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Hybrid Quantum Reinforcement Learning with QAOA for Improved Vehicle Routing Optimization

arXiv:2605.01574v1 Announce Type: new Abstract: Vehicle Routing Problem (VRP) is one of the most complex NP-hard combinatorial optimization problem in transportation and logistics that requires a dyna

safetyarxiv-cs-lg

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Local Ai

Hybrid Visual Telemetry for Bandwidth-Constrained Robotic Vision: A Pilot Study with HEVC Base Video and JPEG ROI Stills

DGX agent

arXiv:2605.01826v1 Announce Type: new Abstract: Bandwidth-constrained robotic and surveillance systems often rely on a single compressed video stream to support both continuous scene awareness and dow

local-aiarxiv-cs-cv

5 May 2026

Hydra-DP3: Frequency-Aware Right-Sizing of 3D Diffusion Policies for Visuomotor Control

arXiv:2605.01581v1 Announce Type: new Abstract: Diffusion-based visuomotor policies perform well in robotic manipulation, yet current methods still inherit image-generation-style decoders and multi-st

safetyarxiv-cs-ro

HyMem: Hybrid Memory Architecture with Dynamic Retrieval Scheduling

arXiv:2602.13933v2 Announce Type: replace Abstract: Large language model (LLM) agents demonstrate strong performance in short-text contexts but often underperform in extended dialogues due to ineffici

researcharxiv-cs-ai

Hyp2Former: Hierarchy-Aware Hyperbolic Embeddings for Open-Set Panoptic Segmentation

arXiv:2605.02580v1 Announce Type: new Abstract: Recognizing unknown objects is crucial for safety-critical applications such as autonomous driving and robotics. Open-Set Panoptic Segmentation (OPS) ai

safetyarxiv-cs-cv

Local Ai

IConFace: Identity-Structure Asymmetric Conditioning for Unified Reference-Aware Face Restoration

arXiv:2605.02814v1 Announce Type: new Abstract: Blind face restoration is highly ill-posed under severe degradation, where identity-critical details may be missing from the degraded input. Same-identi

local-aiarxiv-cs-cv

IMPACT-HOI: Supervisory Control for Onset-Anchored Partial HOI Event Construction

arXiv:2605.01666v1 Announce Type: new Abstract: We present IMPACT-HOI, a mixed-initiative framework for annotating egocentric procedural video by constructing structured event graphs for Human-Object

IMPACT-Scribe: Interactive Temporal Action Segmentation with Boundary Scribbles and Query Planning

arXiv:2605.01668v1 Announce Type: new Abstract: Dense temporal annotation of procedural activity videos is vital for action understanding and embodied intelligence but remains labor-intensive due to r

Implicature in Interaction: Understanding Implicature Improves Alignment in Human-LLM Interaction

arXiv:2510.25426v2 Announce Type: replace Abstract: The rapid advancement of Large Language Models (LLMs) is positioning language at the core of human-computer interaction (HCI). We argue that advanci

safetyarxiv-cs-cl

Implicit Neural Representation-Based Continuous Single Image Super-Resolution: An Empirical Benchmark

arXiv:2601.17723v2 Announce Type: replace Abstract: Implicit neural representation (INR) has become the standard approach for arbitrary-scale image super-resolution (ASSR). To date, no empirical study

Importance-Guided Basis Selection for Low-Rank Decomposition of Large Language Models

model-releasesarxiv-cs-lg

arXiv:2605.01627v1 Announce Type: new Abstract: Low-rank decomposition is a compelling approach for compressing large language models, but its effectiveness hinges on selecting which singular-vector b

Improving Factuality in LLMs via Inference-Time Knowledge Graph Construction

arXiv:2509.03540v3 Announce Type: replace Abstract: Large Language Models (LLMs) often struggle with producing factually consistent answers due to limitations in their parametric memory. Retrieval-Aug

Improving Imbalanced Multi-Label Chest X-Ray Diagnosis via CBAM-Enhanced CNN Backbones

arXiv:2605.02328v1 Announce Type: new Abstract: Chest radiography is a widely used imaging modality for thoracic disease diagnosis, yet its conventional interpretation remains time-consuming and heavi

