Search: “applications”

How well behaved is finite dimensional Diffusion Maps?

arXiv:2412.03992v3 Announce Type: replace-cross Abstract: Under a set of assumptions on a family of submanifolds subset {mathbb R}^D, we derive a series of geometric properties that remain valid after

Agents

LiWi: Layering in the Wild

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arXiv:2605.14552v1 Announce Type: new Abstract: Recent advances in generative models have empowered impressive layered image generation, yet their success is largely confined to graphic design domains

agentsarxiv-cs-cv

15 May 2026

Tutorials

Local Spatiotemporal Convolutional Network for Robust Gait Recognition

arXiv:2605.14548v1 Announce Type: new Abstract: Gait recognition, as a promising biometric technology, identifies individuals through their unique walking patterns and offers distinctive advantages in

tutorialsarxiv-cs-cv

MD-PNOP: Equation-Recast Neural Operators for Minimal-Data Extrapolation and PDE Solver Acceleration

arXiv:2509.01416v2 Announce Type: replace Abstract: The computational overhead of traditional numerical solvers for partial differential equations (PDEs) remains a critical bottleneck for large-scale

Med-DisSeg: Dispersion-Driven Representation Learning for Fine-Grained Medical Image Segmentation

arXiv:2605.14579v1 Announce Type: new Abstract: Accurate medical image segmentation is fundamental to precision medicine, yet robust delineation remains challenging under heterogeneous appearances, am

researcharxiv-cs-cv

MetaBackdoor: Exploiting Positional Encoding as a Backdoor Attack Surface in LLMs

arXiv:2605.15172v1 Announce Type: cross Abstract: Backdoor attacks pose a serious security threat to large language models (LLMs), which are increasingly deployed as general-purpose assistants in safe

safetyarxiv-cs-cl

MicroscopyMatching: Towards a Ready-to-use Framework for Microscopy Image Analysis in Diverse Conditions

arXiv:2605.14980v1 Announce Type: cross Abstract: Analyzing microscopy images to extract biological object properties (e.g., their morphological organization, temporal dynamics, and population density

Mixed Integer Goal Programming for Personalized Meal Optimization with User-Defined Serving Granularity

arXiv:2605.13849v1 Announce Type: new Abstract: Determining what to eat to satisfy nutritional requirements is one of the oldest optimization problems in operations research, yet existing formulations

Monitoring Data-aware Temporal Properties (Extended Version)

arXiv:2605.14666v1 Announce Type: new Abstract: Dynamic systems in AI are often complex and heterogeneous, so that an internal specification is not accessible and verification techniques such as model

Multimodal Causal-Driven Representation Learning for Generalizable Medical Image Segmentation

arXiv:2508.05008v2 Announce Type: replace Abstract: Vision-Language Models (VLMs), such as CLIP, have demonstrated remarkable zero-shot capabilities in various computer vision tasks. However, their ap

researcharxiv-cs-cv

OmniDrop: Layer-wise Token Pruning for Omni-modal LLMs via Query-Guidance

arXiv:2605.14458v1 Announce Type: new Abstract: Omni-modal large language models have demonstrated remarkable potential in holistic multimodal understanding; however, the token explosion caused by hig

Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients

arXiv:2605.14297v1 Announce Type: cross Abstract: We study reinforcement learning in hybrid discrete-continuous action spaces, such as settings where the discrete component selects a regime (or index)

Probing into Camera Control of Video Models

model-releasesarxiv-cs-cv

arXiv:2605.14815v1 Announce Type: new Abstract: Video is a rich and scalable source of 3D/4D visual observations, and camera control is a key capability for video generation models to produce geometri

QOuLiPo: What a quantum computer sees when it reads a book

model-releasesarxiv-cs-cl

arXiv:2605.14188v1 Announce Type: cross Abstract: What does a book look like to a quantum computer? This paper takes eight classical works of the Renaissance and its late-antique inheritance -- from A

