Search: “models”

Are Current Continual Learning Methods Truly Agnostic? Introducing OPRE, a Step Toward Agnostic Continual Learning

arXiv:2511.08226v2 Announce Type: replace-cross Abstract: In order to achieve Continual Learning (CL), the problem of catastrophic forgetting, one that has plagued neural networks since their inceptio

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Attention-Based Segmentation of WMHs and Differentiation of Vascular vs. Demyelinating Lesions

DGX agent

arXiv:2607.08171v1 Announce Type: new Abstract: White Matter Hyperintensities (WMHs) are commonly observed in brain Magnetic Resonance Imaging (MRI) scans. They are associated with various neurologica

researcharxiv-cs-cv

10 Jul 2026

CAAD: Causality-Aware Multivariate Time Series Anomaly Detection via Multi-Scale Alignment and Structural Causal Consistency

arXiv:2607.08555v1 Announce Type: new Abstract: The operational integrity of complex industrial systems relies on precise anomaly detection and diagnosis. The vast majority of existing methods narrowl

safetyarxiv-cs-lg

Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents

arXiv:2306.02704v2 Announce Type: replace-cross Abstract: We introduce Calibrated Stackelberg Games (CSGs), a generalization of the standard Stackelberg Games (SGs) framework. In CSGs, a principal rep

agentsarxiv-cs-lg

CoCo-Fed: A Unified Framework for Memory- and Communication-Efficient Federated Learning at the Wireless Edge

arXiv:2601.00549v2 Announce Type: replace-cross Abstract: The deployment of large-scale neural networks within the Open Radio Access Network (O-RAN) architecture is pivotal for enabling native edge in

local-aiarxiv-cs-ai

ConRad: Efficient Conformal Prediction for Radiomics

arXiv:2607.08084v1 Announce Type: cross Abstract: Radiomic features derived from medical images and segmentation masks are used to support decision making in clinical imaging pipelines. In practice, t

Hardware

CTA-Pipelining: A Latency-Oriented Spatial Scaling Method for Multi-GPU Systems

arXiv:2607.07862v1 Announce Type: cross Abstract: The evolution of compute infrastructure has transformed multi-GPU systems into tightly integrated shared-memory structures. However, current software

hardwarearxiv-cs-lg

Applications

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation

arXiv:2607.07767v1 Announce Type: cross Abstract: Missing values undermine statistical inference and machine learning pipelines, yet most imputation methods rely on heuristics or restrictive parametri

applicationsarxiv-cs-lg

DKDNet: Dual Knowledge and Data-Driven Network for Cross-Domain Automatic Modulation Classification

arXiv:2607.08031v1 Announce Type: cross Abstract: The dynamics of communication environments induce significant distribution shifts across domains, challenging the generalization of deep learning-base

Effective Gaussian Management for High-fidelity Scene Reconstruction

arXiv:2509.12742v4 Announce Type: replace Abstract: This paper proposes an effective Gaussian management framework for high-fidelity scene reconstruction of both appearance and geometry. Unlike recent

Hardware

EVIS: A Physics-Grounded Event Camera Plugin for NVIDIA Isaac Sim

arXiv:2607.08098v1 Announce Type: new Abstract: Event cameras offer microsecond temporal resolution, low latency, and high dynamic range, making them attractive for robotics. However, labeled event-ca

hardwarearxiv-cs-cv

Explaining Near-Zero Hessian Eigenvalues Through Approximate Symmetries in Neural Networks

arXiv:2607.07845v1 Announce Type: new Abstract: The Hessian of the training loss governs the local geometry of the loss landscape, yet despite existing explanations for its largest eigenvalues, the or

Expressivity and Statistical Trade-offs in Diffusion Policy Learning

arXiv:2607.07967v1 Announce Type: cross Abstract: Diffusion-based policies have recently emerged as powerful policy parameterizations for reinforcement learning, representing state-conditioned action

safetyarxiv-cs-lg

FPGN: Redefining Ultra-Fast Programmable Gate-based Neural Acceleration with Differentiable LUTs

arXiv:2607.08427v1 Announce Type: cross Abstract: Achieving nanosecond-scale inference latency for deep neural networks (DNNs) has become a primary architectural concern for latency-critical applicati

GenDA: Generative Data Assimilation on Complex Urban Areas via Classifier-Free Diffusion Guidance

arXiv:2601.11440v3 Announce Type: replace-cross Abstract: Urban wind flow reconstruction is essential for assessing air quality, heat dispersion, and pedestrian comfort, yet remains challenging when o

