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ViBE: Visual-to-M/EEG Brain Encoding via Spatio-Temporal VAE and Distribution-Aligned Projection

arXiv:2604.26218v1 Announce Type: new Abstract: Brain encoding models not only serve to decipher how visual stimuli are transformed into neural responses, but also represent a critical step toward vis

safetyarxiv-cs-cv

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Human DGX agent

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Local Ai

ViCrop-Det: Spatial Attention Entropy Guided Cropping for Training-Free Small-Object Detection

DGX agent

arXiv:2604.26806v1 Announce Type: cross Abstract: Transformer-based architectures have established a dominant paradigm in global semantic perception; however, they remain fundamentally constrained by

local-aiarxiv-cs-ai

30 Apr 2026

Hardware

Video Compression Meets Video Generation: Latent Inter-Frame Pruning with Attention Recovery

arXiv:2603.05811v2 Announce Type: replace Abstract: Current video generation models suffer from high computational latency, making real-time applications prohibitively costly. In this paper, we addres

hardwarearxiv-cs-cv

VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models

arXiv:2505.22897v2 Announce Type: replace Abstract: While bias in large language models (LLMs) is well-studied, similar concerns in vision-language models (VLMs) have received comparatively less atten

Virtual-reality based patient-specific simulation of spine surgical procedures: A fast, highly automated and high-fidelity system for surgical education and planning

arXiv:2604.26781v1 Announce Type: new Abstract: Surgical training involves didactic teaching, mentor-led learning, surgical skills laboratories, and direct exposure to surgery; however, increasing cli

applicationsarxiv-cs-cv

ViTaPEs: Visuotactile Position Encodings for Cross-Modal Alignment in Multimodal Transformers

arXiv:2505.20032v3 Announce Type: replace Abstract: Tactile sensing provides local essential information that is complementary to visual perception, such as texture, compliance, and force. Despite rec

safetyarxiv-cs-cv

VLN-Cache: Enabling Token Caching for VLN Models with Visual/Semantic Dynamics Awareness

arXiv:2603.07080v3 Announce Type: replace-cross Abstract: Vision-and-Language Navigation (VLN) increasingly relies on large vision-language models, but their inference cost conflicts with real-time de

VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection

arXiv:2604.26313v1 Announce Type: cross Abstract: We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Synta

Walk With Me: Long-Horizon Social Navigation for Human-Centric Outdoor Assistance

arXiv:2604.26839v1 Announce Type: new Abstract: Assisting humans in open-world outdoor environments requires robots to translate high-level natural-language intentions into safe, long-horizon, and soc

safetyarxiv-cs-ro

WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models

arXiv:2510.14438v2 Announce Type: replace Abstract: The hallmark of Deep Research agents lies in compositional reasoning, the capacity to aggregate distributed, heterogeneous information into coherent

What Kind of Language is Easy to Language-Model Under Curriculum Learning?

arXiv:2604.26844v1 Announce Type: new Abstract: Many of the thousands of attested languages share common configurations of features, creating a spectrum from typologically very rare (e.g., object-verb

safetyarxiv-cs-cl

When Annotators Disagree, Topology Explains: Mapper, a Topological Tool for Exploring Text Embedding Geometry and Ambiguity

arXiv:2510.17548v2 Announce Type: replace Abstract: Language models are often evaluated with scalar metrics like accuracy, but such measures fail to capture how models internally represent ambiguity,

safetyarxiv-cs-cl

When Hidden States Drift: Can KV Caches Rescue Long-Range Speculative Decoding?

arXiv:2604.26412v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference, but SOTA hidden-state-based drafters suffer from long-range decay: draft accuracy degrades as the specul

When to Retrieve During Reasoning: Adaptive Retrieval for Large Reasoning Models

model-releasesarxiv-cs-ai

arXiv:2604.26649v1 Announce Type: cross Abstract: Large reasoning models such as DeepSeek-R1 and OpenAI o1 generate extended chains of thought spanning thousands of tokens, yet their integration with

