Search: “models”

DiffSegLung: Diffusion Radiomic Distillation for Unsupervised Lung Pathology Segmentation

arXiv:2605.11758v1 Announce Type: cross Abstract: Unsupervised segmentation of pulmonary pathologies in CT remains an open challenge due to the absence of annotated multi pathology cohorts and the fai

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Elastic Attention Cores for Scalable Vision Transformers

DGX agent

arXiv:2605.12491v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve strong data-driven scaling by leveraging all-to-all self-attention. However, this flexibility incurs a computational

researcharxiv-cs-cv

13 May 2026

Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance

arXiv:2605.12453v1 Announce Type: cross Abstract: To address the issues of high interruption time and measurement report overhead under user equipment (UE) mobility especially in high speed 5G use cas

applicationsarxiv-cs-lg

Encore: Conditioning Trajectory Forecasting via Biased Ego Rehearsals

arXiv:2605.11463v1 Announce Type: new Abstract: Learning and representing the subjectivities of agents has become a challenging but crucial problem in the trajectory prediction task. Such subjectiviti

agentsarxiv-cs-cv

Enhancing Domain Generalization in 3D Human Pose Estimation through Controllable Generative Augmentation

arXiv:2605.12198v1 Announce Type: new Abstract: Pedestrian motion, due to its causal nature, is strongly influenced by domain gaps arising from discrepancies between training and testing data distribu

EPIC: Efficient Predicate-Guided Inference-Time Control for Compositional Text-to-Image Generation

arXiv:2605.11722v1 Announce Type: new Abstract: Recent text-to-image (T2I) generators can synthesize realistic images, but still struggle with compositional prompts involving multiple objects, counts,

local-aiarxiv-cs-cv

Expected Batch Optimal Transport Plans and Consequences for Flow Matching

arXiv:2605.12174v1 Announce Type: new Abstract: Solving optimal transport (OT) on random minibatches is a common surrogate for exact OT in large-scale learning. In flow matching (FM), this surrogate i

From Observations to States: Latent Time Series Forecasting

arXiv:2602.00297v2 Announce Type: replace Abstract: Deep learning has achieved strong performance in Time Series Forecasting (TSF). However, we identify a critical representation paradox, termed Laten

tutorialsarxiv-cs-lg

GATA2Floor: Graph attention for floor counting in street-view facades

arXiv:2605.11863v1 Announce Type: new Abstract: Automated analysis of building facades from street-level imagery has great potential for urban analytics, energy assessment, and emergency planning. How

Grounding by Remembering: Cross-Scene and In-Scene Memory for 3D Functional Affordances

arXiv:2605.11616v1 Announce Type: new Abstract: Functional affordance grounding requires more than recognizing an object: an agent must localize the specific region that supports an interaction, such

local-aiarxiv-cs-cv

Hindsight Hint Distillation: Scaffolded Reasoning for SWE Agents from CoT-free Answers

arXiv:2605.11556v1 Announce Type: cross Abstract: Solving complex long-horizon tasks requires strong planning and reasoning capabilities. Although datasets with explicit chain-of-thought (CoT) rationa

I implemented NegPip on the Z-image series.

local-air-stablediffusion

NegPip is an extension that enhances negative prompts in Stable Diffusion, making them more effective by allowing negative prompts to have comparable impact to regular prompts. The tool was updated to

IGV-RRT: Prior-Real-Time Observation Fusion for Active Object Search in Changing Environments

arXiv:2603.21887v2 Announce Type: replace Abstract: Object Goal Navigation (ObjectNav) in temporally changing indoor environments is challenging because object relocation can invalidate historical sce

applicationsarxiv-cs-ro

Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning

arXiv:2605.11235v1 Announce Type: new Abstract: In LLM Reinforcement Fine-Tuning (RFT), curriculum learning drives both efficiency and performance. Yet, current methods externalize curriculum judgment

Learning density ratios in causal inference using Bregman-Riesz regression

arXiv:2510.16127v2 Announce Type: replace-cross Abstract: The ratio of two probability density functions is a fundamental quantity that appears in many areas of statistics and machine learning, includ

tutorialsarxiv-cs-lg

Localising Dropout Variance in Twin Networks

arXiv:2507.03622v2 Announce Type: replace Abstract: Accurate individual treatment-effect estimation demands not only reliable point predictions but also uncertainty measures that help practitioners lo

applicationsarxiv-cs-lg

MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining

arXiv:2605.11034v1 Announce Type: cross Abstract: We present MambaNetBurst, a compact tokenizer-free byte-level sequence classifier for network burst classification based on a Mamba-2 backbone. In con

