Search: “applications”

T-STAR: A Large-Scale Benchmark for Spatio-Temporal Panoptic Scene Graph Generation in Satellite Video

arXiv:2607.21228v1 Announce Type: new Abstract: Structured understanding of satellite video is essential for advancing dynamic geospatial scene analysis from low-level perception to high-level cogniti

24 Jul 2026

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Research

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings

DGX agent

arXiv:2607.11007v2 Announce Type: replace Abstract: Few-shot multimodal classification commonly attaches a lightweight head, such as k-nearest neighbors, logistic regression, or a linear SVM, to a fro

researcharxiv-cs-lg

24 Jul 2026

TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics

model-releasesarxiv-cs-ai

arXiv:2602.19313v2 Announce Type: replace-cross Abstract: General-purpose robot learning requires dense, instruction-conditioned feedback that can distinguish meaningful task progress from stalled, fa

24 Jul 2026

Transformer-based Diffusion models for Hydrological Time Series Probabilistic Imputation and Forecasting

arXiv:2607.21200v1 Announce Type: cross Abstract: The modeling of hydrometeorological time series with limited observations is a key challenge in the monitoring of hydro-systems and water resources, a

24 Jul 2026

A Unified Variational Framework for Deep Weakly Supervised Image Segmentation

arXiv:2607.19669v1 Announce Type: new Abstract: We propose a unified variational framework for image segmentation under sparse pixel-level supervision. Our method is based on a simplex-constrained Pot

Agents

Agent-Centric Animal Pose Forecasting

arXiv:2607.19548v1 Announce Type: new Abstract: Understanding animal behavior at an algorithmic level -- what animals attend to, how they form internal models and plans, and how this maps to action --

agentsarxiv-cs-lg

AuditVotes: Elevating Provable Defense for GNNs with Efficient Augmentation and Conditional Smoothing

arXiv:2503.22998v3 Announce Type: replace-cross Abstract: Despite advancements in Graph Neural Networks (GNNs), adaptive attacks continue to challenge their robustness. Certified robustness via random

Breaking the T^{3/4} Barrier for Regret Minimization With Bi-Dimensional CDFs

arXiv:2607.20258v1 Announce Type: new Abstract: We study regret minimization for learning CDF-related objectives of the form [ g(x)dotP_{XsimD}(Xle x), ] over [0,1]^2, where g is a known Lipschitz fun

CGCE: Classifier-Guided Concept Erasure in Generative Models

arXiv:2511.05865v3 Announce Type: replace-cross Abstract: Recent advancements in large-scale generative models have enabled the creation of high-quality images and videos, but have also raised signifi

CreatiPoster: Towards Editable and Controllable Multi-Layer Graphic Design Generation

arXiv:2506.10890v2 Announce Type: replace Abstract: Graphic design plays a crucial role in both commercial and personal contexts, yet creating high-quality, editable, and aesthetically pleasing graphi

Defense Against LLM Backdoors using Critical Neuron Isolation Pruning

model-releasesarxiv-cs-ai

arXiv:2607.19894v1 Announce Type: cross Abstract: Large language models (LLMs) are vulnerable to backdoor attacks, where hidden triggers induce malicious outputs. Existing defenses generally fall into

EGRNet: A Lightweight Semantic Segmentation Network with Edge-Gated Refinement and Adversarial Sensing

arXiv:2607.19617v1 Announce Type: new Abstract: As autonomous systems and smart cities continue to evolve, the demand for efficient and robust scene understanding becomes increasingly critical. Semant

safetyarxiv-cs-cv

emb-diversity: A Tool for Embedding-Based Measurement of Data Diversity

arXiv:2607.19848v1 Announce Type: new Abstract: There is growing evidence that data diversity is crucial for developing fair and robust NLP models. However, current approaches to measure diversity rem

researcharxiv-cs-cl

Generative AI-enhanced Probabilistic Multi-Fidelity Surrogate Modeling Via Transfer Learning

model-releasesarxiv-cs-lg

arXiv:2602.00072v2 Announce Type: replace Abstract: The performance of machine learning surrogates is critically dependent on data quality and quantity. This presents a major challenge, as high-fideli

Hardware

InstantSfM: Towards GPU-Native SfM for the Deep Learning Era

arXiv:2510.13310v3 Announce Type: replace Abstract: Structure-from-Motion (SfM) is a fundamental technique for recovering camera poses and scene structure from multi-view imagery, serving as a critica

hardwarearxiv-cs-cv

Learning About Learning: A Path from Spin Glasses to Artificial Intelligence

arXiv:2601.07635v3 Announce Type: replace-cross Abstract: The Hopfield model, originally inspired by spin glasses, occupies a central place at the intersection of statistical mechanics, neural network

