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arXiv:2512.19396v3 Announce Type: replace Abstract: Contemporary GUI agents, while increasingly capable due to advances in Large Vision-Language Models (VLMs), often operate with a critical limitation

agentsarxiv-cs-ai

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Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving

DGX agent

arXiv:2603.13842v3 Announce Type: replace-cross Abstract: End-to-end autonomous driving is typically built upon imitation learning (IL), yet its performance is constrained by the quality of human demo

model-releasesarxiv-cs-ai

13 Apr 2026

Finite-Sample Analysis of Nonlinear Independent Component Analysis:Sample Complexity and Identifiability Bounds

arXiv:2604.08850v1 Announce Type: new Abstract: Independent Component Analysis (ICA) is a fundamental unsupervised learning technique foruncovering latent structure in data by separating mixed signals

GeoPAS: Geometric Probing for Algorithm Selection in Continuous Black-Box Optimisation

arXiv:2604.09095v1 Announce Type: new Abstract: Automated algorithm selection in continuous black-box optimisation typically relies on fixed landscape descriptors computed under a limited probing budg

Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning

arXiv:2403.19253v3 Announce Type: replace Abstract: Effective agent coordination is crucial in cooperative Multi-Agent Reinforcement Learning (MARL). While agent cooperation can be represented by grap

Local Ai

MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification

arXiv:2604.08868v1 Announce Type: cross Abstract: To ensure safe clinical integration, deep learning models must provide more than just high accuracy; they require dependable uncertainty quantificatio

local-aiarxiv-cs-ai

MeshOn: Intersection-Free Mesh-to-Mesh Composition

arXiv:2604.08799v1 Announce Type: cross Abstract: We propose MeshOn, a method that finds physically and semantically realistic compositions of two input meshes. Given an accessory, a base mesh with a

safetyarxiv-cs-cv

OASIS: Online Activation Subspace Learning for Memory-Efficient Training

arXiv:2604.09406v1 Announce Type: new Abstract: Training large language models (LLMs) is constrained by memory requirements, with activations accounting for a substantial fraction of the total footpri

On Divergence Measures for Training GFlowNets

arXiv:2410.09355v2 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) are amortized inference models designed to sample from unnormalized distributions over composable objects, with a

On the Representational Limits of Quantum-Inspired 1024-D Document Embeddings: An Experimental Evaluation Framework

arXiv:2604.09430v1 Announce Type: cross Abstract: Text embeddings are central to modern information retrieval and Retrieval-Augmented Generation (RAG). While dense models derived from Large Language M

On the Spectral Geometry of Cross-Modal Representations: A Functional Map Diagnostic for Multimodal Alignment

arXiv:2604.08579v1 Announce Type: cross Abstract: We study cross-modal alignment between independently pretrained vision (DINOv2) and language (all-MiniLM-L6-v2) encoders using the functional map fram

Online Intention Prediction via Control-Informed Learning

arXiv:2604.09303v1 Announce Type: cross Abstract: This paper presents an online intention prediction framework for estimating the goal state of autonomous systems in real time, even when intention is

Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing

arXiv:2604.08624v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are naturally suited for speech processing tasks due to their specific dynamics, which allows them to handle temporal d

Precomputing Multi-Agent Path Replanning using Temporal Flexibility

arXiv:2601.04884v2 Announce Type: replace Abstract: Executing a multi-agent plan can be challenging when an agent is delayed, because this typically creates conflicts with other agents. So, we need to

Local Ai

Process Reward Agents for Steering Knowledge-Intensive Reasoning

arXiv:2604.09482v1 Announce Type: new Abstract: Reasoning in knowledge-intensive domains remains challenging as intermediate steps are often not locally verifiable: unlike math or code, evaluating ste

local-aiarxiv-cs-ai

QARIMA: A Quantum Approach To Classical Time Series Analysis

arXiv:2604.08277v2 Announce Type: replace-cross Abstract: We present a quantum-inspired ARIMA methodology that integrates quantum-assisted lag discovery with fixed-configuration variational quantum ci

Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories

arXiv:2604.09429v1 Announce Type: cross Abstract: Recovering camera parameters from images and rendering scenes from novel viewpoints have long been treated as separate tasks in computer vision and gr

