Search: “applications”

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models

arXiv:2604.18512v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable progress in single-image understanding, yet effective reasoning across multiple images remain

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Safety

Safety, Security, and Cognitive Risks in State-Space Models: A Systematic Threat Analysis with Spectral, Stateful, and Capacity Attacks

DGX agent

arXiv:2604.16424v1 Announce Type: cross Abstract: State-Space Models (SSMs) -- structured SSMs (S4, S4D, DSS, S5), selective SSMs (Mamba, Mamba-2), and hybrid architectures (Jamba) -- are deployed in

safetyarxiv-cs-cl

21 Apr 2026

Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks

arXiv:2604.16815v1 Announce Type: cross Abstract: Quantum error mitigation (QEM) provides a practical route for estimating reliable observables on noisy intermediate-scale quantum (NISQ) devices. Trad

local-aiarxiv-cs-lg

Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration

model-releasesarxiv-cs-cl

arXiv:2505.21471v2 Announce Type: replace Abstract: With the rapid advancement of post-training techniques for reasoning and information seeking, large language models (LLMs) can incorporate a large q

Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework

arXiv:2602.19549v2 Announce Type: replace Abstract: Visual Document Retrieval (VDR), which aims to retrieve relevant pages within vast corpora of visually-rich documents, is of significance in current

researcharxiv-cs-cl

Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images

arXiv:2604.17652v1 Announce Type: new Abstract: Sentinel-5P (S5P) plays a critical role in atmospheric monitoring; however, its spatial resolution limits fine-scale analysis. Existing super-resolution

researcharxiv-cs-cv

Semantic-based Distributed Learning for Diverse and Discriminative Representations

arXiv:2604.18237v1 Announce Type: new Abstract: In large-scale distributed scenarios, increasingly complex tasks demand more intelligent collaboration across networks, requiring the joint extraction o

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation

arXiv:2511.10370v2 Announce Type: replace Abstract: Geospatial foundation models (GFMs) for Earth observation often fail to perform reliably in environments underrepresented during pretraining. We int

Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches

arXiv:2604.16842v1 Announce Type: cross Abstract: This thesis develops numerical and theoretical approaches for understanding and analyzing singularity formation in Partial Differential Equations (PDE

Sub-metre Lunar DEM Generation and Validation from Chandrayaan-2 OHRC Multi-View Imagery Using an Open-Source Pipeline

arXiv:2604.01032v3 Announce Type: replace Abstract: High-resolution digital elevation models (DEMs) of the lunar surface are essential for surface mobility planning, landing site characterization, and

safetyarxiv-cs-cv

SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair

arXiv:2604.17184v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for automated code repair but often struggle with the complex semantic and structural correctness required.

TGLF-WINN: Data-Efficient Deep Learning Surrogate for Turbulent Transport Modeling in Fusion

arXiv:2509.07024v2 Announce Type: replace-cross Abstract: The Trapped Gyro-Landau Fluid (TGLF) model provides fast, accurate predictions of turbulent transport in tokamaks, but whole device simulation

The Gait Signature of Frailty: Transfer Learning based Deep Gait Models for Scalable Frailty Assessment

arXiv:2603.24434v2 Announce Type: replace Abstract: Frailty is a condition in aging medicine characterized by diminished physiological reserve and increased vulnerability to stressors. However, frailt

researcharxiv-cs-cv

Agents

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

arXiv:2509.02547v5 Announce Type: replace-cross Abstract: The emergence of agentic reinforcement learning (Agentic RL) marks a paradigm shift from conventional reinforcement learning applied to large

agentsarxiv-cs-cl

The MediaSpin Dataset: Post-Publication News Headline Edits Annotated for Media Bias

model-releasesarxiv-cs-cl

arXiv:2412.02271v4 Announce Type: replace Abstract: We present MediaSpin, a large-scale language resource capturing how major news outlets modify headlines after publication, and MediaSpin-in-the-Wild

Tighter Performance Theory of FedExProx

arXiv:2410.15368v2 Announce Type: replace-cross Abstract: We revisit FedExProx - a recently proposed distributed optimization method designed to enhance convergence properties of parallel proximal alg