R2PS: Worst-Case Robust Real-Time Pursuit Strategies under Partial Observability

arXiv:2511.17367v2 Announce Type: replace Abstract: Computing worst-case robust strategies in pursuit-evasion games (PEGs) is time-consuming, especially when real-world factors like partial observabil

safetyarxiv-cs-lg

Agents

Remember Your Trace: Memory-Guided Long-Horizon Agentic Framework for Consistent and Hierarchical Repository-Level Code Documentation

arXiv:2605.14563v1 Announce Type: cross Abstract: Automated code documentation is essential for modern software development, providing the contextual grounding that both human developers and coding ag

agentsarxiv-cs-cl

Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons

arXiv:2603.02115v2 Announce Type: replace-cross Abstract: General-purpose robot reward models are typically trained to predict absolute task progress from expert demonstrations, providing only local,

local-aiarxiv-cs-ai

Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image

arXiv:2605.14984v1 Announce Type: cross Abstract: Generating a street-level 3D scene from a single satellite image is a crucial yet challenging task. Current methods present a stark trade-off: geometr

Second-Order Actor-Critic Methods for Discounted MDPs via Policy Hessian Decomposition

arXiv:2605.14982v1 Announce Type: cross Abstract: We address the discounted reward setting in reinforcement learning (RL). To mitigate the value approximation challenges in policy gradient methods, ac

Seed3D 2.0: Advancing High-Fidelity Simulation-Ready 3D Content Generation

arXiv:2605.13862v1 Announce Type: cross Abstract: We present Seed3D 2.0, an advanced 3D content generation system built on Seed3D 1.0, with substantial improvements across generation fidelity, simulat

local-aiarxiv-cs-cv

Semantic Feature Segmentation for Interpretable Predictive Maintenance in Complex Systems

arXiv:2605.14318v1 Announce Type: new Abstract: Predictive maintenance in complex systems is often complicated by the heterogeneity and redundancy of monitored variables,which can obscure fault-releva

Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations

arXiv:2605.14937v1 Announce Type: cross Abstract: Predictive world models enable agents to model scene dynamics and reason about the consequences of their actions. Inspired by human perception, object

SOCC-ICP: Semantics-Assisted Odometry based on Occupancy Grids and ICP

arXiv:2605.15074v1 Announce Type: new Abstract: Reliable pose estimation in previously unseen environments is a fundamental capability of autonomous systems. Existing LiDAR odometry methods typically

safetyarxiv-cs-ro

Streaming Speech-to-Text Translation with a SpeechLLM

arXiv:2605.14766v1 Announce Type: cross Abstract: Normally, a system that translates speech into text consists of separate modules for speech recognition and text-to-text translation. Combining those

Synthesizing POMDP Policies: Sampling Meets Model-checking via Learning

arXiv:2605.14440v1 Announce Type: new Abstract: Partially Observable Markov Decision Processes (POMDPs) are the standard framework for decision-making under uncertainty. While sampling-based methods s

Synthetic American Option Pricing via Jump-HMM-Driven Heston Implied Volatility

arXiv:2605.13998v1 Announce Type: cross Abstract: Generating realistic synthetic option prices requires implied volatility as an input, yet implied volatility is itself derived from observed option pr

TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models

arXiv:2602.04657v3 Announce Type: replace Abstract: Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most ex

local-aiarxiv-cs-cv

Unsteady Metrics and Benchmarking Cultures of AI Model Builders

arXiv:2605.14164v1 Announce Type: new Abstract: The primary way to establish and compare competencies in foundation and generative AI models has shifted from peer-reviewed literature to press releases

VGGT-Edit: Feed-forward Native 3D Scene Editing with Residual Field Prediction

arXiv:2605.15186v1 Announce Type: cross Abstract: High-quality 3D scene reconstruction has recently advanced toward generalizable feed-forward architectures, enabling the generation of complex environ

VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing

arXiv:2602.07045v2 Announce Type: replace-cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have enabled complex reasoning. However, existing remote sensing (RS) benchmar

A3 : an Analytical Low-Rank Approximation Framework for Attention

arXiv:2505.12942v4 Announce Type: replace-cross Abstract: Large language models have demonstrated remarkable performance; however, their massive parameter counts make deployment highly expensive. Low-