GitLake: Git-for-data for the agentic lakehouse

arXiv:2607.08319v1 Announce Type: cross Abstract: We present GitLake, a Git-for-data design for an agent-first lakehouse. The system lifts single-table Iceberg snapshots into lakehouse-wide commits, b

agentsarxiv-cs-ai

GRE-Diff: Gaussian Room Embeddings for Structured Layout Diffusion

arXiv:2607.08086v1 Announce Type: new Abstract: Designing functional and aesthetically coherent floor plans requires exploring a vast space of possible room arrangements, a task that quickly becomes o

HeaPA: Difficulty-Aware Heap Sampling and On-Policy Query Augmentation for LLM Reinforcement Learning

arXiv:2601.22448v2 Announce Type: replace-cross Abstract: RLVR has become a standard recipe for training LLMs on reasoning tasks with verifiable outcomes, but when rollout generation dominates the cos

safetyarxiv-cs-cl

Input-Constrained Spatiotemporal Tubes for Safe Navigation of Unknown Euler-Lagrange Systems in Dynamic Environments

arXiv:2607.08189v1 Announce Type: cross Abstract: Safe navigation in dynamic environments is challenging when system dynamics are unknown and actuator inputs are limited. Existing methods either rely

researcharxiv-cs-ro

Kime-Representation Formulations of Three Open Problems in the Foundations of Classical Mechanics: Uncertainty, Invariant Entropy, and Directional Degrees of Freedom

arXiv:2607.07851v1 Announce Type: cross Abstract: We give mathematically self-contained formulations, in the complex-time (kime) representation, of three open problems from the foundations of classica

Knowledge Graph and Accurate Portrait Construction of Scientific and Technological Academic Conferences

arXiv:2204.04888v2 Announce Type: replace-cross Abstract: In recent years, with the continuous progress of science and technology, the number of scientific research achievements has increased rapidly.

LDFE: Laplacian Decoupled Feature Enhancement Block for Dual-Stream CNN-based RGB-IR Object Detection

arXiv:2607.08076v1 Announce Type: cross Abstract: The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions. Existing meth

local-aiarxiv-cs-ai

LESV: Language Embedded Sparse Voxel Fusion for Open-Vocabulary 3D Scene Understanding

arXiv:2604.01388v2 Announce Type: replace Abstract: Recent advancements in open-vocabulary 3D scene understanding heavily rely on 3D Gaussian Splatting (3DGS) to register vision-language features into

safetyarxiv-cs-cv

Tutorials

LOGOS: Language-guided Oriented Object Detection in Aerial Scenes

arXiv:2607.08004v1 Announce Type: new Abstract: Object detection in geospatial scenes, such as satellite and aerial imagery, poses significant challenges due to the varying orientations and densities

tutorialsarxiv-cs-cv

Applications

MobiDiff: Semantic-Aware Multi-Channel Discrete Diffusion for Human Mobility Data Generation

arXiv:2607.08357v1 Announce Type: new Abstract: Human mobility data are essential for transportation optimization, urban planning, and resource allocation, yet real-world mobility data are costly to c

applicationsarxiv-cs-ai

Open-ended Multi-agent Autocurricula via Visual Inspection of Policies with Multi-modal LLMs

arXiv:2607.08193v1 Announce Type: cross Abstract: Open-ended curricula in Reinforcement Learning (RL) aim to train generally-capable agents by identifying tasks that facilitate learning increasingly c

Tutorials

Optimal Learning Rate Scaling Depends on Data in Deep Scalar Linear Networks

arXiv:2607.07884v1 Announce Type: new Abstract: In this short note we consider the gradient descent dynamics of deep scalar linear networks, f(x) = prod_{l=1}^L w_l x, which enjoy exact time-course so

tutorialsarxiv-cs-lg

Tutorials

Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions

arXiv:2603.02204v2 Announce Type: replace Abstract: Selective conformal prediction can yield substantially tighter uncertainty sets when we can identify calibration examples that are exchangeable with

tutorialsarxiv-cs-lg

PGD-NO: A Neural Operator with Precomputed Geometry Decomposition for 3D Million-scale Physics Simulations

arXiv:2607.08025v1 Announce Type: new Abstract: While neural PDE solvers have demonstrated significant potential for accelerating engineering simulations, existing architectures remain constrained by

Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs

arXiv:2310.07895v2 Announce Type: replace Abstract: This paper presents a method to efficiently classify the gastroenterologic section of images derived from Video Capsule Endoscopy (VCE) studies by e

