Search: “applications”

Privacy-Preserving and Verifiable Approximate Distributed Coded Computing

arXiv:2607.02187v1 Announce Type: new Abstract: Distributed machine learning enables collaborative model training without centralizing data, but it also exposes learning processes to privacy leakage a

3 Jul 2026

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VisionAId: An Offline-First Multimodal Android Assistant for People with Visual Impairment, Featuring Personalized Object Retrieval

DGX agent

arXiv:2607.02371v1 Announce Type: cross Abstract: Over 285 million people worldwide live with a visual impairment, for whom everyday tasks such as avoiding obstacles, locating personal belongings, rec

model-releasesarxiv-cs-ai

3 Jul 2026

Dataset Biases and Shortcut Learning in Motion-Based AI-Generated Video Detection

arXiv:2607.00948v1 Announce Type: new Abstract: The visual quality of AI-generated videos has improved drastically in recent years, making it increasingly difficult for humans to distinguish between r

safetyarxiv-cs-cv

2 Jul 2026

Optimization on the Oblique Manifold for Sparse Simplex Constraints via Multiplicative Updates

arXiv:2503.24075v4 Announce Type: replace-cross Abstract: Low-rank optimization problems with sparse simplex constraints involve variables that must satisfy nonnegativity, sparsity, and sum-to-1 condi

2 Jul 2026

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook

arXiv:2607.00839v1 Announce Type: new Abstract: Multi-label image classification (MLIC), a fundamental task in computer vision, focuses on identifying multiple objects or concepts within an image, und

agentsarxiv-cs-cv

2 Jul 2026

Building an ASR Solution for Training and Assessing Children's Reading

model-releasesarxiv-cs-cl

arXiv:2606.31508v1 Announce Type: new Abstract: Automatic speech recognition for children's reading remains underdeveloped for most African languages, including Bambara, despite its potential value fo

Tutorials

CoDex: Learning Compositional Dexterous Functional Manipulation without Demonstrations

arXiv:2606.31909v1 Announce Type: new Abstract: In this work, we study Compositional Dexterous Functional Object Manipulation (CD-FOM): tasks such as aiming and actuating a spray bottle on a plant or

tutorialsarxiv-cs-ro

Deep Reinforcement Learning for Spacecraft Attitude Control During Atmospheric Re-Entry

arXiv:2606.31291v1 Announce Type: new Abstract: Deep reinforcement learning has the potential to solve attitude control problems more adaptively, precisely, and robustly by handling nonlinear dynamics

Temporal Training Strategies for Left Atrium and Left Atrial Appendage Segmentation in Dynamic Contrast 4DCT

arXiv:2606.31444v1 Announce Type: new Abstract: Dynamic contrast-enhanced cardiac CT enables time-resolved analysis of contrast filling and washout in the left atrium (LA) and left atrial appendage (L

Generalization error of min-norm interpolators in transfer learning

arXiv:2406.13944v2 Announce Type: replace-cross Abstract: This paper establishes the generalization error of pooled min-ell_2-norm interpolation in transfer learning, where data from diverse distribut

GPC: Large-Scale Generative Pretraining for Transferable Motor Control

arXiv:2606.29148v1 Announce Type: cross Abstract: Developing controllers capable of completing a wide range of tasks in a natural and life-like manner is a key challenge in enabling practical applicat

safetyarxiv-cs-ai

In-Vehicle Digital Twin-Based Collision Warning Framework with Sybil Attack Detection

arXiv:2606.28625v1 Announce Type: cross Abstract: Connected Vehicles (CVs) rely extensively on communication technologies to enable data-driven predictive analyses for enhancing performance and safety

Kriging and neural network models for pressure losses across perforated plates

arXiv:2606.29628v1 Announce Type: cross Abstract: In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates

MARS: A neurosymbolic approach for interpretable drug discovery

arXiv:2410.05289v4 Announce Type: replace Abstract: Background: Neurosymbolic (NeSy) artificial intelligence describes the combination of logic or rule-based techniques with neural networks. Compared

safetyarxiv-cs-ai

AI-Model Network: Concept, Current State and Future

arXiv:2606.27382v1 Announce Type: new Abstract: While the primary function of computers lies in computation and processing, the core value of the Internet is rooted in sharing and collaboration. Compu

