Search: “framework”

NegROI: Click-Centric Uncertainty-Guided Refinement with Scene-Conditioned Negative Prompts for Robust Interactive 3D Segmentation

arXiv:2607.05955v1 Announce Type: cross Abstract: Interactive 3D segmentation aims to extract object masks in point clouds with minimal user clicks. Despite recent progress, most existing approaches s

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Local Ai

NumGrad-Pull: Numerical Gradient Guided Tri-plane Representation for Surface Reconstruction from Point Clouds

DGX agent

arXiv:2411.17392v3 Announce Type: replace Abstract: Reconstructing continuous surfaces from unoriented and unordered 3D points is a fundamental challenge in computer vision and graphics. Recent advanc

local-aiarxiv-cs-cv

8 Jul 2026

O3N: Omnidirectional Open-Vocabulary Occupancy Prediction

arXiv:2603.12144v2 Announce Type: replace Abstract: Understanding and reconstructing the 3D world through omnidirectional perception is becoming increasingly important for autonomous agents and embodi

Observation Quality Matters: Robust Multi-Fisheye Calibration via Failure-Oriented Analysis

arXiv:2607.05777v1 Announce Type: new Abstract: Reliable calibration of multi-fisheye camera systems remains challenging as rig size, camera arrangement diversity, and field of view increase. Existing

applicationsarxiv-cs-ro

On the Redundancy of Timestep Embeddings in Diffusion Models

arXiv:2606.20416v2 Announce Type: replace-cross Abstract: Diffusion models rely heavily on explicit timestep embeddings to modulate the denoising process across various noise scales. In this work, we

OpenGround: Planning-based Online Perception for Open-World 3D Visual Grounding

arXiv:2512.23020v3 Announce Type: replace-cross Abstract: 3D visual grounding aims to locate objects based on natural language descriptions in 3D scenes. Existing supervised methods are limited by gen

Optimized Adaptive Loop Filter in Versatile Video Coding

model-releasesarxiv-cs-cv

arXiv:2607.05737v1 Announce Type: new Abstract: In the Versatile Video Coding~(VVC) standard, adaptive loop filter~(ALF), including Geometry transformation-based Adaptive Loop Filter~(GALF) and Cross

Orthogonal Dendritic Intrinsic Networks: An Architecture for Significance-Ordered, Orthogonal Latent Spaces

arXiv:2607.05653v1 Announce Type: new Abstract: Principal Component Analysis or PCA-like properties (orthogonality, variance ranking) are seldom realized in deep autoencoder architectures. In this wor

applicationsarxiv-cs-lg

Partial Symmetry Detection for 3D Geometry using Contrastive Learning with Geodesic Point Cloud Patches

model-releasesarxiv-cs-cv

arXiv:2312.08230v2 Announce Type: replace Abstract: Detecting partial extrinsic symmetry in 3D geometry is a fundamental yet persistent challenge in computer vision and graphics, critical for tasks ra

PhyMRI-SR: Toward Physics-Aware MRI Image Super-Resolution

arXiv:2607.06238v1 Announce Type: new Abstract: Magnetic resonance imaging (MRI) super-resolution is vital for improving diagnostic accessibility, yet most methods treat it as a deterministic mapping

applicationsarxiv-cs-cv

PluraMath: Extending Mathematical Reasoning Evaluation Beyond High-Resource Languages

arXiv:2607.05992v1 Announce Type: cross Abstract: Mathematical reasoning has become a central task for evaluating and tuning reasoning Large Language Models (LLMs), yet existing benchmarks remain heav

Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation

arXiv:2607.06516v1 Announce Type: new Abstract: Evaluating end-to-end autonomous driving (E2E-AD) remains challenging, as existing driving simulation methods often trade off closed-loop interactivity

agentsarxiv-cs-cv

PolyWorkBench: Benchmarking Multilingual Long-Horizon LLM Agents

arXiv:2607.06008v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong performance in long-horizon tasks that require planning, tool use, and interaction with external env

Privilege and confidentiality in generative AI workflows

arXiv:2607.05479v1 Announce Type: cross Abstract: Generative AI (GenAI) systems store and process client data in three distinct ways: in the model's parameters through training and memorisation, in th

Progressive Reasoning with Primitive Correction for Compositional Zero-Shot Learning

arXiv:2607.05911v1 Announce Type: new Abstract: Compositional Zero-Shot Learning (CZSL) aims to combine known attributes and objects as primitives for recognizing previously unseen attribute-object pa