Monitoring access to piped water and sanitation infrastructure in Africa at disaggregated scales using satellite imagery and self-supervised learning

arXiv:2411.19093v4 Announce Type: replace Abstract: Access to drinking water and sanitation services is essential for health and well-being, yet large global disparities persist. Sustainable Developme

MotionGRPO: Overcoming Low Intra-Group Diversity in GRPO-Based Egocentric Motion Recovery

arXiv:2605.05680v2 Announce Type: replace Abstract: This paper studies full-body 3D human motion recovery from head-mounted device signals. Existing diffusion-based methods often rely on global distri

local-aiarxiv-cs-cv

Neural Statistical Functions

arXiv:2605.11327v1 Announce Type: new Abstract: Classical deep learning typically operates on individual cases. Despite its success, real-world usage often requires repeated inference to estimate stat

applicationsarxiv-cs-lg

Not to mention 7 blog posts dropped today, including a new Deep Agents version with significant improvements… Especially excited about the C…

Not to mention 7 blog posts dropped today, including a new Deep Agents version with significant improvements… Especially excited about the Code Interpreter feature which is a sneaky powerful feature e

agentsharrison-chase--x

OmniHumanoid: Streaming Cross-Embodiment Video Generation with Paired-Free Adaptation

arXiv:2605.12038v1 Announce Type: new Abstract: Cross-embodiment video generation aims to transfer motions across different humanoid embodiments, such as human-to-robot and robot-to-robot, enabling sc

Physics-Informed Teacher-Student Ensemble Learning for Traffic State Estimation with a Varying Speed Limit Scenario

arXiv:2605.11346v1 Announce Type: new Abstract: Physics-informed deep learning (PIDL) neural networks have shown their capability as a useful instrument for transportation practitioners in utilizing t

local-aiarxiv-cs-lg

PointGS: Semantic-Consistent Unsupervised 3D Point Cloud Segmentation with 3D Gaussian Splatting

arXiv:2605.11520v1 Announce Type: new Abstract: Unsupervised point cloud segmentation is critical for embodied artificial intelligence and autonomous driving, as it mitigates the prohibitive cost of d

Post-ADC Inference: Valid Inference After Active Data Collection

arXiv:2605.11511v1 Announce Type: cross Abstract: The validity of statistical inference depends critically on how data are collected. When data gathered through active data collection (ADC) are reused

Random-Set Graph Neural Networks

arXiv:2605.11987v1 Announce Type: cross Abstract: Uncertainty quantification has become an important factor in understanding the data representations produced by Graph Neural Networks (GNNs). Despite

agentsarxiv-cs-lg

Read, Extract, Classify: A Tool for Smarter Requirements Engineering

arXiv:2605.11045v1 Announce Type: cross Abstract: This paper presents the ReXCL tool, which automates the extraction and classification processes in requirements engineering, enhancing the software de

Resilient Vision-Tabular Multimodal Learning under Modality Missingness

arXiv:2605.12031v1 Announce Type: cross Abstract: Multimodal deep learning has shown strong potential in medical applications by integrating heterogeneous data sources such as medical images and struc

ReVision: Scaling Computer-Use Agents via Temporal Visual Redundancy Reduction

arXiv:2605.11212v1 Announce Type: new Abstract: Computer-use agents~(CUAs) rely on visual observations of graphical user interfaces, where each screenshot is encoded into a large number of visual toke

researcharxiv-cs-cl

Safety-Oriented Evaluation of Language Understanding Systems for Air Traffic Control

arXiv:2605.11769v1 Announce Type: new Abstract: Air Traffic Control (ATC) is a safety-critical domain in which incorrect interpretation of instructions may lead to severe operational consequences. Whi

safetyarxiv-cs-cl

Seeing the Needle in the Haystack: Towards Weakly-Supervised Log Instance Anomaly Localization via Counterfactual Perturbation

arXiv:2605.10988v1 Announce Type: new Abstract: Log anomaly detection is a critical task for system operations and security assurance. However, in networked systems at scale, log data are generated at

local-aiarxiv-cs-lg

ShardTensor: Domain Parallelism for Scientific Machine Learning

arXiv:2605.11111v1 Announce Type: cross Abstract: Scientific Machine Learning (SciML) faces unique challenges for extreme-resolution data, with mitigations that often fail to scale or degrade the accu

