Search: “applications”

A Lightweight Self-Supervised Learning Framework for Multivariate Time Series using Hierarchical-JEPA on ECG Data

arXiv:2607.01145v1 Announce Type: new Abstract: Data analysis in the medical domain often encounters scenarios involving a limited target dataset and a large, unannotated dataset with a general distri

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Agents

A Task-State Representation for Long-Horizon Mobile GUI Agents

DGX agent

arXiv:2607.00502v1 Announce Type: new Abstract: While long-horizon mobile GUI agents typically rely on thought-action-observation loops, they struggle to separate persistent task states from transient

agentsarxiv-cs-cl

2 Jul 2026

Hardware

Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling

arXiv:2607.00773v1 Announce Type: new Abstract: Discrete diffusion models are widely used for learning and generating discrete distributions. As the generation process is inherently sequential, the ac

hardwarearxiv-cs-lg

Tutorials

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration

arXiv:2607.01029v1 Announce Type: new Abstract: Collaborative capture of dynamic targets is common in nature as an essential strategy for weaker species against the strong. Similar concepts have shown

tutorialsarxiv-cs-ro

Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization

arXiv:2607.01080v1 Announce Type: new Abstract: We investigate Gaussian process (GP) bandit optimization with quantum kernels, assuming the mean reward function lies in the reproducing kernel Hilbert

Beyond Pixel Overlap: A Framework for Decomposing Segmentation Evaluation Metrics

arXiv:2607.00886v1 Announce Type: new Abstract: Evaluation metrics are central to binary target segmentation because they determine how progress is measured, compared, and interpreted. In this paper,

Beyond the Prompt: Jailbreaking Function-Calling LLMs via Simulated Moderation Traces

arXiv:2607.00481v1 Announce Type: cross Abstract: Jailbreak attacks remain a critical threat to the safe deployment of large language models (LLMs). While prior work has primarily studied attacks and

Coachable agents for interactive gameplay

arXiv:2607.00642v1 Announce Type: new Abstract: Reinforcement learning has proven to be a valuable tool in the creation of advanced AI and robotic systems, contributing to everything from game playing

agentsarxiv-cs-ai

Tutorials

CORGI: Consistency-Aware 3D Dog Reconstruction from a Single Image in the Wild

arXiv:2607.00321v1 Announce Type: new Abstract: Reconstructing high-fidelity 3D models of highly articulated animals, such as dogs, from a single in-the-wild image remains a formidable challenge. In t

tutorialsarxiv-cs-cv

CPDDNet: Color-Polarization Denoising and Demosaicking Network

arXiv:2607.01100v1 Announce Type: new Abstract: Color-polarization imaging using a color-polarization filter array (CPFA) sensor captures both texture (color intensity) and physical (polarization) inf

Deep Multitask Learning for Mixed-Type Outcomes with Shared Sparsity

arXiv:2607.00995v1 Announce Type: cross Abstract: Most existing multitask learning approaches are limited by their reliance on task-specific loss functions tailored to the scale and type of each outco

Tutorials

Detecting the Undetectable: Enhancing Unsupervised time series Anomaly Detection via Active Learning

arXiv:2607.00720v1 Announce Type: cross Abstract: Despite the increasing sophistication of industrial AI systems, the ability to reliably detect subtle and noisy anomalies in complex time series data

tutorialsarxiv-cs-ai

DeWorldSG: Depth-Aware 3D Semantic Scene Graph Generation via World-Model Priors

arXiv:2607.00889v1 Announce Type: cross Abstract: We present DeWorldSG, a novel framework that generates spatio-temporally robust 3D Semantic Scene Graphs from RGB-D sequences. Existing methods often

Distributionally Robust Linear Regression With Block Lewis Weights

arXiv:2607.00252v1 Announce Type: new Abstract: We present an algorithm for the group distributionally robust (GDR) least squares problem. Given m groups, a parameter vector in R^d, and stacked design

E-TIDE: Fast, Structure-Preserving Motion Forecasting from Event Sequences

arXiv:2603.27757v2 Announce Type: replace Abstract: Event-based cameras capture visual information as asynchronous streams of per-pixel brightness changes, generating sparse, temporally precise data.