PVCap: Towards Accurate 3D Dense Captioning via PseudoCap and VoxelCapNet

arXiv:2607.06097v1 Announce Type: cross Abstract: 3D dense captioning, an emerging vision-language task, aims to generate descriptive sentences for each object in the 3D scene. Despite the impressive

Quantitative Gaussian-Process limits of Tensor Programs

arXiv:2607.06290v1 Announce Type: new Abstract: We study the infinite-width Gaussian-process limit of random neural networks through the lens of tensor programs, and we provide a quantitative converge

researcharxiv-cs-lg

Recovering Cloud Microstructures with Cascaded Diffusion Inversion

arXiv:2607.05637v1 Announce Type: new Abstract: High-resolution satellite imagery is critical for observing fine-scale cloud structures that inform weather modification strategies like cloud seeding f

Rendering-Aware Bayesian 3D Gaussian Splatting with Native Uncertainty and Adaptive Complexity Control

arXiv:2607.05522v1 Announce Type: cross Abstract: 3D Gaussian splatting (3DGS) is a strong representation for real-time novel-view synthesis, but its standard training pipeline relies on point estimat

Rethinking Visual Autoregressive Sampling with Information-Grounding Guidance

arXiv:2509.23876v3 Announce Type: replace-cross Abstract: Autoregressive (AR) models based on next-scale prediction have emerged as a powerful tool for image generation, but they face a critical weakn

Reward as An Agent for Embodied World Models

arXiv:2606.19990v2 Announce Type: replace Abstract: While RL has become a promising tool for refining world models, existing methods largely rely on conservative rollouts near the training distributio

agentsarxiv-cs-ai

RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes

arXiv:2601.05249v3 Announce Type: replace Abstract: Nighttime color constancy still remains a challenging problem in computational photography due to low-light noise and complex illumination condition

RoboTALES: Learning Reasoning-Guided Robot Policies via Task-Aligned Simulated Futures

arXiv:2607.06018v1 Announce Type: new Abstract: Pretrained video generative models are promising backbones for visuomotor control, but their imagined futures often drift from task intent and are not r

safetyarxiv-cs-ro

RoboVAST: Automated Scenario-Based Validation of Robots at Scale

arXiv:2607.06248v1 Announce Type: new Abstract: Validation of robotic systems critically depends on the operating conditions under which they are assessed. Scenario selection and variation are often m

researcharxiv-cs-ro

RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation

arXiv:2607.06527v1 Announce Type: cross Abstract: Multi-hop Question Answering over Knowledge Graphs faces a critical challenge: traditional retrieve-then-read pipelines break differentiability, preve

RT @cvmilo00: tbf this is one of the best repos on github, specially if you are REALLY into AI

This post references a notable GitHub repository that the commenter considers particularly valuable for those with a serious interest in AI development. The tweet appears to be a recommendation or end

agentsharrison-chase--x

Hardware

RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation

arXiv:2607.06558v1 Announce Type: new Abstract: Scaling robot learning requires massive, diverse trajectory data, yet collection is currently bottlenecked by physical teleoperation, where every demons

hardwarearxiv-cs-ro

SafeImpute: Reliable Clinical Data Imputation via Conformal Selection

model-releasesarxiv-cs-lg

arXiv:2607.05613v1 Announce Type: new Abstract: Clinical care often relies on key laboratory indicators, yet real-world patient visits are sparse and tests are ordered irregularly, leading to pervasiv

SCOReD: Student-Aware CoT Optimization for Recommendation Distillation

arXiv:2607.05734v1 Announce Type: cross Abstract: Chain-of-thought (CoT) distillation in the recommendation domain is a necessary precursor to RL training, but raw teacher traces are ill-suited to thi

Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding

arXiv:2607.06132v1 Announce Type: cross Abstract: Multi-Pool Chemical Exchange Saturation Transfer (CEST) MRI provides valuable metabolic information but is clinically limited by long acquisition time

Signed-Graph Recommendation as Structural Consistency Maximization

arXiv:2607.05952v1 Announce Type: cross Abstract: While signed social recommendation has shown great potential by modeling both trust and distrust relations, its effectiveness is often hindered by str

Social 3D Scene Graphs: Modeling Human Actions and Relations for Interactive Service Robots

model-releasesarxiv-cs-cv

arXiv:2509.24966v2 Announce Type: replace Abstract: Understanding how people interact with their surroundings and each other is essential for enabling robots to act in socially compliant and context-a

SpanUQ: Span-Level Uncertainty Quantification for Large Language Model Generation

model-releasesarxiv-cs-cl

arXiv:2607.05721v1 Announce Type: new Abstract: Uncertainty estimation is essential not only for the trustworthy deployment of large language models (LLMs) but also as a foundation for self-refinement