29 Jun 2026

Local Ai

Long-Term Prediction of Local and Global Human Motion with Occlusion Recovery

arXiv:2606.27900v1 Announce Type: new Abstract: Human motion describes the three-dimensional full-body movement of a person. Anticipating such motion holds significant relevance across a wide range of

local-aiarxiv-cs-cv

29 Jun 2026

Local Ai

AnySimLite: A Lightweight Few-Shot Similarity Encoder for On-Device Speech-Adjacent Classification

arXiv:2606.26452v1 Announce Type: new Abstract: To minimize privacy concerns and inference latency on edge devices like smartphones, lightweight on-device models remain important for end-user applicat

local-aiarxiv-cs-cl

26 Jun 2026

Context-Aware Synthesis of Optimization Pipelines for Warehouse Optimization

arXiv:2606.26852v1 Announce Type: new Abstract: Order fulfillment in manual picker-to-goods warehouses involves interconnected decisions such as item assignment, order batching, and picker routing. Wh

26 Jun 2026

AIChilles: Automatically Uncovering Hidden Weaknesses in AI-Evolved Systems

arXiv:2606.15834v2 Announce Type: replace Abstract: The computer systems community has recently seen growing interest in AI-driven system evolution, where AI agents iteratively rewrite systems. Framew

Energy-Efficient CNN Acceleration with MSDF Digit-Serial Arithmetic on FPGA

arXiv:2606.25562v1 Announce Type: cross Abstract: This paper presents an energy-efficient hardware acceleration of the convolutional layers in the U-Net architecture for image segmentation, implemente

Reasonable Motion: A General ASP Foundation for Environment Constrained Movement Trajectory Computation

model-releasesarxiv-cs-ro

arXiv:2606.25626v1 Announce Type: cross Abstract: We present a general answer set programming based hybrid quantitative-qualitative method for computing constrained branching trajectory modes for movi

Surrogate models for Rock-Fluid Interaction: A Grid-Size-Invariant Approach

arXiv:2602.22188v2 Announce Type: replace Abstract: Modelling rock-fluid interaction requires solving a set of partial differential equations (PDEs) to predict the flow behaviour and the reactions of

A Fast and Effective Method for Euclidean Anticlustering: The Assignment-Based-Anticlustering Algorithm

arXiv:2601.06351v2 Announce Type: replace Abstract: Anticlustering is an NP-hard combinatorial optimization problem that consists of partitioning a set of objects into equal-sized groups called anticl

24 Jun 2026

Managing Task Execution for Unknown Workloads in Batteryless IoT: A Hardware-Agnostic Evaluation

arXiv:2606.24340v1 Announce Type: new Abstract: In recent years, the Internet of Things (IoT) paradigm has been shifting toward batteryless, energy-harvesting architectures. Sustaining reliable operat

agentsarxiv-cs-lg

24 Jun 2026

Token-to-Token Alignment of Text Embeddings for Semantic Blending

arXiv:2606.24021v1 Announce Type: new Abstract: In modern generative models, images are specified and controlled through text prompts. In practice, images are generated from sequences of tokens derive

safetyarxiv-cs-cv

24 Jun 2026

Tutorials

A large-scale foundation model enables simulation-to-real adaptation for nuclear magnetic resonance-based molecular structure analysis

arXiv:2606.20756v1 Announce Type: cross Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful tool for molecular structure analysis, and spectral artificial intelligence offers great p

tutorialsarxiv-cs-lg

Boundary-by-Mask: Few-Shot Instance Segmentation with Mask-Conditioned Boundary Learning for Texture-Poor Industrial Parts

arXiv:2606.21594v1 Announce Type: new Abstract: Recent advances in large pre-trained models have led to remarkable progress in instance segmentation on general images. However, industrial scenarios re

CFAgentBench: A Reproducible Environment and Benchmark for Autonomous Construction-Finance Agents

model-releasesarxiv-cs-lg

arXiv:2606.22000v1 Announce Type: cross Abstract: We introduce CFAgentBench, a reproducible, self-hostable environment and benchmark for autonomous construction-finance agents: a CFO/controller-class

Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations

arXiv:2406.07884v2 Announce Type: replace-cross Abstract: Using partial knowledge of a quantum state to control multiqubit entanglement is a largely unexplored paradigm in the emerging field of quantu

agentsarxiv-cs-lg

Scalable Maximum Entropy Reinforcement Learning for Diffusion Policies via Adjoint Matching

arXiv:2606.22630v1 Announce Type: new Abstract: Diffusion policies have recently emerged as a powerful paradigm for representing complex action distributions in reinforcement learning (RL). However, t

The Unreasonable Effectiveness of VLMs for Zero-shot Procedural Mistake Detection

arXiv:2606.21579v1 Announce Type: new Abstract: Procedural mistake detection is important for quality control and user assistance across many disciplines. Recent work in this field has achieved signif

