All entries

Generative Modeling of Complex-Valued Brain MRI Data

arXiv:2604.14800v1 Announce Type: cross Abstract: Objective. Standard Magnetic Resonance Imaging (MRI) reconstruction pipelines discard phase information captured during acquisition, despite evidence

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI

DGX agent

arXiv:2403.10559v3 Announce Type: replace Abstract: This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing

safetyarxiv-cs-lg

17 Apr 2026

GeoAgentBench: A Dynamic Execution Benchmark for Tool-Augmented Agents in Spatial Analysis

model-releasesarxiv-cs-ai

arXiv:2604.13888v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into Geographic Information Systems (GIS) marks a paradigm shift toward autonomous spatial analysis. How

Geometrically Consistent Multi-View Scene Generation from Freehand Sketches

arXiv:2604.14302v1 Announce Type: new Abstract: We tackle a new problem: generating geometrically consistent multi-view scenes from a single freehand sketch. Freehand sketches are the most geometrical

GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification

arXiv:2604.14258v1 Announce Type: cross Abstract: Large language models are typically post-trained using supervised fine-tuning (SFT) and reinforcement learning (RL), yet effectively unifying efficien

safetyarxiv-cs-lg

Giving Faces Their Feelings Back: Explicit Emotion Control for Feedforward Single-Image 3D Head Avatars

arXiv:2604.14541v1 Announce Type: new Abstract: We present a framework for explicit emotion control in feed-forward, single-image 3D head avatar reconstruction. Unlike existing pipelines where emotion

Local Ai

GlobalSplat: Efficient Feed-Forward 3D Gaussian Splatting via Global Scene Tokens

arXiv:2604.15284v1 Announce Type: new Abstract: The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representa

local-aiarxiv-cs-cv

Grading the Unspoken: Evaluating Tacit Reasoning in Quantum Field Theory and String Theory with LLMs

arXiv:2604.14188v1 Announce Type: cross Abstract: Large language models have demonstrated impressive performance across many domains of mathematics and physics. One natural question is whether such mo

Graph-Based Alternatives to LLMs for Human Simulation

arXiv:2511.02135v2 Announce Type: replace Abstract: Large language models (LLMs) have become a popular approach for simulating human behaviors, yet it remains unclear if LLMs are necessary for all sim

Applications

Graph-Based Fraud Detection with Dual-Path Graph Filtering

arXiv:2604.14235v1 Announce Type: new Abstract: Fraud detection on graph data can be viewed as a demanding task that requires distinguishing between different types of nodes. Because graph neural netw

applicationsarxiv-cs-lg

Graph Theoretical Outlier Rejection for 4D Radar Registration in Feature-Poor Environments

arXiv:2604.14857v1 Announce Type: new Abstract: Automotive 4D imaging radar is well suited for operation in dusty and low-visibility environments, but scan registration remains challenging due to scan

researcharxiv-cs-ro

GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning

model-releasesarxiv-cs-ai

arXiv:2603.01410v2 Announce Type: replace Abstract: Knowledge graphs provide structured and reliable information for many real-world applications, motivating increasing interest in combining large lan

GSNR: Graph Smooth Null-Space Representation for Inverse Problems

arXiv:2602.20328v2 Announce Type: replace Abstract: Inverse problems in imaging are ill-posed, leading to infinitely many solutions consistent with the measurements due to the non-trivial null-space o

safetyarxiv-cs-cv

GUI-Perturbed: Domain Randomization Reveals Systematic Brittleness in GUI Grounding Models

arXiv:2604.14262v1 Announce Type: new Abstract: GUI grounding models report over 85% accuracy on standard benchmarks, yet drop 27-56 percentage points when instructions require spatial reasoning rathe

H2VLR: Heterogeneous Hypergraph Vision-Language Reasoning for Few-Shot Anomaly Detection

model-releasesarxiv-cs-cv

arXiv:2604.14507v1 Announce Type: new Abstract: As a classic vision task, anomaly detection has been widely applied in industrial inspection and medical imaging. In this task, data scarcity is often a

HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet

arXiv:2604.14724v1 Announce Type: new Abstract: Vision State Space Models (SSMs) like Vim, VMamba, and SiMBA rely on complex scanning strategies to adapt sequential SSMs to process 2D images, introduc