SparseCtrl-HOI: Sparse Temporal Control for Human-Object Interaction Video Generation

arXiv:2607.05994v1 Announce Type: new Abstract: Human-Object Interaction (HOI) video generation aims to synthesize realistic videos of humans manipulating diverse objects, serving as a promising avenu

SpatialFly: Implicit 3D Prior-Guided Visual Reparameterization for Continuous UAV Vision-and-Language Navigation

arXiv:2603.21046v2 Announce Type: replace-cross Abstract: UAVs play an important role in applications such as autonomous exploration, disaster response, and infrastructure inspection. However, UAV VLN

safetyarxiv-cs-ai

SSA-3DGS: Unsupervised Removal of Screen-Space Artifacts for 3D Gaussian Splatting

arXiv:2607.05598v1 Announce Type: cross Abstract: Novel View Synthesis (NVS) methods, such as 3D Gaussian Splatting (3DGS), rely heavily on the assumption of clean, multi-view consistent, posed input

applicationsarxiv-cs-cv

Statistically Meaningful Geometry and Gauge Symmetry Breaking: A Geometric Foundation for Scientific Discovery and Intelligence Emergence

model-releasesarxiv-cs-lg

arXiv:2607.05436v1 Announce Type: new Abstract: The rapid scaling of over-parameterized machine learning architectures, particularly LLMs, raises a profound crisis: do these systems exhibit genuine in

Superman: Unifying Skeleton and Vision for Human Motion Perception and Generation

arXiv:2602.02401v2 Announce Type: replace Abstract: Human motion analysis tasks, such as temporal 3D pose estimation, motion prediction, and motion in-betweening, play an essential role in computer vi

Supervised Reward Inference

model-releasesarxiv-cs-lg

arXiv:2502.18447v2 Announce Type: replace Abstract: Existing approaches to reward inference typically assume that humans provide demonstrations according to specific behavior models. However, humans o

Hardware

SUSE, NVIDIA, and Vultr Simplify the Path from AI Pilots to Production

SUSE, NVIDIA, and Vultr have partnered to create a streamlined solution for deploying AI applications from pilot phase to production environments. The collaboration leverages SUSE's AI Factory framewo

hardwarevultr

Synthetic-to-Real Translation for Class-Agnostic Motion Prediction

arXiv:2607.06319v1 Announce Type: new Abstract: Motion understanding is critical for ensuring safety and robustness in autonomous driving systems, driving increasing interest in motion prediction. A k

Task Decomposition-Guided Reranking for Adaptive Agent Skill Retrieval

arXiv:2607.06283v1 Announce Type: new Abstract: Skill usage can significantly enhance the ability of modern agent systems to complete complex tasks. However, the growing scale of skill libraries makes

agentsarxiv-cs-ai

The GenAI Skill Bypass: Mapping Divergent Pathways of University Students and Staff AI Literacy

arXiv:2607.05411v1 Announce Type: cross Abstract: Higher education institutions are increasingly expected to ensure that both students and staff develop Generative AI (GenAI) literacies. In response,

applicationsarxiv-cs-ai

Thor: Towards Human-Level Whole-Body Reactions for Intense Contact-Rich Environments

arXiv:2510.26280v3 Announce Type: replace Abstract: Humanoids hold great potential for service, industrial, and rescue applications, in which robots must sustain whole-body stability while performing

applicationsarxiv-cs-ro

ThorArena: Benchmarking Humanoid Physical Interaction with Human Motion-Force Demonstrations

model-releasesarxiv-cs-ro

arXiv:2607.06052v1 Announce Type: new Abstract: Humanoid robots are increasingly expected to perform contact-rich tasks that require not only accurate whole-body motion but also robust physical intera

TMF-RSE: Tri-Modal Fusion with Regional Semantics and Evidential Uncertainty for Lung Severity Scoring

arXiv:2607.06356v1 Announce Type: cross Abstract: Accurate quantification of lung disease severity from chest imaging is critical for clinical decision-making and resource allocation. We propose a tri

To Retain or to Adapt? Generalizing Continual Learning

arXiv:2607.05609v1 Announce Type: cross Abstract: The Continual Learning (CL) literature has long been driven by the goal of mitigating catastrophic forgetting. This objective rests on a pervasive, of

safetyarxiv-cs-ai

TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting

arXiv:2607.06349v1 Announce Type: new Abstract: Building sensors are embedded in physical topology, spatial hierarchy, and operational context, yet existing forecasters often treat them as isolated ti

agentsarxiv-cs-ai