiv:2607.21988v1 Announce Type: new Abstract: Self-harm content is particularly challenging to detect using NLP techniques, and is also a high-stakes task which requires the highest accuracy to enab

Explicit Iteration Complexity of Exact Data-Driven Inverse Optimization for Integer Linear Programs

model-releasesarxiv-cs-lg

arXiv:2607.22263v1 Announce Type: cross Abstract: A data-driven inverse optimization problem (DDIOP) is the problem of estimating the objective-function parameters (weights) that explain observed opti

Improving Large Vision-Language Models' Understanding for Flow Field Data

arXiv:2507.18311v3 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) have shown impressive capabilities across a range of tasks that integrate visual and textual understanding, suc

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction

arXiv:2508.13826v4 Announce Type: replace-cross Abstract: Cardiac Magnetic Resonance (CMR) imaging is a critical tool for diagnosing and managing cardiovascular disease, yet its utility is often limit

Agents

Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks

arXiv:2607.22313v1 Announce Type: cross Abstract: Estimating contemporaneous bidirectional interactions from observational data is difficult because each outcome is endogenous to the other, while flex

agentsarxiv-cs-lg

LunarFM: A Shared Multimodal Representation of the Moon's Surface

arXiv:2607.22408v1 Announce Type: new Abstract: The renewed global focus on lunar exploration, driven by the prospect of in-situ resource utilization and a sustained human presence on the Moon, has cr

researcharxiv-cs-lg

Medical-Checklist: Assessing the Comprehension of Medical Images by Multimodal Models

arXiv:2607.21998v1 Announce Type: new Abstract: This paper introduces a new benchmark test, Medical-Checklist, for assessing medical multimodal models. The recent advancements in multimodal models hav

Offline Vision-Language Navigation with Geometric Goal Localization for Outdoor Environments

model-releasesarxiv-cs-ro

arXiv:2607.22226v1 Announce Type: new Abstract: Foundation-model-based vision-language navigation (VLN) has advanced autonomous robot navigation by enabling robots to interpret natural-language instru

Plug, Play, and Comply: A Modular Framework for Online Variable Impedance with Arbitrarily Oriented Compliance Axes

arXiv:2607.22483v1 Announce Type: new Abstract: The paper proposes a robot-agnostic compliant-control framework that extends the ROS control ecosystem with standardized joint and Cartesian command int

researcharxiv-cs-ro

Procedural Knowledge Is Not Low-Rank: Why LoRA Fails to Internalize Multi-Step Procedures

model-releasesarxiv-cs-lg

arXiv:2607.21612v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning methods like LoRA have become the default for adapting large language models, succeeding across instruction following,

Local Ai

RED-PIM: Reducing Data Movement for Transformers using Processing-in-Memory

arXiv:2607.21731v1 Announce Type: new Abstract: Transformers are widely used across many domains, including natural language processing, computer vision, web search, and DNA sequence analysis. Given t

local-aiarxiv-cs-lg

Local Ai

SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes

arXiv:2607.21850v1 Announce Type: new Abstract: As semiconductor manufacturing advances toward sub-2nm nodes, local place-and-route (P&R) design-rule violation (DRV) fixing is increasingly limited by

local-aiarxiv-cs-cv

SceneActBench: Can Agents Act on the 3D Scenes They See?

arXiv:2607.22393v1 Announce Type: cross Abstract: Vision-language model (VLM) agents increasingly use tools to act on 3D scenes rather than only describe them. Existing 3D benchmarks score textual res

Hardware

Singular value soft-thresholding via the polar decomposition

arXiv:2607.22484v1 Announce Type: cross Abstract: Singular value soft-thresholding can be computed via a reduction to the matrix polar decomposition, which allows one to exploit GPU-friendly algorithm

hardwarearxiv-cs-lg

Tutorials

Statistical mechanics of extensive-width Bayesian neural networks near interpolation

arXiv:2505.24849v2 Announce Type: replace-cross Abstract: For three decades statistical mechanics has been providing a framework to analyse neural networks. However, the theoretically tractable models

tutorialsarxiv-cs-lg

TDiR: Transformer based Diffusion for Image Restoration Tasks

arXiv:2506.20302v2 Announce Type: replace Abstract: Images captured in challenging environments often experience various types of degradation, such as noise, color cast, blur, and light scattering. Th

TRACE-ROUTER: Task-Consistent and Adaptive Online Routing for Agentic AI

arXiv:2607.22465v1 Announce Type: cross Abstract: Routing to select large language models (LLMs) with different cost-quality trade-offs has become a fundamental deployment feature of enterprise AI. Ex

safetyarxiv-cs-lg

AI-Driven Multi-Hop Relay Selection for Smart Urban NR-V2X Networks via Learning-to-Optimize Graph Neural Networks

arXiv:2607.20554v1 Announce Type: new Abstract: Reliable and low-latency NR-V2X communications are essential for smart mobility in dense urban environments. However, limited Road-Side Unit (RSU) densi

Axolotl3D: a Unified Framework for Faithful 3D Shape Completion

arXiv:2607.20660v1 Announce Type: new Abstract: Recent 3D generative models produce high-quality geometry from a single image using large-scale priors and diffusion architectures. However, they assume

safetyarxiv-cs-cv

Tutorials

Beyond SBDD: Geometric Deep Learning in Polypharmacology and Multi-target Drug Design

arXiv:2607.20550v1 Announce Type: cross Abstract: The traditional 'one drug, one target' paradigm of structure-based drug design (SBDD) frequently proves inadequate for treating multifactorial disease

tutorialsarxiv-cs-ai

Black box behavioural modelling: Predicting human activity schedules with a deep conditional generative approach

arXiv:2512.04223v2 Announce Type: replace Abstract: Modelling the complexity and diversity of human activity scheduling behaviour is inherently challenging. We demonstrate ActVAE, a deep conditional-g

researcharxiv-cs-lg

ClickGuard: Detecting and Spoiling Clickbait News with Informativeness Measures and Large Language Models

arXiv:2607.20463v1 Announce Type: new Abstract: This paper presents an AI-driven browser extension that identifies clickbait to help users avoid misleading Internet articles. Moving beyond traditional

