Search: “models”

The grip of grammar on meaning uncertainty: cross-linguistic evidence, neural correlates, and clinical relevance

arXiv:2605.01537v1 Announce Type: new Abstract: Isolated word meanings are inherently uncertain. This uncertainty reduces when they are combined and anchored in context. We propose that grammar compre

applicationsarxiv-cs-cl

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Research

Toward Resilient 5G Networks: Comparative Analysis of Federated and Centralized Learning for RF Jamming Detection

DGX agent

arXiv:2605.01705v1 Announce Type: cross Abstract: Jamming attacks are proliferating and pose a significant threat to the security of 5G and beyond networks. These attacks target 5G radio frequency (RF

researcharxiv-cs-lg

5 May 2026

Training Non-Differentiable Networks via Optimal Transport

arXiv:2605.01928v1 Announce Type: new Abstract: Neural networks increasingly embed non-differentiable components (spiking neurons, quantized layers, discrete routing, blackbox simulators, etc.) where

safetyarxiv-cs-lg

TT4D: A Pipeline and Dataset for Table Tennis 4D Reconstruction From Monocular Videos

arXiv:2605.01234v1 Announce Type: new Abstract: We present TT4D, a large-scale, high-fidelity table tennis dataset. It provides 140+ hours of reconstructed singles and doubles gameplay from monocular

Tutorials

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning

arXiv:2605.02765v1 Announce Type: cross Abstract: LLMs are increasingly used for end-user task planning, yet their black-box nature limits users' ability to ensure reliability and control. While recen

tutorialsarxiv-cs-lg

Local Ai

Ultrafast On-chip Online Learning via Spline Locality in Kolmogorov-Arnold Networks

arXiv:2602.02056v2 Announce Type: replace-cross Abstract: Ultrafast online learning is essential for high-frequency systems, such as controls for quantum computing and nuclear fusion, where adaptation

local-aiarxiv-cs-lg

Unified Map Prior Encoder for Mapping and Planning

arXiv:2605.02762v1 Announce Type: new Abstract: Online mapping and end-to-end (E2E) planning in autonomous driving remain largely sensor-centric, leaving rich map priors, including HD/SD vector maps,

safetyarxiv-cs-cv

Vanast: Virtual Try-On with Human Image Animation via Synthetic Triplet Supervision

arXiv:2604.04934v2 Announce Type: replace Abstract: We present Vanast, a unified framework that generates garment-transferred human animation videos directly from a single human image, garment images,

Virtual Scanning for NSCLC Histology: Investigating the Discriminatory Power of Synthetic PET

arXiv:2605.02746v1 Announce Type: new Abstract: Accurate histological differentiation between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is critical for personalized treatment in non-small

Virtual Speech Therapist: A Clinician-in-the-Loop AI Speech Therapy Agent for Personalized and Supervised Therapy

arXiv:2605.01101v1 Announce Type: cross Abstract: This paper develops Virtual Speech Therapist (VST), an intelligent agent-based platform that streamlines stuttering assessment and delivers customized

safetyarxiv-cs-cl

Visual Chart Representations for Cryptocurrency Regime Prediction: A Systematic Deep Learning Study

arXiv:2605.00875v1 Announce Type: new Abstract: Technical traders have long relied on visual analysis of candlestick charts to identify market patterns and predict price movements. While deep learning

Zero-Shot, Safe and Time-Efficient UAV Navigation via Potential-Based Reward Shaping, Control Lyapunov and Barrier Functions

arXiv:2605.01787v1 Announce Type: cross Abstract: Autonomous navigation and obstacle avoidance remain a core challenge of modern Unmanned Aerial Vehicles (UAVs). While traditional control methods stru

safetyarxiv-cs-lg

Hardware

AdaMeZO: Adam-style Zeroth-Order Optimizer for LLM Fine-tuning Without Maintaining the Moments

arXiv:2605.00650v1 Announce Type: new Abstract: Fine-tuning LLMs is necessary for various dedicated downstream tasks, but classic backpropagation-based fine-tuning methods require substantial GPU memo

hardwarearxiv-cs-lg

Adaptive Norm-Based Regularization for Neural Networks

arXiv:2605.00171v1 Announce Type: cross Abstract: In this paper, we study norm-based regularization methods for neural networks. We compare existing penalization approaches and introduce two regulariz

