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Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty

model-releasesarxiv-cs-lg

arXiv:2604.25897v1 Announce Type: cross Abstract: Contact variability, sensing uncertainty, and external disturbances make grasp execution stochastic. Expected-quality objectives ignore tail outcomes

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VibeToken: Scaling 1D Image Tokenizers and Autoregressive Models for Dynamic Resolution Generations

DGX agent

arXiv:2604.24885v1 Announce Type: new Abstract: We introduce an efficient, resolution-agnostic autoregressive (AR) image synthesis approach that generalizes to arbitrary resolutions and aspect ratios,

applicationsarxiv-cs-cv

29 Apr 2026

Tutorials

ViPO: Visual Preference Optimization at Scale

arXiv:2604.24953v1 Announce Type: new Abstract: While preference optimization is crucial for improving visual generative models, how to effectively scale this paradigm remains largely unexplored. Curr

tutorialsarxiv-cs-cv

VISION-SLS: Safe Perception-Based Control from Learned Visual Representations via System Level Synthesis

arXiv:2604.24894v1 Announce Type: cross Abstract: We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction gu

safetyarxiv-cs-cv

Vision SmolMamba: Spike-Guided Token Pruning for Energy-Efficient Spiking State-Space Vision Models

arXiv:2604.25570v1 Announce Type: new Abstract: Spiking Transformers have shown strong potential for long-range visual modeling through spike-driven self-attention. However, their quadratic token inte

researcharxiv-cs-cv

VLM Judges Can Rank but Cannot Score: Task-Dependent Uncertainty in Multimodal Evaluation

arXiv:2604.25235v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used as automated judges for multimodal systems, yet their scores provide no indication of reliability.

Vocabulary Dropout for Curriculum Diversity in LLM Co-Evolution

arXiv:2604.03472v2 Announce Type: replace Abstract: Co-evolutionary self-play, where one language model generates problems and another solves them, promises autonomous curriculum learning without huma

Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation

arXiv:2511.21517v2 Announce Type: replace Abstract: Unlike text, speech conveys information about the speaker, such as gender, through acoustic cues like pitch. This gives rise to modality-specific bi

VOYAGER: A Training Free Approach for Generating Diverse Datasets using LLMs

arXiv:2512.12072v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly being used to generate synthetic datasets for the evaluation and training of downstream models. Howeve

Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models

arXiv:2604.25591v1 Announce Type: cross Abstract: Recent audio-aware large language models (ALLMs) have demonstrated strong capabilities across diverse audio understanding and reasoning tasks, but the

What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective

arXiv:2604.25132v1 Announce Type: new Abstract: Instruction-tuning datasets often contain substantial redundancy and low-quality samples, necessitating effective data selection methods. We propose an

When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient

arXiv:2604.25872v1 Announce Type: new Abstract: Training language models via reinforcement learning often relies on imperfect proxy rewards, since ground truth rewards that precisely define the intend

safetyarxiv-cs-lg

When the Forger Is the Judge: GPT-Image-2 Cannot Recognize Its Own Faked Documents

model-releasesarxiv-cs-cv

arXiv:2604.25213v1 Announce Type: new Abstract: OpenAI's GPT-Image-2 has effectively erased the visual boundary between authentic and AI-edited document images: a single number on a receipt can be rep

When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs

arXiv:2510.07499v2 Announce Type: replace Abstract: Recent Long-Context Language Models (LCLMs) can process hundreds of thousands of tokens in a single prompt, enabling new opportunities for knowledge

Hardware

WhisperPipe: A Resource-Efficient Streaming Architecture for Real-Time Automatic Speech Recognition

arXiv:2604.25611v1 Announce Type: new Abstract: Real-time automatic speech recognition (ASR) systems face a fundamental trade-off between transcription accuracy and computational efficiency, particula

hardwarearxiv-cs-cl

Why Do LLM-based Web Agents Fail? A Hierarchical Planning Perspective

arXiv:2603.14248v2 Announce Type: replace-cross Abstract: Large language model (LLM) web agents are increasingly used for web navigation but remain far from human reliability on realistic, long-horizo

Why Does Reinforcement Learning Generalize? A Feature-Level Mechanistic Study of Post-Training in Large Language Models

arXiv:2604.25011v1 Announce Type: new Abstract: Reinforcement learning (RL)-based post-training often improves the reasoning performance of large language models (LLMs) beyond the training domain, whi