Achieving epsilon^{-2} Sample Complexity for Single-Loop Actor-Critic under Minimal Assumptions

arXiv:2605.13639v1 Announce Type: new Abstract: In this paper, we establish last-iterate convergence rates for off-policy actor--critic methods in reinforcement learning. In particular, under a single

safetyarxiv-cs-lg

Adaptive Conformal Prediction for Reliable and Explainable Medical Image Classification

arXiv:2605.12917v1 Announce Type: new Abstract: Deep learning models for medical imaging often exhibit overconfidence, creating safety risks in ambiguous diagnostic scenarios. While Conformal Predicti

safetyarxiv-cs-cv

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results

arXiv:2502.15761v3 Announce Type: replace-cross Abstract: The deployment of large language models (LLMs) on extended reality (XR) devices has great potential to advance the field of human-AI interacti

local-aiarxiv-cs-ai

Amortized Neural Clustering of Time Series based on Statistical Features

arXiv:2605.13128v1 Announce Type: cross Abstract: This paper introduces an algorithm-agnostic approach to feature-based time series clustering via amortized neural inference. By training neural networ

Bounded-Input True Proportional Navigation for Impact-Time Control

arXiv:2605.13669v1 Announce Type: cross Abstract: This paper proposes a nonlinear guidance strategy capable of intercepting a constant-velocity, non-maneuvering target while strictly satisfying the pr

researcharxiv-cs-ro

Context-Aware Web Attack Detection in Open-Source SIEM Systems via MITRE ATT&CK-Enriched Behavioral Profiling

arXiv:2605.13337v1 Announce Type: cross Abstract: Security Information and Event Management (SIEM) systems aggregate log data from heterogeneous sources to detect coordinated attacks. Traditional rule

CRePE: Curved Ray Expectation Positional Encoding for Unified-Camera-Controlled Video Generation

arXiv:2605.12938v1 Announce Type: cross Abstract: Camera-conditioned video generation requires positional encoding that remains reliable under changes in camera motion, lens configuration, and scene s

Design of Magnetic Continuum Robots with Tunable Force Response Using Rotational Ring Pairs

arXiv:2605.13613v1 Announce Type: new Abstract: In this paper, we discuss a novel continuum robot design that enables the online tuning of the magnetic response at its tip. The proposed method allows

researcharxiv-cs-ro

DistractMIA: Black-Box Membership Inference on Vision-Language Models via Semantic Distraction

arXiv:2605.12574v1 Announce Type: cross Abstract: Vision-language models (VLMs) are trained on large-scale image-text corpora that may contain private, copyrighted, or otherwise sensitive data, motiva

Distributionally Robust Safety Under Arbitrary Uncertainties: A Safety Filtering Approach

arXiv:2605.12974v1 Announce Type: new Abstract: In this work, we study how to ensure probabilistic safety for nonlinear systems under distributional ambiguity. Our approach builds on a backup-based sa

safetyarxiv-cs-ro

Does language matter for spoken word classification? A multilingual generative meta-learning approach

arXiv:2605.13084v1 Announce Type: cross Abstract: Meta-learning has been shown to have better performance than supervised learning for few-shot monolingual spoken word classification. However, the met

DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning

arXiv:2605.13418v1 Announce Type: new Abstract: Differentially private optimization suffers from a fundamental geometric mismatch: deep networks have highly anisotropic loss landscapes, yet DP-SGD inj

Embodied Neurocomputation: A Framework for Interfacing Biological Neural Cultures with Scaled Task-Driven Validation

arXiv:2605.13315v1 Announce Type: cross Abstract: Biological neural networks (BNNs) have been established as a powerful and adaptive substrate that offer the potential for incredibly energy and data e

EVA-Bench: A New End-to-end Framework for Evaluating Voice Agents

arXiv:2605.13841v1 Announce Type: cross Abstract: Voice agents, artificial intelligence systems that conduct spoken conversations to complete tasks, are increasingly deployed across enterprise applica

Exact Sequence Interpolation with Transformers

arXiv:2502.02270v3 Announce Type: replace Abstract: We prove that transformers can exactly interpolate datasets of finite input sequences in R^d, dgeq 2, with corresponding output sequences of smaller

Few-Shot Physics-Informed Neural Network for Shape Reconstruction of Concentric-Tube Robots

model-releasesarxiv-cs-ro

arXiv:2605.12790v1 Announce Type: new Abstract: Modeling concentric tube robots (CTRs) involves complex nonlinear continuum mechanics, and despite recent progress, physics-based models often lack an a

Flow Matching for Offline Reinforcement Learning with Discrete Actions

arXiv:2602.06138v2 Announce Type: replace Abstract: Generative policies based on diffusion models and flow matching have shown strong promise for offline reinforcement learning (RL), but their applica

safetyarxiv-cs-lg