Applications

HARNESS: Lightweight Distilled Arabic Speech Foundation Models

arXiv:2604.14186v1 Announce Type: cross Abstract: Large self-supervised speech (SSL) models achieve strong downstream performance, but their size limits deployment in resource-constrained settings. We

applicationsarxiv-cs-cl

Heat and Matern Kernels on Matchings

arXiv:2604.14331v1 Announce Type: new Abstract: Applying kernel methods to matchings is challenging due to their discrete, non-Euclidean nature. In this paper, we develop a principled framework for co

safetyarxiv-cs-lg

Local Ai

HELENA: High-Efficiency Learning-based channel Estimation using dual Neural Attention

arXiv:2506.13408v2 Announce Type: replace-cross Abstract: Accurate channel estimation is critical for high-performance Orthogonal Frequency-Division Multiplexing systems such as 5G New Radio, particul

local-aiarxiv-cs-lg

Hardware

HERMES: KV Cache as Hierarchical Memory for Efficient Streaming Video Understanding

arXiv:2601.14724v3 Announce Type: replace-cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated significant improvement in offline video understanding. Howe

hardwarearxiv-cs-cl

Hierarchical Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text

arXiv:2604.14166v1 Announce Type: new Abstract: Mapping Cyber Threat Intelligence (CTI) text to MITRE ATT&CK technique IDs is a critical task for understanding adversary behaviors and automating threa

safetyarxiv-cs-cl

Hierarchical Semantic Retrieval with Cobweb

arXiv:2510.02539v2 Announce Type: replace Abstract: Neural document retrieval often treats a corpus as a flat cloud of vectors scored at a single granularity, leaving corpus structure underused and ex

Hierarchical vs. Flat Iteration in Shared-Weight Transformers

arXiv:2604.14442v1 Announce Type: new Abstract: We present an empirical study of whether hierarchically structured, shared-weight recurrence can match the representational quality of independent-layer

High Probability Guarantees for Random Reshuffling

arXiv:2311.11841v4 Announce Type: replace-cross Abstract: We consider the stochastic gradient method with random reshuffling (mathsf{RR}) for tackling smooth nonconvex optimization problems. mathsf{RR

High-Speed Full-Color HDR Imaging via Unwrapping Modulo-Encoded Spike Streams

arXiv:2604.14632v1 Announce Type: new Abstract: Conventional RGB-based high dynamic range (HDR) imaging faces a fundamental trade-off between motion artifacts in multi-exposure captures and irreversib

Agents

Hijacking online reviews: sparse manipulation and behavioral buffering in popularity-biased rating systems

arXiv:2604.13049v1 Announce Type: cross Abstract: Online reviews and recommendation systems help users navigate overwhelming choice, but they are vulnerable to self-reinforcing distortions. This paper

agentsarxiv-cs-ai

Hoi! -- A Multimodal Dataset for Force-Grounded, Cross-View Articulated Manipulation

arXiv:2512.04884v3 Announce Type: replace Abstract: We present a dataset for force-grounded, cross-view articulated manipulation that couples what is seen with what is done and what is felt during rea

researcharxiv-cs-ro

How Embeddings Shape Graph Neural Networks: Classical vs Quantum-Oriented Node Representations

model-releasesarxiv-cs-lg

arXiv:2604.15273v1 Announce Type: new Abstract: Node embeddings act as the information interface for graph neural networks, yet their empirical impact is often reported under mismatched backbones, spl

How Retrieved Context Shapes Internal Representations in RAG

arXiv:2602.20091v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enhances large language models (LLMs) by conditioning generation on retrieved external documents, but the effec

Tutorials

How to Correctly Make Mistakes: A Framework for Constructing and Benchmarking Mistake Aware Egocentric Procedural Videos

arXiv:2604.15134v1 Announce Type: new Abstract: Reliable procedural monitoring in video requires exposure to naturally occurring human errors and the recoveries that follow. In egocentric recordings,

tutorialsarxiv-cs-cv

Tutorials

How to Fine-Tune a Reasoning Model? A Teacher-Student Cooperation Framework to Synthesize Student-Consistent SFT Data

arXiv:2604.14164v1 Announce Type: new Abstract: A widely adopted strategy for model enhancement is to use synthetic data generated by a stronger model for supervised fine-tuning (SFT). However, for em

tutorialsarxiv-cs-cl

HRDexDB: A Large-Scale Dataset of Dexterous Human and Robotic Hand Grasps

model-releasesarxiv-cs-cv

arXiv:2604.14944v1 Announce Type: cross Abstract: We present HRDexDB, a large-scale, multi-modal dataset of high-fidelity dexterous grasping sequences featuring both human and diverse robotic hands. U