Why Search When You Can Transfer? Amortized Agentic Workflow Design from Structural Priors

model-releasesarxiv-cs-lg

arXiv:2604.25012v1 Announce Type: new Abstract: Automated agentic workflow design currently relies on per-task iterative search, which is computationally prohibitive and fails to reuse structural know

Wiki Dumps to Training Corpora: South Slavic Case

arXiv:2604.25384v1 Announce Type: new Abstract: This paper presents a methodology for transforming raw Wikimedia dumps into quality textual corpora for seven South Slavic languages. The work is divide

Agents

Zero Shot Coordination for Sparse Reward Tasks with Diverse Reward Shapings

arXiv:2604.25076v1 Announce Type: new Abstract: Many Multi-Agent Reinforcement Learning (MARL) agents fail to adapt properly to cooperating with agents trained with the same objectives but different s

agentsarxiv-cs-lg

Tutorials

2D Pre-Training for 3D Pose Estimation

arXiv:2604.22830v1 Announce Type: new Abstract: Pre-training is a general method that is used in a range of deep learning tasks. By first training a model on one task, and then further training on the

tutorialsarxiv-cs-cv

2nd of the 5th PVUW MeViS-Audio Track: ASR-SaSaSa2VA

arXiv:2604.23935v1 Announce Type: new Abstract: Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both ap

local-aiarxiv-cs-cv

6thGrid-Net: Unified Remote Sensing Image Dehazing Based on Color Restoration and Edge-Preserving

model-releasesarxiv-cs-cv

arXiv:2604.24149v1 Announce Type: new Abstract: Remote sensing images are frequently degraded by adverse weather conditions, particularly clouds and haze, which severely impair downstream applications

A Benchmark Suite of Reddit-Derived Datasets for Mental Health Detection

arXiv:2604.23458v1 Announce Type: new Abstract: The growing availability of online support groups has opened up new windows to study mental health through natural language processing (NLP). However, i

A BERTology View of LLM Orchestrations: Token- and Layer-Selective Probes for Efficient Single-Pass Classification

arXiv:2601.13288v2 Announce Type: replace Abstract: Production LLM systems often rely on separate models for safety and other classification-heavy steps, increasing latency, VRAM footprint, and operat

A Comparative analysis of Layer-wise Representational Capacity in AR and Diffusion LLMs

arXiv:2603.07475v2 Announce Type: replace Abstract: Autoregressive (AR) language models build representations incrementally via left-to-right prediction, while diffusion language models (dLLMs) are tr

A Decoupled Human-in-the-Loop System for Controlled Autonomy in Agentic Workflows

arXiv:2604.23049v1 Announce Type: new Abstract: AI agents are increasingly deployed to execute tasks and make decisions within agentic workflows, introducing new requirements for safe and controlled a

safetyarxiv-cs-ai

A Differentiable Framework for Global Circulation Model Precipitation Bias Correction

arXiv:2604.23045v1 Announce Type: new Abstract: Systematic biases in Global Circulation Model (GCM) outputs limit their direct applicability in regional planning, necessitating bias correction. Correc

safetyarxiv-cs-lg

A Digital Pathology Resource for Liver Cancer Quantification with Datasets, Benchmarks, and Tools

arXiv:2604.22858v1 Announce Type: new Abstract: Liver cancer, especially hepatocellular carcinoma (HCC), imposes a substantial global disease burden. Accurate diagnosis and prognostic assessment direc

local-aiarxiv-cs-cv

A Divergence-Based Method for Weighting and Averaging Model Predictions

arXiv:2604.24172v1 Announce Type: cross Abstract: This paper uses a minimum divergence framework to introduce a new way of calculating model weights that can be used to average probabilistic predictio

researcharxiv-cs-lg

A Dynamic Learning Observatory Reveals the Rapid Salinization of Satkhira, Bangladesh

arXiv:2604.23127v1 Announce Type: cross Abstract: Soil salinity is a major environmental challenge in coastal Bangladesh, threatening agricultural productivity and local livelihoods. This study develo

local-aiarxiv-cs-lg

A Fano-Style Accuracy Upper Bound for LLM Single-Pass Reasoning in Multi-Hop QA

model-releasesarxiv-cs-ai

arXiv:2509.21199v3 Announce Type: replace Abstract: Multi-Hop Question Answering (MHQA) requires integrating dispersed, interdependent evidence through sequential reasoning under noise. This task is c

