Search: “papers”

Finite-dimensional approximations of push-forwards on locally analytic functionals

arXiv:2404.10769v4 Announce Type: replace-cross Abstract: This paper develops a functional-analytic framework for approximating the push-forward induced by an analytic map from finitely many samples.

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Geometry-Guided Self-Supervision for Ultra-Fine-Grained Recognition with Limited Data

DGX agent

arXiv:2604.19345v1 Announce Type: new Abstract: This paper investigates the intrinsic geometrical features of highly similar objects and introduces a general self-supervised framework called the Geome

researcharxiv-cs-cv

22 Apr 2026

Hybrid Task and Motion Planning with Reactive Collision Handling for Multi-Robot Disassembly of Complex Products: Application to EV Batteries

arXiv:2509.21020v2 Announce Type: replace Abstract: This paper addresses the problem of multi-robot coordination for complex manipulation task sequences. We present a vision-driven task-and-motion pla

safetyarxiv-cs-ro

Applications

Joint Magnetometer-IMU Calibration via Maximum A Posteriori Estimation

arXiv:2505.16662v4 Announce Type: replace Abstract: This paper presents a new method for jointly calibrating a magnetometer and inertial measurement unit (IMU), focusing on balancing calibration accur

applicationsarxiv-cs-ro

LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results

model-releasesarxiv-cs-cv

arXiv:2604.19445v1 Announce Type: new Abstract: This paper presents a review for the LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aimed to advance research on real-world a

Mind the Unseen Mass: Unmasking LLM Hallucinations via Soft-Hybrid Alphabet Estimation

arXiv:2604.19162v1 Announce Type: new Abstract: This paper studies uncertainty quantification for large language models (LLMs) under black-box access, where only a small number of responses can be sam

researcharxiv-cs-cl

MoonSeg3R: Monocular Online Zero-Shot Segment Anything in 3D with Reconstructive Foundation Priors

arXiv:2512.15577v2 Announce Type: replace Abstract: In this paper, we focus on online zero-shot monocular 3D instance segmentation, a novel practical setting where existing approaches fail to perform

Nonmonotone subgradient methods based on a local descent lemma

arXiv:2510.19341v2 Announce Type: replace-cross Abstract: In this paper we present a nonmonotone line search subgradient algorithm tailored to upper-C^2 functions. This is a family of nonsmooth and no

On Solving the Multiple Variable Gapped Longest Common Subsequence Problem

arXiv:2604.18645v1 Announce Type: new Abstract: This paper addresses the Variable Gapped Longest Common Subsequence (VGLCS) problem, a generalization of the classical LCS problem involving flexible ga

researcharxiv-cs-ai

Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels

arXiv:2506.18186v3 Announce Type: replace Abstract: The restless multi-armed bandit (RMAB) framework is a popular approach to solving resource allocation problems in networked systems. In this paper,

Agents

PanDA: Unsupervised Domain Adaptation for Multimodal 3D Panoptic Segmentation in Autonomous Driving

arXiv:2604.19379v1 Announce Type: new Abstract: This paper presents the first study on Unsupervised Domain Adaptation (UDA) for multimodal 3D panoptic segmentation (mm-3DPS), aiming to improve general

agentsarxiv-cs-cv

Applications

Seeing Candidates at Scale: Multimodal LLMs for Visual Political Communication on Instagram

arXiv:2604.19489v1 Announce Type: new Abstract: This paper presents a computational case study that evaluates the capabilities of specialized machine learning models and emerging multimodal large lang

applicationsarxiv-cs-cv

Syntax as a Rosetta Stone: Universal Dependencies for In-Context Coptic Translation

arXiv:2604.18758v1 Announce Type: new Abstract: Low-resource machine translation requires methods that differ from those used for high-resource languages. This paper proposes a novel in-context learni

researcharxiv-cs-cl

Unifying Controller Design for Stabilizing Nonlinear Systems with Norm-Bounded Control Inputs

arXiv:2403.03030v2 Announce Type: replace-cross Abstract: This paper revisits a classical challenge in the design of stabilizing controllers for nonlinear systems with a norm-bounded input constraint.

researcharxiv-cs-ai

VecHeart: Holistic Four-Chamber Cardiac Anatomy Modeling via Hybrid VecSets

model-releasesarxiv-cs-cv

arXiv:2604.19403v1 Announce Type: new Abstract: Accurate cardiac anatomy modeling requires the model to be able to handle intricate interrelations among structures. In this paper, we propose VecHeart,