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling

arXiv:2604.26644v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on mathematical reasoning tasks but remain unreliable on challenging instances. Existing test-t

researcharxiv-cs-ai

Which Face and Whose Identity? Solving the Dual Challenge of Deepfake Proactive Forensics in Multi-Face Scenarios

arXiv:2604.26342v1 Announce Type: new Abstract: Unlike single-face forgeries, deepfakes in complex multi-person interaction scenarios (such as group photos and multi-person meetings) more closely refl

applicationsarxiv-cs-cv

Local Ai

Who Trains Matters: Federated Learning under Enrollment and Participation Selection Biases

arXiv:2604.26604v1 Announce Type: new Abstract: Federated learning (FL) trains a shared model from updates contributed by distributed clients, often implicitly assuming that contributing clients are r

local-aiarxiv-cs-lg

Why Attend to Everything? Focus is the Key

arXiv:2604.03260v2 Announce Type: replace-cross Abstract: Standard attention scales quadratically with sequence length. Efficient attention methods reduce this O(n^2) cost, but when retrofitted into p

researcharxiv-cs-ai

Why Domain Matters: A Preliminary Study of Domain Effects in Underwater Object Detection

arXiv:2604.26174v1 Announce Type: new Abstract: Domain shift, where deviations between training and deployment data distributions degrade model performance, is a key challenge in underwater environmen

applicationsarxiv-cs-cv

World2VLM: Distilling World Model Imagination into VLMs for Dynamic Spatial Reasoning

arXiv:2604.26934v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong performance on static visual understanding, yet they still struggle with dynamic spatial reasoning that

Zero-Shot to Full-Resource: Cross-lingual Transfer Strategies for Aspect-Based Sentiment Analysis

arXiv:2604.26619v1 Announce Type: new Abstract: Aspect-based Sentiment Analysis (ABSA) extracts fine-grained opinions toward specific aspects within text but remains largely English-focused despite ma

8DNA: 8D Neural Asset Light Transport by Distribution Learning

arXiv:2604.25129v1 Announce Type: cross Abstract: High-fidelity 3D assets exhibit intriguing global illumination effects like subsurface scattering, glossy interreflections, and fine-scale fiber scatt

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards

arXiv:2505.13766v5 Announce Type: replace-cross Abstract: Software Quality Assurance (SQA) is critical for delivering reliable, secure, and efficient software products. The Software Quality Assurance

safetyarxiv-cs-cl

A Comparative Analysis on the Performance of Upper Confidence Bound Algorithms in Adaptive Deep Neural Networks

arXiv:2604.24810v1 Announce Type: new Abstract: Edge computing environments impose strict constraints on energy consumption and latency, making the deployment of deep neural networks a significant cha

A Comparative Study in Surgical AI: Datasets, Foundation Models, and Barriers to Med-AGI

model-releasesarxiv-cs-cv

arXiv:2603.27341v2 Announce Type: replace-cross Abstract: Recent Artificial Intelligence (AI) models have matched or exceeded human experts in several benchmarks of biomedical task performance, but su

A Deep Reinforcement Learning Approach to Automated Stock Trading, using xLSTM Networks

arXiv:2503.09655v2 Announce Type: replace-cross Abstract: Traditional Long Short-Term Memory (LSTM) networks are effective for handling sequential data but have limitations such as gradient vanishing

safetyarxiv-cs-lg

A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback

arXiv:2604.25025v1 Announce Type: cross Abstract: Preference feedback, in the form of pairwise comparisons rather than scalar scores, has seen increasing use in applications such as human-, laboratory

applicationsarxiv-cs-lg

A graph generation pipeline for critical infrastructures based on heuristics, images and depth data

arXiv:2512.07269v2 Announce Type: replace Abstract: Virtual representations of physical critical infrastructures, such as water or energy plants, are used for simulations and digital twins to ensure r

A multi-stage soft computing framework for complex disease modelling and decision support: A liver cirrhosis case study

arXiv:2604.24796v1 Announce Type: cross Abstract: Liver cirrhosis is a major global health problem causing millions of deaths annually, and timely detection with aggressive treatment can significantly

applicationsarxiv-cs-lg

Tutorials

A New Kind of Network? Review and Reference Implementation of Neural Cellular Automata

arXiv:2604.24990v1 Announce Type: new Abstract: Stephen Wolfram proclaimed in his 2003 seminal work 'A New Kind Of Science' that simple recursive programs in the form of Cellular Automata (CA) are a p

tutorialsarxiv-cs-cv

A paradox of AI fluency

arXiv:2604.25905v1 Announce Type: new Abstract: How much does a user's skill with AI shape what AI actually delivers for them? This question is critical for users, AI product builders, and society at

A Survey on LLM-based Conversational User Simulation

arXiv:2604.24977v1 Announce Type: new Abstract: User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary

A systematic literature Review for Transformer-based Software Vulnerability detection

arXiv:2604.24822v1 Announce Type: cross Abstract: Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas

applicationsarxiv-cs-lg

A Systematic Post-Train Framework for Video Generation

arXiv:2604.25427v1 Announce Type: new Abstract: While large-scale video diffusion models have demonstrated impressive capabilities in generating high-resolution and semantically rich content, a signif

safetyarxiv-cs-cv

A Unifying Framework for Unsupervised Concept Extraction

arXiv:2604.24936v1 Announce Type: new Abstract: Techniques for concept extraction, such as sparse autoencoders and transcoders, aim to extract high-level symbolic concepts from low-level nonsymbolic r

researcharxiv-cs-lg

Tutorials

Accelerating Regularized Attention Kernel Regression for Spectrum Cartography

arXiv:2604.25138v1 Announce Type: cross Abstract: Spectrum cartography reconstructs spatial radio fields from sparse and heterogeneous wireless measurements, underpinning many sensing and optimization

tutorialsarxiv-cs-lg

Accuracy Improvement of Cell Image Segmentation Using Feedback Former

arXiv:2408.12974v4 Announce Type: replace Abstract: Semantic segmentation of microscopy cell images by deep learning is a significant technique. We considered that the Transformers, which have recentl

Tutorials

Accurate and Robust Generative Approach for Overcoming Data Sparsity and Imbalance in Landslide Modeling with A Tabular Foundation Model

arXiv:2604.25159v1 Announce Type: new Abstract: Landslide investigation relies on sufficient and well-balanced observational data influenced by geological, hydrological, and anthropogenic factors. Ava

tutorialsarxiv-cs-lg

Adaptable phase retrieval for coherent transition radiation spectroscopy based on differentiable physics information

arXiv:2604.25489v1 Announce Type: cross Abstract: Coherent transition radiation (CTR) spectroscopy is a critical diagnostic for characterizing the longitudinal structure of relativistic electron bunch

Adaptive Meta-Learning Stochastic Gradient Hamiltonian Monte Carlo Simulation for Bayesian Updating of Structural Dynamic Models

arXiv:2604.25710v1 Announce Type: cross Abstract: In the last few decades, Markov chain Monte Carlo (MCMC) methods have been widely applied to Bayesian updating of structural dynamic models in the fie

researcharxiv-cs-lg

AdaTooler-V: Adaptive Tool-Use for Images and Videos

model-releasesarxiv-cs-cv

arXiv:2512.16918v3 Announce Type: replace Abstract: Recent advances have shown that multimodal large language models (MLLMs) benefit from multimodal interleaved chain-of-thought (CoT) with vision tool

ADE: Adaptive Dictionary Embeddings -- Scaling Multi-Anchor Representations to Large Language Models

arXiv:2604.24940v1 Announce Type: new Abstract: Word embeddings are fundamental to natural language processing, yet traditional approaches represent each word with a single vector, creating representa

Agent-Diff: Benchmarking LLM Agents on Enterprise API Tasks via Code Execution with State-Diff-Based Evaluation

arXiv:2602.11224v3 Announce Type: replace-cross Abstract: We present Agent-Diff, a novel benchmarking framework for evaluating agentic Large Language Models (LLMs) on real-world productivity software

Agents

Agentic AI for Remote Sensing: Technical Challenges and Research Directions

arXiv:2604.24919v1 Announce Type: new Abstract: Earth Observation (EO) is moving beyond static prediction toward multi-step analytical workflows that require coordinated reasoning over data, tools, an

agentsarxiv-cs-cv

Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses

arXiv:2604.25850v1 Announce Type: new Abstract: Harnesses have become a central determinant of coding-agent performance, shaping how models interact with repositories, tools, and execution environment

Agents

AIDOVECL: AI-generated Dataset of Outpainted Vehicles for Eye-level Classification and Localization

arXiv:2410.24116v3 Announce Type: replace Abstract: Image labeling is a critical bottleneck in the development of computer vision technologies, often constraining machine learning performance due to t

agentsarxiv-cs-cv

Align then Adapt: Rethinking Parameter-Efficient Transfer Learning in 4D Perception

model-releasesarxiv-cs-cv

arXiv:2602.23069v2 Announce Type: replace Abstract: Point cloud video understanding is critical for robotics as it accurately encodes motion and scene interaction. We recognize that 4D datasets are fa

An analysis of sensor selection for fruit picking with suction-based grippers

arXiv:2604.24906v1 Announce Type: cross Abstract: Robotic fruit harvesting often fails to reliably detect whether a fruit has been successfully picked, limiting efficiency and increasing crop damage.

researcharxiv-cs-lg