Flow-Through Tensors: A Unified Computational Graph Architecture for Multi-Layer Transportation Network Optimization

arXiv:2507.02961v2 Announce Type: replace-cross Abstract: Modern transportation network modeling increasingly involves the integration of diverse methodologies including sensor-based forecasting, rein

FSA: An Alternative Efficient Implementation of Native Sparse Attention Kernel

arXiv:2508.18224v3 Announce Type: replace-cross Abstract: Recent advances in sparse attention mechanisms have demonstrated strong potential for reducing the computational cost of long-context training

GAIA: Geometry-Adaptive Operator Learning for Forward and Inverse Problems

arXiv:2607.01128v1 Announce Type: new Abstract: Operator learning for partial differential equations (PDEs) on arbitrary geometries builds fast neural surrogates for large-scale simulation. Although r

GKDT: General Keypoint Detection Transformer

arXiv:2607.00752v1 Announce Type: new Abstract: With the emergence of various pre-trained vision and language models, computer vision is shifting from narrow-domain to open-domain recognition. The con

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination

arXiv:2607.00924v1 Announce Type: new Abstract: Accelerating materials discovery requires AI systems that can generate scientifically valid hypotheses through multi-step, domain-grounded reasoning. St

HieDG: A Hierarchical Discrete Geometry-Guided Framework for Multi-Animal Tracking

arXiv:2607.00494v1 Announce Type: new Abstract: Multi-animal tracking (MAT) is critical for wildlife monitoring and behavioral analysis, yet remains challenging due to uniform appearance, high density

Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility

arXiv:2607.00228v1 Announce Type: cross Abstract: Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions

LLVM-Bench: Benchmarking and Advancing Large Language Models for LLVM Compiler Issue Resolution

arXiv:2607.00700v1 Announce Type: cross Abstract: LLVM is a widely used compiler infrastructure whose scale and complexity make issue resolution labor-intensive and challenging. Although large languag

Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs

arXiv:2602.05275v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various

Manifold-constrained Hamilton-Jacobi Reachability Learning for Decentralized Multi-Agent Motion Planning

arXiv:2511.03591v2 Announce Type: replace Abstract: Safe multi-agent motion planning (MAMP) under task-induced constraints is a critical challenge in robotics. Many real-world scenarios require robots

safetyarxiv-cs-ro

Memory-Native Non-Terrestrial Networks for Embodied Intelligence

arXiv:2607.00029v1 Announce Type: cross Abstract: Non-terrestrial networks (NTN) provide ubiquitous connectivity for embodied intelligence (EI), enabling robots in wilderness to leverage cloud resourc

MemSyco-Bench: Benchmarking Sycophancy in Agent Memory

arXiv:2607.01071v1 Announce Type: cross Abstract: Memory has emerged as a cornerstone of modern LLM-based agents, supporting their evolution from single-turn assistants to long-term collaborators. How

NeHMO: Neural Hamilton-Jacobi Reachability Learning for Decentralized Safe Multi-Arm Motion Planning

arXiv:2607.00326v1 Announce Type: new Abstract: Safe multi-arm motion planning is a challenging problem in robotics due to its high dimensionality, coupled configuration space, and complex collision c

safetyarxiv-cs-ro

NeuroFilter: Activation-Based Guardrails for Privacy-Conscious LLM Agents

arXiv:2601.14660v2 Announce Type: replace-cross Abstract: Agentic Large Language Models (LLMs) are models able to reason, plan, and execute tools over unstructured data. These abilities are enabling t

agentsarxiv-cs-ai

OSCAR: Occupancy-based Shape Completion via Acoustic Neural Implicit Representations

arXiv:2603.08279v2 Announce Type: replace Abstract: Accurate 3D reconstruction of vertebral anatomy from ultrasound is important for guiding minimally invasive spine interventions, but it remains chal

Local Ai

Personalized Object Identification and Localization via In-Context Inference with Vision-Language Models

arXiv:2607.00357v1 Announce Type: new Abstract: Personalized object localization (POL) localizes an object instance in a query image based on a few reference images with bounding-box annotations and a

local-aiarxiv-cs-cv

PorTEXTO: A European Portuguese Benchmark for Visual Text Extraction

arXiv:2606.19096v2 Announce Type: replace Abstract: European Portuguese (pt-PT) is largely absent from OCR benchmarks, which skew toward high-resource languages. The few benchmarks that cover pt-PT fo