Learning Encoding-Decoding Direction Pairs to Unveil Concepts of Influence in Deep Vision Networks

arXiv:2509.23926v4 Announce Type: replace Abstract: Empirical evidence shows that deep vision networks often represent concepts as directions in latent space with concept information written along dir

safetyarxiv-cs-cv

Learning Personalized Safety Interventions for Haptic Human-Robot Shared Control

arXiv:2607.19534v1 Announce Type: new Abstract: Haptic feedback provides an implicit channel for communicating safety intentions during human-robot shared control. Existing haptic guidance systems typ

safetyarxiv-cs-ro

Local Ai

Lipschitzian SLLNs for random functions

arXiv:2607.20411v1 Announce Type: cross Abstract: We prove strong laws of large numbers for locally Lipschitz functions in the Lipschitz pseudometric. Our results hold under either a topological or a

local-aiarxiv-cs-lg

Membership Inference Attacks for Unseen Classes

arXiv:2506.06488v3 Announce Type: replace Abstract: A key tool in developing safe AI models is data auditing, i.e., using statistical tools to determine whether harmful content may have been used in t

safetyarxiv-cs-lg

Morphing MILR: Design and control of a cable-driven limbless robot with rolling joints for maneuvering in complex environments

arXiv:2607.19714v1 Announce Type: new Abstract: Limbless robots offer exceptional mobility in confined and cluttered environments due to their slender bodies and their ability to exploit body-terrain

researcharxiv-cs-ro

On Optimization Complexity of Second-Order Certified Unlearning

arXiv:2607.20192v1 Announce Type: new Abstract: We study machine unlearning: the removal of memorized training data from a trained model. Specifically, we investigate the algorithmic complexity of cer

One4Many-StablePacker: An Efficient Deep Reinforcement Learning Framework for the 3D Bin Packing Problem

arXiv:2510.10057v2 Announce Type: replace Abstract: The three-dimensional bin packing problem (3D-BPP) is widely applied in logistics and warehousing. Existing learning-based approaches often neglect

safetyarxiv-cs-lg

Open-Vocabulary Gaze Object Prediction: Benchmark and Method

arXiv:2607.18827v1 Announce Type: new Abstract: Gaze Object Prediction (GOP) aims to localize and recognize the objects humans attend to, a task crucial for understanding human-centric interactions. H

Hardware

Optimal Recalibration of an Online Predictor

arXiv:2607.19689v1 Announce Type: cross Abstract: We study the problem of recalibrating an online predictor [KE17, OKS24]: given an arbitrary 'hint' sequence of forecasts, the learner must output new

hardwarearxiv-cs-lg

OSVE: One Step Video Editing with One Step Diffusion Models

arXiv:2607.19895v1 Announce Type: cross Abstract: Text-guided video editing with diffusion models is impractically slow, hindered by costly multi-step sampling and inversion. We present OSVE, the firs

PG-KINN: A Physics-Informed Petrov-Galerkin Kolmogorov-Arnold Network for Solving Forward and Inverse PDEs

model-releasesarxiv-cs-lg

arXiv:2607.20378v1 Announce Type: new Abstract: Physics-informed learning of partial differential equations (PDEs) has been dominated by multilayer perceptrons (MLPs), whose spectral bias and dense pa

Pointing-Based Object Recognition

arXiv:2603.15403v2 Announce Type: replace Abstract: This paper presents a comprehensive pipeline for recognizing objects targeted by human pointing gestures using RGB images. As human-robot interactio

Refnd: Preventing Data Leakage in Relational Datasets

arXiv:2607.19376v1 Announce Type: cross Abstract: Machine learning models trained on biochemical data are routinely evaluated using splits that fail to account for relational structure, causing inform

Scale-Aware Learning of Chaotic Dynamics on Unstructured Meshes via Binned Spectral Losses

arXiv:2607.19387v1 Announce Type: cross Abstract: Surrogate modeling for high-dimensional nonlinear dynamical systems that exhibit chaos requires mechanisms that preserve not only pointwise accuracy b

Seeing Before Generating: Object Perception Enhances Single-View 3D Reconstruction

arXiv:2607.18630v1 Announce Type: new Abstract: The relationship between object perception and reconstruction is well established in human vision, yet remains underexplored in computer vision. In this