TinySR: Pruning Diffusion for Real-World Image Super-Resolution

arXiv:2508.17434v2 Announce Type: replace Abstract: Real-world image super-resolution (Real-ISR) focuses on recovering high-quality images from low-resolution inputs that suffer from complex degradati

Toward Efficient Influence Function: Dropout as a Compression Tool

arXiv:2509.15651v2 Announce Type: replace Abstract: Assessing the impact the training data on machine learning models is crucial for understanding the behavior of the model, enhancing the transparency

Towards Reliable Testing of Machine Unlearning

arXiv:2604.16536v1 Announce Type: new Abstract: Machine learning components are now central to AI-infused software systems, from recommendations and code assistants to clinical decision support. As re

Towards Universal Skeleton-Based Action Recognition

arXiv:2604.17013v1 Announce Type: new Abstract: With the development of robotics, skeleton-based action recognition has become increasingly important, as human-robot interaction requires understanding

safetyarxiv-cs-cv

TrianguLang: Geometry-Aware Semantic Consensus for Pose-Free 3D Localization

arXiv:2603.08096v3 Announce Type: replace Abstract: Localizing objects and parts from natural language in 3D space is essential for robotics, AR, and embodied AI, yet existing methods face a trade-off

local-aiarxiv-cs-cv

Unveiling Deepfakes: A Frequency-Aware Triple Branch Network for Deepfake Detection

arXiv:2604.17477v1 Announce Type: new Abstract: Advanced deepfake technologies are blurring the lines between real and fake, presenting both revolutionary opportunities and alarming threats. While it

Upper Approximation Bounds for Neural Oscillators

arXiv:2512.01015v2 Announce Type: replace Abstract: Neural oscillators, originating from second-order ordinary differential equations (ODEs), have demonstrated strong performance in stably learning ca

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

arXiv:2402.13243v2 Announce Type: replace Abstract: Learning a human-like driving policy from large-scale driving demonstrations is promising, but the uncertainty and non-deterministic nature of plann

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

model-releasesarxiv-cs-cl

arXiv:2505.20279v4 Announce Type: replace-cross Abstract: The rapid advancement of Large Multimodal Models (LMMs) for 2D images and videos has motivated extending these models to understand 3D scenes,

Wasserstein-p Central Limit Theorem Rates: From Local Dependence to Markov Chains

arXiv:2601.08184v3 Announce Type: replace-cross Abstract: Non-asymptotic central limit theorem (CLT) rates play a central role in modern machine learning and operations research. In this paper, we stu

When Choices Become Risks: Safety Failures of Large Language Models under Multiple-Choice Constraints

arXiv:2604.16916v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is primarily evaluated under open-ended generation, where models can mitigate risk by refusing to respo

safetyarxiv-cs-cl

A methodology to rank importance of frequencies and channels in electromyography data with Decision Tree classifiers

arXiv:2604.15353v1 Announce Type: cross Abstract: This study presents a methodology for identifying the most informative frequencies and channels in electromyography (EMG) data to evaluate muscle reco

A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG

arXiv:2503.02497v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) offer powerful capabilities in code generation, natural language understanding, and domain-specific reasoning. Th

A Structure-Preserving Graph Neural Solver for Parametric Hyperbolic Conservation Laws

arXiv:2604.15617v1 Announce Type: cross Abstract: Hyperbolic conservation laws govern a wide range of transport-driven dynamics featuring shocks, contact discontinuities, and complex wave interactions

Adaptive multi-fidelity optimization with fast learning rates

arXiv:2604.16239v1 Announce Type: cross Abstract: In multi-fidelity optimization, biased approximations of varying costs of the target function are available. This paper studies the problem of optimiz

safetyarxiv-cs-lg

AdaVFM: Adaptive Vision Foundation Models for Edge Intelligence via LLM-Guided Execution

arXiv:2604.15622v1 Announce Type: new Abstract: Language-aligned vision foundation models (VFMs) enable versatile visual understanding for always-on contextual AI, but their deployment on edge devices

local-aiarxiv-cs-cv

Agents

AgentV-RL: Scaling Reward Modeling with Agentic Verifier

arXiv:2604.16004v1 Announce Type: cross Abstract: Verifiers have been demonstrated to enhance LLM reasoning via test-time scaling (TTS). Yet, they face significant challenges in complex domains. Error

agentsarxiv-cs-ai

AISysRev -- LLM-based Tool for Title-abstract Screening

arXiv:2510.06708v3 Announce Type: replace-cross Abstract: Conducting systematic reviews is laborious. In the screening or study selection phase, the number of papers can be overwhelming. Recent resear