Are You the A-hole? A Fair, Multi-Perspective Ethical Reasoning Framework

arXiv:2605.00270v1 Announce Type: new Abstract: Standard methods for aggregating natural language judgments, such as majority voting, often fail to produce logically consistent results when applied to

applicationsarxiv-cs-cl

Autoformalizing Memory Specifications with Agents

arXiv:2605.00058v1 Announce Type: cross Abstract: The primary goal of Design Verification (DV) is to ensure that a proposed chip design implementation (either in code, or physical form) exactly matche

applicationsarxiv-cs-lg

Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots

arXiv:2605.00545v1 Announce Type: new Abstract: Inferring cellular trajectories from destructive snapshots is complicated by the challenges of stochasticity and non-conservative mass dynamics such as

applicationsarxiv-cs-lg

Brain MR Image Synthesis with 3D Multi-Contrast Self-Attention GAN

arXiv:2604.00070v2 Announce Type: replace-cross Abstract: Complete and high-quality multi-modal Magnetic Resonance Imaging (MRI) is essential for accurate neuro-oncological assessment, as each contras

Broadband Wide Field of View Imaging with Computational Mirrors

arXiv:2605.00029v1 Announce Type: cross Abstract: Traditional glass-based optics are typically optimized for narrow spectral bands, such as the visible (400-700nm) or shortwave infrared (1000-1800nm).

Budget Constraints as Riemannian Manifolds

arXiv:2605.00649v1 Announce Type: new Abstract: Assigning one of K options to each of N groups under a total cost budget is a recurring problem in machine learning, appearing in mixed-precision quanti

Certain Head, Uncertain Tail: Expert-Sample for Test-Time Scaling in Fine-Grained MoE

arXiv:2602.02443v2 Announce Type: replace Abstract: Test-time scaling improves LLM performance by generating multiple candidate solutions, yet token-level sampling requires temperature tuning that tra

Certifiable Factor Graph Optimization

arXiv:2603.01267v2 Announce Type: replace-cross Abstract: We show that the factor graph and certifiable estimation paradigms, which have thus far been treated as essentially independent in the literat

Characterizing control between interacting subsystems with deep Jacobian estimation

arXiv:2507.01946v2 Announce Type: replace-cross Abstract: Biological function arises through the dynamical interactions of multiple subsystems, including those between brain areas, within gene regulat

CleanBase: Detecting Malicious Documents in RAG Knowledge Databases

arXiv:2605.00460v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is vulnerable to prompt injection attacks, in which an adversary inserts malicious documents containing carefully

ClustViT: Clustering-based Token Merging for Semantic Segmentation

arXiv:2510.01948v2 Announce Type: replace Abstract: Vision Transformers can achieve high accuracy and strong generalization across various contexts, but their practical applicability on real-world rob

Color Conditional Generation with Sliced Wasserstein Guidance

arXiv:2503.19034v2 Announce Type: replace Abstract: We propose SW-Guidance, a training-free approach for image generation conditioned on the color distribution of a reference image. While it is possib

Cultural Benchmarking of LLMs in Standard and Dialectal Arabic Dialogues

arXiv:2605.00119v1 Announce Type: new Abstract: There is a significant gap in evaluating cultural reasoning in LLMs using conversational datasets that capture culturally rich and dialectal contexts. M

researcharxiv-cs-cl

Discrete Cosine Transform Based Decorrelated Attention for Vision Transformers

arXiv:2405.13901v4 Announce Type: replace Abstract: Self-attention is central to the success of Transformer architectures; however, learning the query, key, and value projections from random initializ

DMDSC: A Dynamic-Margin Deep Simplex Classifier for Open-Set Recognition on Medical Image Datasets

arXiv:2605.00675v1 Announce Type: new Abstract: Medical imaging datasets are often characterized by extreme class imbalances, where rare pathologies are significantly underrepresented compared to comm

Dynamic-TD3: A Novel Algorithm for UAV Path Planning with Dynamic Obstacle Trajectory Prediction

arXiv:2605.00059v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) finds extensive application in autonomous drone navigation within complex, high-risk environments. However, its practi

safetyarxiv-cs-ro

Local Ai

E^2DT: Efficient and Effective Decision Transformer with Experience-Aware Sampling for Robotic Manipulation

arXiv:2605.00159v1 Announce Type: new Abstract: In reinforcement learning (RL) for robotic manipulation, the Decision Transformer (DT) has emerged as an effective framework for addressing long-horizon

local-aiarxiv-cs-ro

Fair Dataset Distillation via Cross-Group Barycenter Alignment

arXiv:2605.00185v1 Announce Type: new Abstract: Dataset Distillation aims to compress a large dataset into a small synthetic one while maintaining predictive performance. We show that as different dem

safetyarxiv-cs-lg

GMGaze: MoE-Based Context-Aware Gaze Estimation with CLIP and Multiscale Transformer

arXiv:2605.00799v1 Announce Type: new Abstract: Gaze estimation methods commonly use facial appearances to predict the direction of a person gaze. However, previous studies show three major challenges

GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space

arXiv:2605.00498v1 Announce Type: new Abstract: Recent advances in Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made it standard practice to reconstruct 3D scenes from multi-vie

Agents

Group Cognition Learning: Making Everything Better Through Governed Two-Stage Agents Collaboration

arXiv:2605.00370v1 Announce Type: new Abstract: Centralized multimodal learning commonly compresses language, acoustic, and visual signals into a single fused representation for prediction. While effe

agentsarxiv-cs-lg

H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversations

arXiv:2605.00631v1 Announce Type: new Abstract: We present H-RAG, our submission to SemEval-2026 Task 8 (MTRAGEval), addressing both Task A (Retrieval) and Task C (Generation with Retrieved Passages).

researcharxiv-cs-cl

Human-in-the-Loop Meta Bayesian Optimization for Fusion Energy and Scientific Applications

arXiv:2605.00068v1 Announce Type: new Abstract: Inertial Confinement Fusion (ICF) holds transformative promise for sustainable, near-limitless clean energy, yet remains constrained by prohibitively hi

IdentiFace: Multi-Modal Iterative Diffusion Framework for Identifiable Suspect Face Generation in Crime Investigations

arXiv:2605.00526v1 Announce Type: new Abstract: Suspect face generation remains a technical challenge in crime investigations. Traditional sketch-drawing workflows suffer from low efficiency and quali

Knowing when to trust machine-learned interatomic potentials

arXiv:2605.00640v1 Announce Type: new Abstract: Prevailing machine-learned interatomic potential (MLIP) uncertainty-quantification methods rely on ensembles of independently trained backbones. These m

Learning Coarse-to-Fine Osteoarthritis Representations under Noisy Hierarchical Labels

arXiv:2605.00718v1 Announce Type: new Abstract: Knee osteoarthritis (OA) assessment involves a natural but often underused label hierarchy: a coarse binary OA decision and a fine-grained Kellgren--Law

safetyarxiv-cs-cv

LIMSSR: LLM-Driven Sequence-to-Score Reasoning under Training-Time Incomplete Multimodal Observations

arXiv:2605.00434v1 Announce Type: new Abstract: Real-world multimodal learning is often hindered by missing modalities. While Incomplete Multimodal Learning (IML) has gained traction, existing methods

Tutorials

MAEPose: Self-Supervised Spatiotemporal Learning for Human Pose Estimation on mmWave Video

arXiv:2605.00242v1 Announce Type: new Abstract: Millimetre-wave (mmWave) radar offers a more privacy-preserving alternative to RGB-based human pose estimation. However, existing methods typically rely

tutorialsarxiv-cs-cv

Making Every Verified Token Count: Adaptive Verification for MoE Speculative Decoding

arXiv:2605.00342v1 Announce Type: new Abstract: Tree-based speculative decoding accelerates autoregressive generation by verifying multiple draft candidates in parallel, but this advantage weakens for

researcharxiv-cs-cl

MMAudio-LABEL: Audio Event Labeling via Audio Generation for Silent Video

arXiv:2605.00495v1 Announce Type: cross Abstract: Recent advances in multimodal generation have enabled high-quality audio generation from silent videos. Practical applications, such as sound producti

Mutatis Mutandis: Revisiting the Comparator in Discrimination Testing

arXiv:2405.13693v4 Announce Type: replace Abstract: Testing for individual discrimination involves deriving a profile, the comparator, similar to the one making the discrimination claim, the complaina

applicationsarxiv-cs-lg

Persona-Grounded Safety Evaluation of AI Companions in Multi-Turn Conversations

arXiv:2605.00227v1 Announce Type: new Abstract: There are growing concerns about the risks posed by AI companion applications designed for emotional engagement. Existing safety evaluations often rely

safetyarxiv-cs-cl

Agents

Position: agentic AI orchestration should be Bayes-consistent

arXiv:2605.00742v1 Announce Type: cross Abstract: LLMs excel at predictive tasks and complex reasoning tasks, but many high-value deployments rely on decisions under uncertainty, for example, which to

agentsarxiv-cs-lg

Posterior Augmented Flow Matching

arXiv:2605.00825v1 Announce Type: new Abstract: Flow matching (FM) trains a time-dependent vector field that transports samples from a simple prior to a complex data distribution. However, for high-di