Signed Rectified Flow: Negativity-Controlled Generation

arXiv:2607.18516v1 Announce Type: cross Abstract: We introduce Signed Rectified Flow (Signed RF), a generalization of Rectified Flow that targets the signed measure pi^{sign} = (1+alpha)pi^+ - alphapi

Sound Probabilistic Safety Bounds for Large Language Models

arXiv:2607.20286v1 Announce Type: cross Abstract: We propose a novel framework for computing rigorous bounds on the probability that a large language model (LLM) generates harmful output to a given pr

StreamHOI: Interaction-aware Temporal Memory Adaptation for Streaming HOI Video Generation

arXiv:2607.20174v1 Announce Type: cross Abstract: Existing human--object interaction (HOI) video generation methods are largely limited to offline short-video generation with complex driving condition

StrokeSeg2: Stroke Lesion Segmentation in Clinical Research Workflows

arXiv:2607.19901v1 Announce Type: new Abstract: Deep learning frameworks like nnU-Net achieve state-of-theart brain lesion segmentation performance but remain difficult to deploy in clinical research

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review

arXiv:2507.10142v2 Announce Type: replace Abstract: Multi-Agent Reinforcement Learning (MARL) has achieved strong performance in simulated benchmarks, yet real deployments often violate the assumption

Trustworthy Privacy-Preserving Multimodal Federated Learning for Personalised Breast Cancer Prediction

arXiv:2607.19532v1 Announce Type: cross Abstract: Federated learning has emerged as a potential solution to privacy concerns associated with using sensitive health data for training predictive models,

A Space-Time Transformer for Precipitation Nowcasting

arXiv:2511.11090v3 Announce Type: replace Abstract: Until recently, numerical weather prediction (NWP) models have stood rivalless in operational forecasting despite a few limitations. Namely, physica

A VAE-Driven Multi-Task Satellite-Aided Semantic Communication Framework for 6G-Enabled Connected Autonomous Vehicles

arXiv:2607.13494v1 Announce Type: new Abstract: The development of smart transportation systems and the introduction of 6G wireless communication technologies have significantly changed vehicle networ

safetyarxiv-cs-lg

Hardware

Adaptive Conformal Inference through the Lens of Blackwell Approachability

arXiv:2510.15824v2 Announce Type: replace-cross Abstract: This article considers an online version of conformal inference, called adaptive conformal inference [ACI] and introduced by Gibbs and Candes

hardwarearxiv-cs-lg

Adversarial Prompting Framework for AI Safety Assessment

arXiv:2607.13453v1 Announce Type: cross Abstract: Artificial Intelligence (AI), especially Generative AI (GenAI), adoption has increased in industries significantly in recent years. However, the use o

Classifying daily activities needs posture, reconstructing them needs motion

arXiv:2607.13216v1 Announce Type: cross Abstract: Humans recognize movements effortlessly, even from noisy and complex visual input. But what information in the stimulus allows humans to rapidly class

DarwinLM: Evolutionary Structured Pruning of Large Language Models

model-releasesarxiv-cs-lg

arXiv:2502.07780v4 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved significant success across various NLP tasks. However, their massive computational costs limit their wide

Design, Modeling and Experimental Validation of a Miniature Hybrid Underwater Glider With Large-Range Foldable Deflectable Wings

model-releasesarxiv-cs-ro

arXiv:2607.13622v1 Announce Type: new Abstract: Miniature hybrid underwater gliders have attracted increasing attention for long-endurance ocean observation and confined-space inspection. Large-range

Designing Safety-Constrained LLM Systems for Public Health Information Access

arXiv:2607.13038v1 Announce Type: cross Abstract: We present the design and implementation of a safety constrained large language model (LLM) system for public health information access, focusing on m

Local Ai

Differentiable Polarized Path Tracing

arXiv:2607.13265v1 Announce Type: new Abstract: Physically based differentiable rendering has proven to be a powerful tool for inverse rendering problems (e.g., 3D reconstruction, reflectance estimati

local-aiarxiv-cs-cv

Tutorials

IMMNet: Hybrid Fusion of Model-based and Data-driven Approaches for Maneuvering Target Tracking

arXiv:2607.13573v1 Announce Type: cross Abstract: Maneuvering target tracking in three-dimensional space remains a challenging problem due to complex motion dynamics and model mismatch. To address thi

tutorialsarxiv-cs-ai

Introducing Human-Centeredness in AI-Assisted Lexicography

arXiv:2607.11808v2 Announce Type: replace-cross Abstract: This paper proposes a human-centered artificial intelligence (HCAI) framework for AI-assisted lexicography. While generative AI offers signifi