REACT3D: Recovering Articulations for Interactive Physical 3D Scenes

arXiv:2510.11340v4 Announce Type: replace Abstract: Interactive 3D scenes are increasingly vital for embodied intelligence, yet existing datasets remain limited due to the labor-intensive process of a

researcharxiv-cs-cv

Reducing Class Bias In Data-Balanced Datasets Through Hardness-Based Resampling

arXiv:2504.07031v2 Announce Type: replace Abstract: Class-bias, that is class-wise performance disparities, is typically attributed to data imbalance and addressed through frequency-based resampling.

safetyarxiv-cs-lg

Reinforcement-aware Knowledge Distillation for LLM Reasoning

arXiv:2602.22495v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) post-training has recently driven major gains in long chain-of-thought reasoning large language models (LLMs), but

Agents

Robust by Design: A Continuous Monitoring and Data Integration Framework for Medical AI

arXiv:2604.09009v1 Announce Type: new Abstract: Adaptive medical AI models often face performance drops in dynamic clinical environments due to data drift. We propose an autonomous continuous monitori

agentsarxiv-cs-cv

SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning

arXiv:2604.09452v1 Announce Type: cross Abstract: Safety guarantees are a prerequisite to the deployment of reinforcement learning (RL) agents in safety-critical tasks. Often, deployment environments

Scalable High-Recall Constraint-Satisfaction-Based Information Retrieval for Clinical Trials Matching

arXiv:2604.08849v1 Announce Type: cross Abstract: Clinical trials are central to evidence-based medicine, yet many struggle to meet enrollment targets, despite the availability of over half a million

Scheming in the wild: detecting real-world AI scheming incidents with open-source intelligence

arXiv:2604.09104v1 Announce Type: cross Abstract: Scheming, the covert pursuit of misaligned goals by AI systems, represents a potentially catastrophic risk, yet scheming research suffers from signifi

Screen, Cache, and Match: A Training-Free Causality-Consistent Reference Frame Framework for Human Animation

arXiv:2601.22160v2 Announce Type: replace-cross Abstract: Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies

SEA-Eval: A Benchmark for Evaluating Self-Evolving Agents Beyond Episodic Assessment

arXiv:2604.08988v1 Announce Type: new Abstract: Current LLM-based agents demonstrate strong performance in episodic task execution but remain constrained by static toolsets and episodic amnesia, faili

Semantic Rate-Distortion for Bounded Multi-Agent Communication: Capacity-Derived Semantic Spaces and the Communication Cost of Alignment

arXiv:2604.09521v1 Announce Type: cross Abstract: When two agents of different computational capacities interact with the same environment, they need not compress a common semantic alphabet differentl

SIC3D: Style Image Conditioned Text-to-3D Gaussian Splatting Generation

arXiv:2604.08760v1 Announce Type: new Abstract: Recent progress in text-to-3D object generation enables the synthesis of detailed geometry from text input by leveraging 2D diffusion models and differe

researcharxiv-cs-cv

SimScale: Learning to Drive via Real-World Simulation at Scale

model-releasesarxiv-cs-cv

arXiv:2511.23369v3 Announce Type: replace Abstract: Achieving fully autonomous driving systems requires learning rational decisions in a wide span of scenarios, including safety-critical and out-of-di

SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks

arXiv:2604.08865v1 Announce Type: new Abstract: Proximal Policy Optimization (PPO) is central to aligning Large Language Models (LLMs) in reasoning tasks with verifiable rewards. However, standard tok

StreamMeCo: Long-Term Agent Memory Compression for Efficient Streaming Video Understanding

model-releasesarxiv-cs-cv

arXiv:2604.09000v1 Announce Type: new Abstract: Vision agent memory has shown remarkable effectiveness in streaming video understanding. However, storing such memory for videos incurs substantial memo

Structure-Aware Fine-Grained Gaussian Splatting for Expressive Avatar Reconstruction

arXiv:2604.09324v1 Announce Type: new Abstract: Reconstructing photorealistic and topology-aware human avatars from monocular videos remains a significant challenge in the fields of computer vision an

researcharxiv-cs-cv

The causal relation between off-street parking and electric vehicle adoption in Scotland

arXiv:2604.09271v1 Announce Type: new Abstract: The transition to electric mobility hinges on maximising aggregate adoption while also facilitating equitable access. This study examines whether the 'c

safetyarxiv-cs-lg

The Fast Lane Hypothesis: Von Economo Neurons Implement a Biological Speed-Accuracy Tradeoff

arXiv:2604.09229v1 Announce Type: cross Abstract: Von Economo neurons (VENs) are large bipolar projection neurons found exclusively in the anterior cingulate cortex (ACC) and frontal insula of species