VideoAgent: Personalized Synthesis of Scientific Videos

model-releasesarxiv-cs-ai

arXiv:2509.11253v2 Announce Type: replace Abstract: The technical complexity of research papers often limits their reach, necessitating more accessible formats like scientific videos to disseminate ke

Virtual boundary integral neural network for three-dimensional exterior acoustic problems

arXiv:2604.18636v1 Announce Type: cross Abstract: This paper presents a virtual boundary integral neural network (VBINN) for exterior acoustic problems in three dimensions. The method introduces a vir

A High-Accuracy Optical Music Recognition Method Based on Bottleneck Residual Convolutions

arXiv:2604.16446v1 Announce Type: new Abstract: Optical Music Recognition (OMR) aims to convert printed or handwritten music score images into editable symbolic representations. This paper presents an

safetyarxiv-cs-cv

A novel LSTM music generator based on the fractional time-frequency feature extraction

arXiv:2604.17823v1 Announce Type: cross Abstract: In this paper, we propose a novel approach for generating music based on an artificial intelligence (AI) system. We analyze the features of music and

researcharxiv-cs-cl

A Quasi-Experimental Developer Study of Security Training in LLM-Assisted Web Application Development

arXiv:2604.17763v1 Announce Type: cross Abstract: This paper presents a controlled quasi-experimental developer study examining whether a layer-based security training package is associated with impro

Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark

model-releasesarxiv-cs-cv

arXiv:2604.16984v1 Announce Type: new Abstract: This paper presents the report of the URVIS 2026 challenge on adverse-to-extreme panoptic segmentation. As the first challenge of its kind, it attracted

Agentic Risk-Aware Set-Based Engineering Design

model-releasesarxiv-cs-lg

arXiv:2604.16687v1 Announce Type: cross Abstract: This paper introduces a multi-agent framework guided by Large Language Models (LLMs) to assist in the early stages of engineering design, a phase ofte

ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioning

arXiv:2603.29068v3 Announce Type: replace Abstract: This paper presents ARCS (Autoregressive Circuit Synthesis), a system for amortized analog circuit generation. ARCS produces complete, SPICE-simulat

Barrier-enforced multi-objective optimization for direct point and sharp interval forecasting

arXiv:2604.18492v1 Announce Type: new Abstract: This paper proposes a multi-step probabilistic forecasting framework using a single neural-network based model to generate simultaneous point and interv

CAARL: In-Context Learning for Interpretable Co-Evolving Time Series Forecasting

arXiv:2604.18305v1 Announce Type: new Abstract: In this paper we investigate forecasting coevolving time series that feature intricate dependencies and nonstationary dynamics by using an LLM Large Lan

tutorialsarxiv-cs-lg

Central Limit Theorems for Asynchronous Averaged Q-Learning

arXiv:2509.18964v3 Announce Type: replace Abstract: This paper establishes central limit theorems for Polyak-Ruppert averaged Q-learning under asynchronous updates. We prove a non-asymptotic central l

Detecting Alarming Student Verbal Responses using Text and Audio Classifier

arXiv:2604.16717v1 Announce Type: new Abstract: This paper addresses a critical safety gap in the use Automated Verbal Response Scoring (AVRS). We present a novel hybrid framework for troubled student

safetyarxiv-cs-cl

Distributional Off-Policy Evaluation with Deep Quantile Process Regression

arXiv:2604.18143v1 Announce Type: cross Abstract: This paper investigates the off-policy evaluation (OPE) problem from a distributional perspective. Rather than focusing solely on the expectation of t

Does Welsh media need a review? Detecting bias in Nation.Cymru's political reporting

arXiv:2604.17628v1 Announce Type: new Abstract: Wales' political landscape has been marked by growing accusations of bias in Welsh media. This paper takes the first computational step toward testing t

safetyarxiv-cs-cl

Efficient Federated RLHF via Zeroth-Order Policy Optimization

arXiv:2604.17747v1 Announce Type: new Abstract: This paper considers reinforcement learning from human feedback in a federated learning setting with resource-constrained agents, such as edge devices.