Prediction-Powered Active Testing

arXiv:2607.08347v1 Announce Type: cross Abstract: Active testing provides a label--efficient approach to risk estimation by adaptively selecting which test points should be labelled. However, existing

Prismata: Confining Cross-Site Prompt Injection in Web Agents

arXiv:2607.08147v1 Announce Type: cross Abstract: Autonomous web agents promise to automate everyday browsing tasks, but inherit one of the web's oldest attack surfaces. Cross-Site Scripting proved th

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification

arXiv:2607.08162v1 Announce Type: cross Abstract: Whole slide images (WSIs) provide rich diagnostic information for computational pathology, but their gigapixel scale, stain variation, scanner differe

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization

arXiv:2607.08045v1 Announce Type: cross Abstract: Angular radio maps describe the received-power distribution over the angle of arrival and underpin beam selection and receiver localization in sixth-g

SAM-MT: Real-Time Interactive Multi-Target Video Segmentation

arXiv:2607.08688v1 Announce Type: new Abstract: Modern Video Object Segmentation (VOS) involves tracking and segmenting user-specified targets. While recent approaches have achieved remarkable perform

SASGeo: Stability-Aware Semantic Map Localization for GNSS-Denied UAVs -- A Framework and Synthetic Proof of Concept

arXiv:2607.07737v1 Announce Type: cross Abstract: GNSS-denied unmanned aerial vehicles require occasional absolute position fixes to bound the drift of visual-inertial odometry. Cross-view image retri

safetyarxiv-cs-cv

Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles

arXiv:2607.08373v1 Announce Type: cross Abstract: Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from norm

agentsarxiv-cs-ai

Sign Identifiability of Causal Effects in Stationary Stochastic Dynamical Systems

arXiv:2603.08311v2 Announce Type: replace-cross Abstract: We study identifiability in continuous-time linear stationary stochastic differential equations with a known causal structure. Unlike existing

Simulator Ensembles for Trustworthy Autonomous Driving Systems Testing

arXiv:2503.08936v3 Announce Type: replace-cross Abstract: Scenario-based testing with driving simulators is extensively used to identify failing conditions of automated driving assistance systems (ADA

agentsarxiv-cs-ai

Applications

SkelGen4D: Weakly-Supervised Skeleton-Based 4D Generation for Text-Driven Mesh Animation

arXiv:2607.08246v1 Announce Type: new Abstract: We study 4D generation to synthesize temporally coherent sequences of 3D geometry for animation and content creation. In contrast to existing SDS-based

applicationsarxiv-cs-cv

Statistical inverse learning problems with random observations

arXiv:2312.15341v1 Announce Type: cross Abstract: We provide an overview of recent progress in statistical inverse problems with random experimental design, covering both linear and nonlinear inverse

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures

arXiv:2607.08511v1 Announce Type: cross Abstract: Choosing a learning rate scheduling strategy is critical to neural network training, but manual selection is costly and rarely exhaustive. While class

TriphiBot: A Triphibious Robot Combining FOC-based Propulsion with Eccentric Design

arXiv:2602.01385v2 Announce Type: replace Abstract: Triphibious robots capable of multi-domain motion and cross-domain transitions are promising to handle complex tasks across diverse environments. Ho

researcharxiv-cs-ro

VocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval

arXiv:2607.08541v1 Announce Type: cross Abstract: Open-vocabulary object detection and segmentation aim to recognize arbitrary objects beyond predefined categories. Although recent vision-language and

Wat3R: Underwater 3D Geometry Learning without Annotations

arXiv:2607.08772v1 Announce Type: new Abstract: Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-

Whareformer: Learning to Track What is Where in Long Egocentric Videos

arXiv:2607.08537v1 Announce Type: new Abstract: The recently established 'Out of Sight, Not out of Mind' (OSNOM) task for egocentric videos focuses on tracking objects that are moved by the camera wea

When Debiasing Backfires: Counterintuitive Side Effects of Preprocessing-Based Stereotype Mitigation

arXiv:2607.07937v1 Announce Type: new Abstract: Preprocessing-based methods for stereotype mitigation, such as pre-/post-training on debiased corpora, are widely used in NLP. While these approaches re

researcharxiv-cs-cl

When Synthetic Speech Is All You Have: Better Call GRPO

arXiv:2607.08409v1 Announce Type: cross Abstract: LLM-based ASR adapted to regulated domains such as banking is bottlenecked by privacy: real speech is costly and legally constrained to collect, makin