Clustered Edge Intelligence: Beyond Just Convergence of Edge Computing and AI

arXiv:2607.20937v1 Announce Type: new Abstract: We are moving from an information age to the age of intelligence. A decade, or possibly less than that, data will not be the gold anymore rather the der

ConfidenceBench: Evaluating Confidence Calibration in Large Language Models

arXiv:2607.20526v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in settings where fluent but incorrect answers can be costly. In these settings, accuracy alone i

DINOde: Continuous Vision-Text Alignment for Open-Vocabulary Semantic Segmentation

arXiv:2607.21371v1 Announce Type: cross Abstract: Open-vocabulary semantic segmentation (OVSS) leverages textual semantics to segment objects beyond predefined categories. While the self-supervised mo

safetyarxiv-cs-ai

EmoSpace: Immersive Affective Image Generation Guided by Fine-Grained Emotion Prototypes

arXiv:2602.11658v2 Announce Type: replace Abstract: Immersive affective content generation aims to create visually compelling VR imagery with controllable emotional nuance, yet existing methods typica

safetyarxiv-cs-cv

Evaluating the Effectiveness of Persona Simulation in Opinion Prediction with GPT-4.1

model-releasesarxiv-cs-cl

arXiv:2607.20589v1 Announce Type: new Abstract: Persona simulation involves utilizing large language models (LLMs) to anticipate human choices or interactions based on specific characteristic informat

Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testing

arXiv:2507.14268v2 Announce Type: replace Abstract: This paper reviews algorithmic and modeling approaches for fitting generalized power diagrams to three-dimensional image data, a key step in virtual

GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis

arXiv:2607.18218v2 Announce Type: replace-cross Abstract: Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and

GLAM-SLAM: Real-time Gaussian Large-scale Mapping via Flow Densification and Spatial Decomposition

arXiv:2607.21416v1 Announce Type: cross Abstract: Existing Gaussian-splatting-based monocular Simultaneous Localization and Mapping (SLAM) systems are either tailored to short sequences, are not real-

safetyarxiv-cs-cv

Hybrid MKNF with Classical Negation in the Rule Component

arXiv:2607.21202v1 Announce Type: cross Abstract: Hybrid MKNF knowledge bases under the well-founded semantics integrate Description Logics with Logic Programming. However, they do not support classic

safetyarxiv-cs-ai

Inducing Comparability of Factorised Probability Distributions

arXiv:2607.20502v1 Announce Type: new Abstract: To allow for principled comparison between two probabilistic graphical models defined over non-identical variable sets, they have to be lifted to a comm

Instruct-FD: Can Your Full-Duplex Speech System Follow Turn-Taking Instructions?

arXiv:2607.20460v1 Announce Type: cross Abstract: Current full-duplex (FD) spoken dialogue systems can produce fluid interactions, yet it remains unclear whether they can adapt their turn-taking behav

LegalCiteTrust: Benchmarking Citation Trustworthiness in Chinese Long-Form Legal Research Reports

model-releasesarxiv-cs-cl

arXiv:2607.20872v1 Announce Type: new Abstract: Long-form legal research reports increasingly rely on LLMs and agentic research systems, but their reliability depends not only on answering the task, b

Logical Regression for Planning with Axioms

arXiv:2607.21414v1 Announce Type: new Abstract: In automated planning, logical regression is an operation that returns the most general condition necessary for an action to achieve a particular formul

Tutorials

M^3-Gen: Interpretable Multimodal Generation of Gene Expression Profiles Using Clinical and Imaging Data

arXiv:2607.21343v1 Announce Type: cross Abstract: Integrating heterogeneous biomedical data, including clinical metadata, histopathology images, and molecular profiles, is crucial for comprehensive di

tutorialsarxiv-cs-ai

ODeform: Learning Continuous 4D Motion for Shape Deformation with Neural ODEs

arXiv:2607.20670v1 Announce Type: new Abstract: Modeling continuous object deformation is important for many computer vision and robotics tasks, such as manipulation and simulation. Existing approache

ProCap: Prominence-guided Object Rectification for Faithful and Comprehensive Video Captioning

arXiv:2607.21022v1 Announce Type: new Abstract: Improving video captioning quality typically demands retraining large vision-language models, an expensive and often impractical requirement. Existing t

Refusal-Gated Decoding: Preserving Refusal Behavior Under High-Temperature Sampling

arXiv:2607.20791v1 Announce Type: new Abstract: High-temperature sampling is one of the primary mechanisms for increasing diversity in LLMs. Recent advances in truncation-based sampling techniques hav

Riemannian Deep Learning: Modules, Networks, and Geometries

arXiv:2607.19305v2 Announce Type: replace-cross Abstract: Deep neural networks on manifold-valued representations have attracted growing interest, but many basic components remain tied to specific man

Simple Policy Gradients for Reasoning with Diffusion Language Models

arXiv:2510.04019v3 Announce Type: replace-cross Abstract: Diffusion large language models (dLLMs) represent a promising alternative to autoregressive LLMs; however, the lack of effective post-training

safetyarxiv-cs-ai

Sparse Concept Channels in Frozen 3D CT Vision Encoders

arXiv:2607.20993v1 Announce Type: cross Abstract: Large vision-language models are becoming increasingly dominant in 3D medical image interpretation, but we rarely know which internal units encode cli