Real-Time Hard Negative Sampling via LLM-based Clustering for Large-Scale Two-Tower Retrieval

arXiv:2607.00448v1 Announce Type: cross Abstract: The two-tower model has been widely used for large-scale recommendation systems, particularly in the retrieval stage. Industry standards for training

SemiScope: Disentangling Classifier Tuning and Joint Optimization in Semi-Supervised Security Classification

arXiv:2607.00113v1 Announce Type: new Abstract: Background. Labeled data for security classification is scarce. Semi-supervised learning (SSL) propagates labels from a small labeled pool to larger unl

TCMA: Text-Conditioned Multi-granularity Alignment for Drone Cross-Modal Text-Video Retrieval

arXiv:2510.10180v2 Announce Type: replace Abstract: Unmanned aerial vehicles (UAVs) have become powerful platforms for real-time, high-resolution data collection, producing massive volumes of aerial v

TerraBench: Can Agents Reason Over Heterogeneous Earth-System Data?

arXiv:2606.13148v2 Announce Type: replace Abstract: Climate and environmental decision-making increasingly requires reasoning across heterogeneous inputs, including gridded physical data, satellite im

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming

arXiv:2606.18293v2 Announce Type: replace-cross Abstract: Thanks to rapid developments in generative AI, we are in the midst of a paradigm shift that may change how we interact with computers forever.

Which Metric Reflects the Spelling Rate Accuracy in Event-Related Potential-Based Brain-Computer Interfaces?

arXiv:2607.00794v1 Announce Type: new Abstract: For predictive models, the often-reported performance metrics are the loss and accuracy. In synchronous Brain- Computer Interface (BCI) systems, these m

Zero-Shot Distracted Driver Detection via Vision Language Models with Double Decoupling

arXiv:2601.08467v2 Announce Type: replace Abstract: Distracted driving is a major cause of traffic collisions, calling for robust and scalable detection methods. Vision-language models (VLMs) enable s

safetyarxiv-cs-cv

A Three-Phase Foundation Model for Tax-Aware Personalized Portfolio Management

arXiv:2606.30997v1 Announce Type: new Abstract: We present a three-phase deep reinforcement learning system for personalized portfolio management that addresses three limitations shared by all prior f

Accelerated Likelihood Maximization for Diffusion-based Versatile Content Generation

arXiv:2606.31323v1 Announce Type: new Abstract: Generating diverse, coherent, and plausible content from partially given inputs remains a fundamental challenge for diffusion models. Existing approache

Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback

arXiv:2606.30923v1 Announce Type: cross Abstract: Imitation Learning is a natural framework for learning in sequential decision-making systems and has emerged as the dominant paradigm through which we

Breaking Failure Cascades: Step-Aware Reinforcement Learning for Medical Multimodal Reasoning

arXiv:2606.31825v1 Announce Type: cross Abstract: Recent multimodal large language models have shown great promise in clinical image reasoning, but existing post-training pipelines remain predominantl

Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning

arXiv:2502.00684v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has successfully addressed many complex control problems. However, the neural networks representing policies

agentsarxiv-cs-ai

Conditional Tropical Cyclogenesis Rates via Rare-Event Sampling in a Neural Weather Emulator

arXiv:2606.30920v1 Announce Type: cross Abstract: We couple Forward Flux Sampling (FFS), a non-equilibrium rare-event technique from statistical mechanics, to a neural weather emulator (SDL-WXFormer,

DigitalCoach: Communication and Grounding Gaps in Human and Agentic Computer Use Coaching

arXiv:2606.31980v1 Announce Type: new Abstract: Agents are increasingly capable of automating software tasks, but can they teach humans how to use software themselves? We introduce DigitalCoach, a mul

agentsarxiv-cs-cl

Dualformer: Efficient Feature Extractor for Complex-valued Blind Communication Signal Analysis

arXiv:2606.31352v1 Announce Type: new Abstract: Designing effective feature extractors is critical for blind signal analysis tasks such as automatic modulation recognition (AMR), signal scheme recogni

Dynamic Prediction of Alternating Recurrent Events via Neural Network

arXiv:2606.30889v1 Announce Type: cross Abstract: Alternating recurrent events -- event-times of a specific nature that trigger a secondary refractory period -- occur in a wide-range of fields, includ