Humanoid Factors: Design Principles for AI Humanoids in Human Worlds

arXiv:2602.10069v2 Announce Type: replace Abstract: Human factors research has long focused on optimizing environments, tools, and systems to account for human performance. Yet, as humanoid robots beg

safetyarxiv-cs-ro

Local Ai

HUOZIIME: An On-Device LLM-enhanced Input Method for Deep Personalization

arXiv:2604.14159v1 Announce Type: new Abstract: Mobile input method editors (IMEs) are the primary interface for text input, yet they remain constrained to manual typing and struggle to produce person

local-aiarxiv-cs-cl

HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds

arXiv:2604.14268v1 Announce Type: new Abstract: We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input mod

Tutorials

Hybrid Decision Making via Conformal VLM-generated Guidance

arXiv:2604.14980v1 Announce Type: cross Abstract: Building on recent advances in AI, hybrid decision making (HDM) holds the promise of improving human decision quality and reducing cognitive load. We

tutorialsarxiv-cs-cl

Hybrid Latents -- Geometry-Appearance-Aware Surfel Splatting

arXiv:2604.14928v1 Announce Type: new Abstract: We introduce a hybrid Gaussian-hash-grid radiance representation for reconstructing 2D Gaussian scene models from multi-view images. Similar to NeST spl

safetyarxiv-cs-cv

Identifying Information from Observations with Uncertainty and Novelty

arXiv:2501.09331v3 Announce Type: replace Abstract: A machine that learns a task from observations must encounter and process uncertainty and novelty, especially when it is to maintain performance whe

Agents

IE as Cache: Information Extraction Enhanced Agentic Reasoning

arXiv:2604.14930v1 Announce Type: new Abstract: Information Extraction aims to distill structured, decision-relevant information from unstructured text, serving as a foundation for downstream understa

agentsarxiv-cs-cl

IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation

arXiv:2511.01014v3 Announce Type: replace Abstract: Instruction-following is a fundamental ability of Large Language Models (LLMs), requiring their generated outputs to follow multiple constraints imp

IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation

arXiv:2603.04738v2 Announce Type: replace Abstract: Instruction-following is a foundational capability of large language models (LLMs), with its improvement hinging on scalable and accurate feedback f

IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning

arXiv:2604.15148v1 Announce Type: cross Abstract: Reinforcement learning has emerged as an effective paradigm for training large language models to perform search-augmented reasoning. However, existin

safetyarxiv-cs-cl

IMPACTX: improving model performance by appropriately constraining the training with teacher explanations

arXiv:2502.12222v2 Announce Type: replace Abstract: The eXplainable Artificial Intelligence (XAI) research predominantly concentrates to provide explainations about AI model decisions, especially Deep

Implicit Neural Representations: A Signal Processing Perspective

arXiv:2604.15047v1 Announce Type: new Abstract: Implicit neural representations (INRs) mark a fundamental shift in signal modeling, moving from discrete sampled data to continuous functional represent

safetyarxiv-cs-cv

ImplicitMemBench: Measuring Unconscious Behavioral Adaptation in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2604.08064v2 Announce Type: replace Abstract: Existing memory benchmarks for LLM agents evaluate explicit recall of facts, yet overlook implicit memory where experience becomes automated behavio

Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration

arXiv:2604.14837v1 Announce Type: new Abstract: Alzheimer's disease (AD) confirmation often relies on positron emission tomography (PET) or cerebrospinal fluid (CSF) analysis, which are costly and inv

Improving Clean Accuracy via a Tangent-Space Perspective on Adversarial Training

model-releasesarxiv-cs-lg

arXiv:2408.14728v2 Announce Type: replace Abstract: Adversarial training has proven effective in improving the robustness of deep neural networks against adversarial attacks. However, this enhanced ro

Improving Language Models with Intentional Analysis

arXiv:2502.04689v4 Announce Type: replace Abstract: Intent, a critical cognitive notion and mental state, is ubiquitous in human communication and problem-solving. Accurately understanding the underly