The Two-Stage Decision-Sampling Hypothesis: Understanding the Emergence of Self-Reflection in RL-Trained LLMs

arXiv:2601.01580v2 Announce Type: replace-cross Abstract: Self-reflection capabilities emerge in Large Language Models after RL post-training, with multi-turn RL achieving substantial gains over SFT c

Uncertainty Estimation for the Open-Set Text Classification systems

arXiv:2604.08560v1 Announce Type: cross Abstract: Accurate uncertainty estimation is essential for building robust and trustworthy recognition systems. In this paper, we consider the open-set text cla

Using Synthetic Data for Machine Learning-based Childhood Vaccination Prediction in Narok, Kenya

arXiv:2604.08902v1 Announce Type: new Abstract: Background: Limited data utilization in low-resource settings poses a barrier to the vaccine delivery ecosystem, undermining efforts to achieve equitabl

ViSAGE @ NTIRE 2026 Challenge on Video Saliency Prediction

model-releasesarxiv-cs-cv

arXiv:2604.08613v1 Announce Type: new Abstract: In this report, we present our champion solution for the NTIRE 2026 Challenge on Video Saliency Prediction held in conjunction with CVPR 2026. To exploi

VSI: Visual Subtitle Integration for Keyframe Selection to enhance Long Video Understanding

arXiv:2508.06869v4 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) demonstrate exceptional performance in vision-language tasks, yet their processing of long videos is

Applications

A Decomposition Perspective to Long-context Reasoning for LLMs

arXiv:2604.07981v1 Announce Type: new Abstract: Long-context reasoning is essential for complex real-world applications, yet remains a significant challenge for Large Language Models (LLMs). Despite t

applicationsarxiv-cs-cl

A Physical Agentic Loop for Language-Guided Grasping with Execution-State Monitoring

arXiv:2604.07395v1 Announce Type: cross Abstract: Robotic manipulation systems that follow language instructions often execute grasp primitives in a largely single-shot manner: a model proposes an act

safetyarxiv-cs-cv

A-SLIP: Acoustic Sensing for Continuous In-hand Slip Estimation

arXiv:2604.08528v1 Announce Type: new Abstract: Reliable in-hand manipulation requires accurate real-time estimation of slip between a gripper and a grasped object. Existing tactile sensing approaches

researcharxiv-cs-ro

A solver-in-the-loop framework for end-to-end differentiable coastal hydrodynamics

arXiv:2604.07129v1 Announce Type: cross Abstract: Numerical simulation of wave propagation and run-up is a cornerstone of coastal engineering and tsunami hazard assessment. However, applying these for

A Study of LLMs' Preferences for Libraries and Programming Languages

arXiv:2503.17181v3 Announce Type: replace-cross Abstract: Despite the rapid progress of large language models (LLMs) in code generation, existing evaluations focus on functional correctness or syntact

Accuracy Improvement of Semi-Supervised Segmentation Using Supervised ClassMix and Sup-Unsup Feature Discriminator

arXiv:2604.07122v1 Announce Type: cross Abstract: In semantic segmentation, the creation of pixel-level labels for training data incurs significant costs. To address this problem, semi-supervised lear

Active Statistical Inference

arXiv:2403.03208v3 Announce Type: replace-cross Abstract: Inspired by the concept of active learning, we propose active inferencenicode{x2013}a methodology for statistical inference with machine-l

AdaBoost Does Not Always Cycle: A Computer-Assisted Counterexample

arXiv:2604.07055v1 Announce Type: new Abstract: We give a computer-assisted counterexample to the open question, posed by Rudin, Schapire, and Daubechies in COLT 2012, of whether exhaustive AdaBoost a

Adaptive Symmetrization of the KL Divergence

arXiv:2511.11159v2 Announce Type: replace Abstract: Many tasks in machine learning can be described as or reduced to learning a probability distribution given a finite set of samples. A common approac