TROPT: An Open Framework for Unifying and Advancing Discrete Text Optimization

arXiv:2606.23496v1 Announce Type: new Abstract: Discrete text-trigger optimization -- searching for text sequences that, when ingested by a model, steer it toward a specified objective -- underpins mo

A Lightweight Multi-Agent Framework for Automated Concrete Barrier Design

arXiv:2606.12040v1 Announce Type: new Abstract: The design of reinforced concrete highway barriers is a safety-critical process that requires strict compliance with regulatory provisions such as the A

Local Ai

Non-frontal face recognition using GANs and memristor-based classifiers

arXiv:2606.12074v1 Announce Type: cross Abstract: Face recognition systems have advanced significantly through deep learning techniques, delivering high performance and robustness in complex scenarios

local-aiarxiv-cs-ai

Open Materials Generation with Inference-Time Reinforcement Learning

arXiv:2602.00424v2 Announce Type: replace Abstract: Continuous-time generative models for crystalline materials enable inverse materials design by learning to predict stable crystal structures, but in

SpikeDecoder: Realizing the GPT Architecture with Spiking Neural Networks

arXiv:2606.12287v1 Announce Type: cross Abstract: The Transformer architecture is widely regarded as the most powerful tool for natural language processing, but due to a high number of complex operati

Tabular Foundation Models for Clinical Survival Analysis via Survival-Aware Adaptation

arXiv:2606.12006v1 Announce Type: cross Abstract: Predicting time-to-event outcomes such as mortality is a fundamental task in clinical decision-making, commonly addressed through survival analysis. W

Towards Deep Learning Surrogate for the Forward Problem in Electrocardiology: A Scalable Alternative to Physics-Based Models

arXiv:2512.13765v2 Announce Type: replace-cross Abstract: The forward problem in electrocardiology, computing body surface potentials from cardiac electrical activity, is traditionally solved using ph

A Survey on Semantic Modeling for Building Energy Management

arXiv:2404.11716v2 Announce Type: replace Abstract: Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the building sector. Although IoT technologies now provide e

agentsarxiv-cs-ai

Belief Acquisition as Stochastic Filtering

arXiv:2206.02178v3 Announce Type: replace Abstract: This paper studies how belief acquisition can be accomplished using stochastic filtering. First, a theoretical foundation for empirical beliefs is o

Beyond Explaining Predictions: Logic-Based Explanations for Confidence in Machine Learning Models

arXiv:2606.10347v1 Announce Type: new Abstract: Machine learning is increasingly used in critical domains, where both predictions and their associated confidence levels influence important decisions.

Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation

arXiv:2606.09923v1 Announce Type: cross Abstract: Neural operators such as the Fourier Neural Operator (FNO) have emerged as powerful surrogates for solving partial differential equations (PDEs), achi

safetyarxiv-cs-ai

Contrastive Spectral Rectification: Test-Time Defense towards Zero-shot Adversarial Robustness of CLIP

arXiv:2601.19210v2 Announce Type: replace Abstract: Vision-language models (VLMs) such as CLIP have demonstrated remarkable zero-shot generalization, yet remain highly vulnerable to adversarial exampl

safetyarxiv-cs-cv

EEVEE: Towards Test-time Prompt Learning in the Real World for Self-Improving Agents

arXiv:2606.11182v1 Announce Type: cross Abstract: In this paper, we propose EEVEE, the first multi-dataset test-time prompt learning framework for LLM agents, enabling test-time prompt learning under

An Interval Branch-and-Bound-Based Inverse Kinemetics Algorithm Towards Global Optimal Redundancy Resolution

arXiv:2104.12183v2 Announce Type: replace Abstract: The general inverse kinematics (IK) problem of a manipulator, namely that of acquiring the self-motion manifold (SMM) of all admissible joint angles

researcharxiv-cs-ro

Conditional Normalizing Flows for Forward and Backward Joint State and Parameter Estimation

model-releasesarxiv-cs-lg

arXiv:2601.07013v2 Announce Type: replace-cross Abstract: Traditional filtering algorithms for state estimation -- such as classical Kalman filtering, unscented Kalman filtering, and particle filters

Cryptographic Backdoor for Neural Networks: Boon and Bane

arXiv:2509.20714v2 Announce Type: replace-cross Abstract: In this paper we show that cryptographic backdoors in a neural network (NN) can be highly effective in two directions, namely mounting the att

Facial Expression Recognition in the Deep Learning Era: A Systematic Multi-Criteria Review of Methods, Models, Datasets, Performance, Challenges, and Future Research Directions

arXiv:2606.08612v1 Announce Type: new Abstract: Facial Expression Recognition (FER) has advanced rapidly over the last decade, driven by the shift from handcrafted descriptors and shallow classifiers