FairNVT: Improving Fairness via Noise Injection in Vision Transformers

arXiv:2604.16780v1 Announce Type: new Abstract: This paper presents FairNVT, a lightweight debiasing framework for pretrained transformer-based encoders that improves both representation and predictio

safetyarxiv-cs-cv

Fast Online 3D Multi-Camera Multi-Object Tracking and Pose Estimation

arXiv:2604.16522v1 Announce Type: new Abstract: This paper proposes a fast and online method for jointly performing 3D multi-object tracking and pose estimation using multiple monocular cameras. Our a

FLiP: Towards understanding and interpreting multimodal multilingual sentence embeddings

model-releasesarxiv-cs-cl

arXiv:2604.18109v1 Announce Type: new Abstract: This paper presents factorized linear projection (FLiP) models for understanding pretrained sentence embedding spaces. We train FLiP models to recover t

FlowC2S: Flowing from Current to Succeeding Frames for Fast and Memory-Efficient Video Continuation

arXiv:2604.17625v1 Announce Type: new Abstract: This paper introduces a novel methodology for generating fast and memory-efficient video continuations. Our method, dubbed FlowC2S, fine-tunes a pre-tra

tutorialsarxiv-cs-cv

Frequency-Decomposed INR for NIR-Assisted Low-Light RGB Image Denoising

arXiv:2604.16800v1 Announce Type: new Abstract: Addressing the issues of severe noise and high frequency structural degradation in visible images under low-light conditions, this paper proposes a Near

tutorialsarxiv-cs-cv

Fuzzy Encoding-Decoding to Improve Spiking Q-Learning Performance in Autonomous Driving

model-releasesarxiv-cs-lg

arXiv:2604.16436v1 Announce Type: cross Abstract: This paper develops an end-to-end fuzzy encoder-decoder architecture for enhancing vision-based multi-modal deep spiking Q-networks in autonomous driv

Graph neural network for colliding particles with an application to sea ice floe modeling

arXiv:2602.16213v2 Announce Type: replace-cross Abstract: This paper introduces a novel approach to sea ice modeling using Graph Neural Networks (GNNs), utilizing the natural graph structure of sea ic

tutorialsarxiv-cs-cv

Applications

How Non-Linguistic Is the Indus Sign System? A Synthetic-Baseline Scorecard

arXiv:2604.17828v1 Announce Type: new Abstract: Whether the Indus Valley sign system (c. 2600-1900 BCE) encodes spoken language has been debated for decades. This paper introduces a multi-metric discr

applicationsarxiv-cs-cl

Hybrid Spectro-Temporal Fusion Framework for Structural Health Monitoring

arXiv:2604.16589v1 Announce Type: new Abstract: Structural health monitoring plays a critical role in ensuring structural safety by analyzing vibration responses from engineering systems. This paper p

Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users

model-releasesarxiv-cs-cl

arXiv:2603.16120v2 Announce Type: replace Abstract: Deep Research (DR) systems help researchers cope with ballooning publishing counts. Such tools synthesize scientific papers to answer research queri

Leveraging Kernel Symmetry for Joint Compression and Error Mitigation in Edge Model Transfer

arXiv:2604.17371v1 Announce Type: cross Abstract: This paper investigates communication-efficient neural network transmission by exploiting structured symmetry constraints in convolutional kernels. In

LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding

arXiv:2501.05067v3 Announce Type: replace Abstract: In this paper, we introduce LLaVA-Octopus, a novel video multimodal large language model. LLaVA-Octopus adaptively weights features from different v

ltzGLUE: Luxembourgish General Language Understanding Evaluation

model-releasesarxiv-cs-cl

arXiv:2604.17976v1 Announce Type: new Abstract: This paper presents ltzGLUE, the first Natural Language Understanding (NLU) benchmark for Luxembourgish (LTZ) based on the popular GLUE benchmark for En

Agents

Memory Centric Power Allocation for Multi-Agent Embodied Question Answering

arXiv:2604.17810v1 Announce Type: new Abstract: This paper considers multi-agent embodied question answering (MA-EQA), which aims to query robot teams on what they have seen over a long horizon. In co

agentsarxiv-cs-ro

Method for Aggregating Unstructured Data Using Large Language Models

model-releasesarxiv-cs-lg

arXiv:2604.16425v1 Announce Type: cross Abstract: This paper presents a method for the automated collection and aggregation of unstructured data from diverse web sources, utilizing Large Language Mode

Mix and Match: Context Pairing for Scalable Topic-Controlled Educational Summarisation

arXiv:2604.18087v1 Announce Type: new Abstract: Topic-controlled summarisation enables users to generate summaries focused on specific aspects of source documents. This paper investigates a data augme

safetyarxiv-cs-cl

MLE-UVAD: Minimal Latent Entropy Autoencoder for Fully Unsupervised Video Anomaly Detection

arXiv:2603.23868v2 Announce Type: replace Abstract: In this paper, we address the challenging problem of single-scene, fully unsupervised video anomaly detection (VAD), where raw videos containing bot

Negative Momentum for Convex-Concave Optimization

arXiv:2604.17145v1 Announce Type: cross Abstract: This paper revisits momentum in the context of min-max optimization. Momentum is a celebrated mechanism for accelerating gradient dynamics in settings