Improving LLM Code Generation via Requirement-Aware Curriculum Reinforcement Learning

arXiv:2605.00433v1 Announce Type: cross Abstract: Code generation, which aims to automatically generate source code from given programming requirements, has the potential to substantially improve soft

researcharxiv-cs-ai

Improving Model Safety by Targeted Error Correction

arXiv:2605.02544v1 Announce Type: cross Abstract: The widespread adoption of machine learning in critical applications demands techniques to mitigate high-consequence errors. Our method utilizes a dua

safetyarxiv-cs-cv

Tutorials

Inducing Permutation Invariant Priors in Bayesian Optimization for Carbon Capture and Storage Applications

arXiv:2605.02409v1 Announce Type: new Abstract: Bayesian Optimization is an iterative method, tailored to optimizing expensive black box objective functions. Surrogate models like Gaussian Processes,

tutorialsarxiv-cs-lg

InfantAgent-Next: A Multimodal Generalist Agent for Automated Computer Interaction

model-releasesarxiv-cs-ai

arXiv:2505.10887v3 Announce Type: replace Abstract: This paper introduces extsc{InfantAgent-Next}, a generalist agent capable of interacting with computers in a multimodal manner, encompassing text, i

InfiltrNet: Dual-Branch CNN-Transformer Architecture for Brain Tumor Infiltration Risk Prediction

arXiv:2605.02230v1 Announce Type: new Abstract: Gliomas are aggressive brain tumors that infiltrate surrounding tissue beyond the visible tumor margins observed on Magnetic Resonance Imaging (MRI). Pr

Hardware

InfiniteDiffusion: Bridging Learned Fidelity and Procedural Utility for Open-World Terrain Generation

arXiv:2512.08309v4 Announce Type: replace Abstract: For decades, procedural worlds have been built on procedural noise functions such as Perlin noise, which are fast and infinite, yet fundamentally li

hardwarearxiv-cs-cv

InfoLaw: Information Scaling Laws for Large Language Models with Quality-Weighted Mixture Data and Repetition

arXiv:2605.02364v1 Announce Type: new Abstract: Upweighting high-quality data in LLM pretraining often improves performance, but in datalimited regimes, especially under overtraining, stronger upweigh

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression

arXiv:2605.01402v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) struggle with numerical regression under long-tailed target distributions. Token-level supervised fine-tuning (

safetyarxiv-cs-cl

Instance-Aware Parameter Configuration in Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem

model-releasesarxiv-cs-ai

arXiv:2605.00572v1 Announce Type: new Abstract: Algorithm performance in combinatorial optimization is highly sensitive to parameter settings, while a single globally tuned configuration often fails t

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation

arXiv:2512.21788v3 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning of Diffusion Transformers (DiTs) for diverse, multi-conditional tasks often suffers from task interference when usin

Interactive Multi-Turn Retrieval for Health Videos

arXiv:2605.01409v1 Announce Type: cross Abstract: The growing availability of health-related instructional videos creates new opportunities for clinical training, patient rehabilitation, and health ed

Interlaced R2D2 DNN Series for Scalable Non-Cartesian MRI with Sensitivity Self-calibration

arXiv:2503.09559v3 Announce Type: replace-cross Abstract: We introduce interlaced R2D2 (iR2D2), a DNN series paradigm for scalable image reconstruction from accelerated non-Cartesian k-space acquisiti

InterPhys: Physics-aware Human Motion Synthesis in a Dynamic Scene

arXiv:2605.01036v1 Announce Type: new Abstract: This paper tackles the problem of physics-aware human motion synthesis in a dynamic scene. Unlike existing works which mainly tend to generate physicall

Interpretable Difficulty-Aware Knowledge Tracing in Tutor-Student Dialogues

arXiv:2605.01097v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have led to the development of AI-powered tutoring systems that provide interactive support via dialogue

Interpretable experiential learning based on state history and global feedback

model-releasesarxiv-cs-lg

arXiv:2605.00940v1 Announce Type: new Abstract: A new interpretable experiential learning model based on state history and global feedback is presented. It is capable of learning a behavioral model re

Tutorials

Intervention-Based Self-Supervised Learning: A Causal Probe Paradigm for Remote Photoplethysmography

arXiv:2605.00882v1 Announce Type: new Abstract: Remote Photoplethysmography (rPPG) enables convenient non-contact physiological measurement. Existing Self-Supervised Learning (SSL) methods commonly fa

tutorialsarxiv-cs-cv

Investigating Anthropometric Fidelity in SAM 3D Body

arXiv:2601.06035v2 Announce Type: replace-cross Abstract: The release of SAM 3D Body is a recent development in human mesh recovery, demonstrating improved performance in producing clean, topologicall

safetyarxiv-cs-cv

IPS: In-Prompt Process Supervision for Short Video Content Moderation

arXiv:2412.15251v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are effective at capturing the semantics of short video content; however, they often fail to attend to the

safetyarxiv-cs-cl

Is It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval

arXiv:2605.02392v1 Announce Type: new Abstract: Novelty assessment is a critical yet complex task in the examination process for patent acceptance, requiring examiners to determine whether an inventio