Art3D: Training-Free 3D Generation from Flat-Colored Illustration

arXiv:2504.10466v2 Announce Type: replace Abstract: Large-scale pre-trained image-to-3D generative models have exhibited remarkable capabilities in diverse shape generations. However, most of them str

BAGEL: Benchmarking Animal Knowledge Expertise in Language Models

arXiv:2604.16241v1 Announce Type: cross Abstract: Large language models have shown strong performance on broad-domain knowledge and reasoning benchmarks, but it remains unclear how well language model

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Analysis

arXiv:2604.16205v1 Announce Type: cross Abstract: Computational X-ray absorption near-edge structure (XANES) is widely used to probe local coordination environments, oxidation states, and electronic s

Creating and Evaluating Personas Using Generative AI: A Scoping Review of 81 Articles

arXiv:2504.04927v2 Announce Type: replace-cross Abstract: As generative AI (GenAI) is increasingly applied in persona development to represent real users, understanding the implications and limitation

researcharxiv-cs-cl

cuNNQS-SCI: A Fully GPU-Accelerated Framework for High-Performance Configuration Interaction Selection withNeural Network QQantum States

arXiv:2604.15768v1 Announce Type: cross Abstract: AI-driven methods have demonstrated considerable success in tackling the central challenge of accurately solving the Schrodinger equation for complex

local-aiarxiv-cs-ai

DB-FGA-Net: Dual Backbone Frequency Gated Attention Network for Multi-Class Brain Tumor Classification with Grad-CAM Interpretability

arXiv:2510.20299v3 Announce Type: replace-cross Abstract: Brain tumors are a challenging problem in neuro-oncology, where early and precise diagnosis is important for successful treatment. Deep learni

local-aiarxiv-cs-ai

DepCap: Adaptive Block-Wise Parallel Decoding for Efficient Diffusion LM Inference

arXiv:2604.15750v1 Announce Type: cross Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive language generation due to their potential for parallel dec

local-aiarxiv-cs-ai

DINOv3 Beats Specialized Detectors: A Simple Foundation Model Baseline for Image Forensics

arXiv:2604.16083v1 Announce Type: new Abstract: With the rapid advancement of deep generative models, realistic fake images have become increasingly accessible, yet existing localization methods rely

local-aiarxiv-cs-cv

EchoVLM: Dynamic Mixture-of-Experts Vision-Language Model for Universal Ultrasound Intelligence

arXiv:2509.14977v2 Announce Type: replace Abstract: Ultrasound imaging has become the preferred imaging modality for early cancer screening due to its advantages of non-ionizing radiation, low cost, a

researcharxiv-cs-cv

Estimating Joint Interventional Distributions from Marginal Interventional Data

arXiv:2409.01794v2 Announce Type: replace-cross Abstract: In this paper we show how to exploit interventional data to acquire the joint conditional distribution of all the variables using the Maximum

Evaluating quality in synthetic data generation for large tabular health datasets

arXiv:2604.15961v1 Announce Type: new Abstract: There is no consensus in the field of synthetic data on concise metrics for quality evaluations or benchmarks on large health datasets, such as historic

From Benchmarking to Reasoning: A Dual-Aspect, Large-Scale Evaluation of LLMs on Vietnamese Legal Text

arXiv:2604.16270v1 Announce Type: cross Abstract: The complexity of Vietnam's legal texts presents a significant barrier to public access to justice. While Large Language Models offer a promising solu

Fusing Cellular Network Data and Tollbooth Counts for Urban Traffic Flow Estimation

arXiv:2604.15782v1 Announce Type: new Abstract: Traffic simulations, essential for planning urban transit infrastructure interventions, require vehicle-category-specific origin-destination (OD) data.

GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow

arXiv:2604.15612v1 Announce Type: cross Abstract: Gaussian splatting has recently gained traction as a compelling map representation for SLAM systems, enabling dense and photo-realistic scene modeling

tutorialsarxiv-cs-cv