Simulation-Ready Cluttered Scene Estimation via Physics-aware Joint Shape and Pose Optimization

arXiv:2602.20150v2 Announce Type: replace-cross Abstract: Estimating simulation-ready scenes from real-world observations is crucial for downstream planning and policy learning tasks. Regretfully, exi

SkillGen: Verified Inference-Time Agent Skill Synthesis

arXiv:2605.10999v1 Announce Type: new Abstract: Skills are a promising way to improve LLM agent capabilities without retraining, while keeping the added procedure reusable and controllable. However, h

agentsarxiv-cs-lg

Spectral-Adaptive Modulation Networks for Visual Perception

arXiv:2503.23947v2 Announce Type: replace Abstract: Recent studies have shown that 2D convolution and self-attention exhibit distinct spectral behaviors, and optimizing their spectral properties can e

Trust the Batch, On- or Off-Policy: Adaptive Policy Optimization for RL Post-Training

arXiv:2605.12380v1 Announce Type: new Abstract: Reinforcement learning is structurally harder than supervised learning because the policy changes the data distribution it learns from. The resulting fr

UGround: Towards Unified Visual Grounding with Unrolled Transformers

arXiv:2510.03853v4 Announce Type: replace Abstract: We present UGround, a extbf{U}nified visual extbf{Ground}ing paradigm that dynamically selects intermediate layers across extbf{U}nrolled transforme

USEMA: a Scalable Efficient Mamba Like Attention for Medical Image Segmentation

arXiv:2605.11131v1 Announce Type: new Abstract: Accurate medical image segmentation is an integral part of the medical image analysis pipeline that requires the ability to merge local and global infor

When and How to Canonize: A Generalization Perspective

arXiv:2605.11008v1 Announce Type: new Abstract: While invariant architectures are standard for processing symmetric data, there is growing interest in achieving invariance by applying group averaging

tutorialsarxiv-cs-lg

When Brains Disagree: Biological Ambiguity Underlies the Challenge of Amyloid PET Synthesis from Structural MRI

arXiv:2605.11867v1 Announce Type: new Abstract: Structural MRI-to-amyloid PET synthesis has been proposed as a non-invasive alternative for amyloid assessment in Alzheimer's disease (AD). However, rep

When the Gold Standard Isn't Necessarily Standard: Challenges of Evaluating the Translation of User-Generated Content

arXiv:2512.17738v2 Announce Type: replace Abstract: User-generated content (UGC) is characterised by frequent use of non-standard language, from spelling errors to expressive choices such as slang, ch

researcharxiv-cs-cl

4D Neural Voxel Splatting: Dynamic Scene Rendering with Voxelized Guassian Splatting

arXiv:2511.00560v2 Announce Type: replace Abstract: Although 3D Gaussian Splatting (3D-GS) achieves efficient rendering for novel view synthesis, extending it to dynamic scenes still results in substa

A Cold Diffusion Approach for Percussive Dereverberation

arXiv:2605.10256v1 Announce Type: cross Abstract: Most recent advances in audio dereverberation focus almost exclusively on speech, leaving percussive and drum signals largely unexplored despite their

applicationsarxiv-cs-ai

A Market-Rule-Informed Neural Network for Efficient Imbalance Electricity Price Forecasting

arXiv:2605.09061v1 Announce Type: cross Abstract: Accurate and efficient imbalance electricity price forecasting is critical for industrial energy trading systems, especially as battery assets and aut

A probabilistic framework for crystal structure denoising, phase classification, and order parameters

arXiv:2512.11077v3 Announce Type: replace-cross Abstract: Atomistic simulations generate large volumes of noisy structural data, yet extracting phase labels and continuous order parameters (OPs) in a

local-aiarxiv-cs-ai

Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights

arXiv:2605.10654v1 Announce Type: cross Abstract: We consider the active learning problem where the goal is to learn an unknown function with low prediction error under an unknown Boltzmann distributi

tutorialsarxiv-cs-ai

Active-SAOOD: Active Sparsely Annotated Oriented Object Detection in Remote Sensing Images

arXiv:2605.10162v1 Announce Type: new Abstract: Reducing the annotation cost of oriented object detection in remote sensing remains a major challenge. Recently, sparse annotation has gained attention

Adaptive Context Matters: Towards Provable Multi-Modality Guidance for Super-Resolution

arXiv:2605.10470v1 Announce Type: new Abstract: Super-resolution (SR) is a severely ill-posed problem with inherent ambiguity, as widely recognized in both empirical and theoretical studies. Although