Is there 'Secret Sauce'' in Large Language Model Development?

model-releasesarxiv-cs-lg

arXiv:2602.07238v2 Announce Type: replace-cross Abstract: Do leading LLM developers possess a proprietary ``secret sauce'', or is LLM performance driven by scaling up compute? Using training and bench

Tutorials

Isotropic Fourier Neural Operators

arXiv:2605.02597v1 Announce Type: new Abstract: Fourier Neural Operators are deep learning models that learn mappings between function spaces and can be used to learn and solve partial differential eq

tutorialsarxiv-cs-lg

jina-vlm: Small Multilingual Vision Language Model

model-releasesarxiv-cs-cl

arXiv:2512.04032v3 Announce Type: replace Abstract: We present jina-vlm, a token-efficient 2.4B parameter vision-language model that achieves state-of-the-art multilingual VQA performance among open 2

Joint Architecture-Token-Bitwidth Multi-Axis Optimization of Vision Transformers for Semiconductor IC Packaging

arXiv:2605.01742v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved strong performance in visual recognition, yet their deployment in resource-constrained industrial environments

KANs need curvature: penalties for compositional smoothness

arXiv:2605.02190v1 Announce Type: new Abstract: Kolmogorov-Arnold networks (KANs) offer a potent combination of accuracy and interpretability, thanks to their compositions of learnable univariate acti

researcharxiv-cs-lg

Kernel Treatment Effects with Adaptively Collected Data

arXiv:2510.10245v2 Announce Type: replace-cross Abstract: Adaptive experiments improve efficiency by adjusting treatment assignments based on past outcomes, but this adaptivity breaks the i.i.d. assum

researcharxiv-cs-lg

Kinematic Kitbashing

arXiv:2510.13048v2 Announce Type: replace Abstract: We introduce Kinematic Kitbashing, an optimization framework that synthesizes articulated 3D objects by assembling reusable parts conditioned on an

researcharxiv-cs-ro

Know Yourself Better: Diverse Object-Related Features Improve Open Set Recognition

arXiv:2404.10370v3 Announce Type: replace Abstract: Open set recognition (OSR) is a critical aspect of machine learning, addressing the challenge of detecting novel classes during inference. Within th

Knowledge-Based Design Requirements for Generative Social Robots in Higher Education

arXiv:2602.12873v4 Announce Type: replace-cross Abstract: Generative social robots (GSRs) powered by large language models enable adaptive, conversational tutoring but also introduce risks such as mis

safetyarxiv-cs-ai

LabBuilder: Protocol-Grounded 3D Layout Generation for Interactable and Safe Laboratory

arXiv:2605.02288v1 Announce Type: new Abstract: Automated laboratories hold the promise of accelerating scientific discovery, yet their deployment is bottlenecked by the difficulty of designing safe a

Language models recognize dropout and Gaussian noise applied to their activations

model-releasesarxiv-cs-ai

arXiv:2604.17465v2 Announce Type: replace Abstract: We provide evidence that language models can detect, localize and, to a certain degree, verbalize the difference between perturbations applied to th

Applications

Laplacian Frequency Interaction Network for Rural Thematic Road Extraction

arXiv:2605.02866v1 Announce Type: new Abstract: Rural thematic road network construction aims to extract topological road structures from movement trajectory images of agricultural machinery. However,

applicationsarxiv-cs-cv

Agents

Large Language Models for Multi-Robot Systems: A Survey

arXiv:2502.03814v5 Announce Type: replace Abstract: The rapid advancement of Large Language Models (LLMs) has opened new possibilities in Multi-Robot Systems (MRS), enabling enhanced communication, ta

agentsarxiv-cs-ro

Large margin classifier with graph-based adaptive regularization

arXiv:2605.02027v1 Announce Type: new Abstract: This paper introduces the use of per-class regularization hyperparameters in Gabriel graph-based binary classifiers. We demonstrate how the quality inde

researcharxiv-cs-lg

Latent Bridge: Feature Delta Prediction for Efficient Dual-System Vision-Language-Action Model Inference

arXiv:2605.02739v1 Announce Type: new Abstract: Dual-system Vision-Language-Action (VLA) models achieve state-of-the-art robotic manipulation but are bottlenecked by the VLM backbone, which must execu

researcharxiv-cs-ro

Latent Space Probing for Adult Content Detection in Video Generative Models

arXiv:2605.00874v1 Announce Type: new Abstract: The rapid proliferation of AI-powered video generation systems has introduced significant challenges in content moderation, particularly with respect to