A Functorial Formulation of Neighborhood Aggregating Deep Learning

arXiv:2604.24672v1 Announce Type: new Abstract: We provide a mathematical interpretation of convolutional (or message passing) neural networks by using presheaves and copresheaves of the set of contin

researcharxiv-cs-lg

A General Framework for Generative Self-supervised Learning in Non-invasive Estimation of Physiological Parameters Using Photoplethysmography

model-releasesarxiv-cs-ai

arXiv:2604.22780v1 Announce Type: cross Abstract: Aligning physiological parameter labels with large-scale photoplethysmographic (PPG) data for deep learning is challenging and resource-intensive. Whi

Tutorials

A General Representation-Based Approach to Multi-Source Domain Adaptation

arXiv:2604.23790v1 Announce Type: new Abstract: A central problem in unsupervised domain adaptation is determining what to transfer from labeled source domains to an unlabeled target domain. To handle

tutorialsarxiv-cs-lg

A Graph-Augmented knowledge Distillation based Dual-Stream Vision Transformer with Region-Aware Attention for Gastrointestinal Disease Classification with Explainable AI

arXiv:2512.21372v2 Announce Type: replace-cross Abstract: The accurate classification of gastrointestinal diseases from endoscopic and histopathological imagery remains a significant challenge in medi

local-aiarxiv-cs-cv

A Heterogeneous Two-Stream Framework for Video Action Recognition with Comparative Fusion Analysis

arXiv:2604.23415v1 Announce Type: new Abstract: Most two-stream action recognition networks apply the same convolutional backbone to both RGB and optical flow streams, ignoring the fact that the two m

researcharxiv-cs-cv

Applications

A Hierarchical Ensemble Inference Pipeline for Robust White Blood Cell Classification Under Domain Shifts

arXiv:2604.23271v1 Announce Type: new Abstract: Automated white blood cell (WBC) classification is essential for scalable leukaemia screening. However, real-world deployment is challenged by domain sh

applicationsarxiv-cs-cv

A Hierarchical Self-Consistent Regularization Approach to Satellite Image Time Series Classification

model-releasesarxiv-cs-cv

arXiv:2510.04916v2 Announce Type: replace Abstract: Deep learning has become increasingly important in remote sensing image classification due to its ability to extract semantic information from compl

A Large-Scale, Cross-Disciplinary Corpus of Systematic Reviews

arXiv:2604.22864v1 Announce Type: cross Abstract: Existing benchmarks for systematic reviewing remain limited either in scale or in disciplinary coverage, with some collections comprising only a modes

A Layer Separation Optimization Framework for Cross-Entropy Training in Deep Learning

arXiv:2604.23225v1 Announce Type: new Abstract: This paper investigates the deep learning optimization problem with softmax cross-entropy loss. We propose a layer separation strategy to alleviate the

researcharxiv-cs-lg

A Lightweight Explainable Guardrail for Prompt Safety

arXiv:2602.15853v2 Announce Type: replace-cross Abstract: We propose a lightweight explainable guardrail (LEG) method to detect unsafe prompts. LEG uses a multi-task learning architecture to jointly l

safetyarxiv-cs-ai

Agents

A Lightweight Toggleable Adhesion Prototype for Multirotor UAV Landing on Tilting Platforms

arXiv:2604.23074v1 Announce Type: new Abstract: Autonomous multirotor landings on uncrewed surface vessels (USVs) are critical for persistent maritime operations but remain challenging due to wave-ind

agentsarxiv-cs-ro

A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws

model-releasesarxiv-cs-lg

arXiv:2604.24037v1 Announce Type: new Abstract: Emergent intelligence have played a major role in the modern AI development. While existing studies primarily rely on empirical observations to characte

A Lower Bound for the Number of Linear Regions of Ternary ReLU Regression Neural Networks

arXiv:2507.16079v2 Announce Type: replace-cross Abstract: With the advancement of deep learning, reducing computational complexity and memory consumption has become a critical challenge, and ternary n

researcharxiv-cs-ai

A Milestone in Formalization: The Sphere Packing Problem in Dimension 8

arXiv:2604.23468v1 Announce Type: cross Abstract: In 2016, Viazovska famously solved the sphere packing problem in dimension 8, using modular forms to construct a 'magic' function satisfying optimalit

researcharxiv-cs-ai

A Mixture of Experts Vision Transformer for High-Fidelity Surface Code Decoding

arXiv:2601.12483v2 Announce Type: replace-cross Abstract: Quantum error correction is a key ingredient for large scale quantum computation, protecting logical information from physical noise by encodi

local-aiarxiv-cs-lg

A Multi-Dimensional Audit of Politically Aligned Large Language Models

arXiv:2604.24429v1 Announce Type: new Abstract: As the application of Large Language Models (LLMs) spreads across various industries, there are increasing concerns about the potential for their misuse