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No Subspace to Track: Non-Identifiability and Optimizer State in Low-Rank Training

arXiv:2607.05872v1 Announce Type: new Abstract: Memory-efficient optimizers such as GaLore train large language models by projecting gradients onto a rank-r subspace recomputed every T steps, assuming

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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

safetyarxiv-cs-cv

OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations

arXiv:2607.06007v1 Announce Type: new Abstract: Pixel-level annotation remains a major bottleneck in medical image segmentation, making weak supervision an attractive yet under-constrained alternative

safetyarxiv-cs-cv

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

Omni-RRM: Advancing Omni Reward Modeling via Automatic Rubric-Grounded Preference Synthesis

model-releasesarxiv-cs-cl

arXiv:2602.00846v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) struggle with alignment due to the limitations of existing reward models (RMs), which are predominantly vis

On the Condition Number Upper Bound of the L-BFGS Inverse Hessian Approximation Matrix with a Two-Sided Geometric Envelope Safeguarding Mechanism

arXiv:2607.05836v1 Announce Type: cross Abstract: The limited-memory BFGS (L-BFGS) algorithm is a cornerstone of large-scale optimization due to its linear memory and computational costs. However, in

On the convergence of graph Laplacians with a symmetric divergence

arXiv:2607.05892v1 Announce Type: cross Abstract: When analyzing a manifold learning algorithm for data lying on a smooth, compact, connected Riemannian submanifold (M, g) of R^d, a key estimate for t

On the feasibility of dependency parsing of non-human sequences without a gold standard. Is evaluation possible in other species?

arXiv:2607.06542v1 Announce Type: new Abstract: Dependency parsing consists of finding a tree representation for a sequence. Unsupervised dependency parsing aims to develop parsing methods without a g

researcharxiv-cs-cl

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

researcharxiv-cs-cv

Onnes: A Physics-Grounded Multi-Agent LLM Simulator for Cryogenic Fault Diagnosis in Quantum Computing Infrastructure

arXiv:2607.05805v1 Announce Type: new Abstract: Dilution refrigerators are the enabling infrastructure of superconducting quantum computers, yet their fault diagnosis is still dominated by threshold a

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

Optimal Transport Q-Learning for Flow Policy Steering and Acceleration

arXiv:2607.06262v1 Announce Type: new Abstract: Diffusion and flow policies have recently demonstrated remarkable performance in robotic applications by accurately capturing multimodal robot trajector

safetyarxiv-cs-ro

Optimized Adaptive Loop Filter in Versatile Video Coding

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

OrchardBench: A Physically-Grounded, GPU-Parallel Apple-Orchard Simulation Benchmark for Agricultural Robotics

arXiv:2607.06337v1 Announce Type: cross Abstract: Robotic tree-fruit harvesting is a flagship problem for agricultural automation, but progress is bottlenecked by the cost and irreproducibility of fie

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

Parameter-Free Encoders Remain Viable for RDB Foundation Models

model-releasesarxiv-cs-lg

arXiv:2607.05476v1 Announce Type: new Abstract: Given a relational database (RDB) storing heterogeneous tabular information, how can we predict missing (or future) values in some target column of inte

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

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

Local Ai

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment

arXiv:2607.05605v1 Announce Type: new Abstract: With the rapid advancement of image generation technologies, perceptual quality assessment of AI-generated images has emerged as a crucial research dire

local-aiarxiv-cs-cv

PatchOptic for Shared-State LLM Workflows with Projected Views and Verified Structured Updates

arXiv:2607.05483v1 Announce Type: cross Abstract: Agentic workflows often operate over shared, structured state. Because LLM context windows are limited, each model invocation is typically shown only

PCBWorld: A Benchmark Environment for Engine-Grounded PCB Design Automation

arXiv:2607.05915v1 Announce Type: new Abstract: PCB routing is the task of connecting the nets of a board with copper traces under strict design rules, yet learning-based methods still lag behind rule

Perceptually Aligning Representations of Music via Noise-Augmented Autoencoders

arXiv:2511.05350v3 Announce Type: replace-cross Abstract: We argue that training autoencoders to reconstruct inputs from noised versions of their encodings, when combined with perceptually motivated l

Performance Optimization and Comparative Analysis of Generative AI Models on Advanced Accelerators

arXiv:2607.05400v1 Announce Type: cross Abstract: Generative AI models, such as Large Language Models (LLMs) and diffusion models, have demonstrated impressive performance across a wide range of tasks

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

Physics-Informed Neural Embeddings of PDE Solution Families

arXiv:2607.06348v1 Announce Type: new Abstract: We introduce a physics-informed framework for learning finite-dimensional embeddings of solution families of partial differential equations. The method

Local Ai

Physics-Regularized Machine Learning for Proprioceptive Vehicle Localization Using Onboard Sensors

arXiv:2607.05663v1 Announce Type: cross Abstract: Accurate and robust localization is essential for autonomous mobility systems in real-world environments. While fusing Inertial Measurement Unit (IMU)

local-aiarxiv-cs-ai

PIPBench: A Profile-Inclusive Framework for Personalized Image Generation Evaluation

arXiv:2607.06440v1 Announce Type: new Abstract: Recent text-to-image models such as DALLE-3 excel at following diverse prompts yet remain blind to individual aesthetic preferences. We study personaliz

Pitwall: Faithful Natural-Language Race-Strategy Briefings from a Calibrated Real-Time Monte Carlo Engine

arXiv:2607.06495v1 Announce Type: cross Abstract: Live sports commentary is grounded generation under a deadline: statements concern real, named athletes, the grounding state changes every few seconds

applicationsarxiv-cs-ai

Plainbook: Data Science, in Plain Language

arXiv:2607.05717v1 Announce Type: cross Abstract: Jupyter Notebooks have become widely adopted in data science, as they allow the sharing of reproducible computational analysis. They are, however, acc

Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty?

arXiv:2508.01109v3 Announce Type: replace Abstract: We investigate whether socioeconomic indicators, like household wealth, leave recoverable informational imprints in both satellite imagery (capturin

Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability

model-releasesarxiv-cs-cl

arXiv:2607.06196v1 Announce Type: new Abstract: Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional law

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

PolicyShiftGuard: Benchmarking and Improving Policy-Adaptive Image Guardrails

arXiv:2607.05910v1 Announce Type: cross Abstract: Image guardrails are typically trained and evaluated under a fixed safety policy, implicitly treating safety as an intrinsic property of an image. Rea

PolyJarvis: An LLM-Orchestrated Agent for Automated All-Atom Molecular Dynamics of Amorphous Homopolymers

arXiv:2604.02537v2 Announce Type: replace Abstract: All-atom molecular dynamics (MD) simulations can predict polymer properties from molecular structure, yet their execution requires specialized exper

agentsarxiv-cs-cl

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

Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical Analysis

model-releasesarxiv-cs-cl

arXiv:2607.05626v1 Announce Type: new Abstract: Background: Depression frequently co-occurs with ADHD and autism spectrum disorder (ASD), but population-level differences in symptom expression between

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models

arXiv:2607.05441v1 Announce Type: cross Abstract: Integrating external tools with Large Language Models (LLMs) has emerged as a promising paradigm for accomplishing complex tasks. Since LLMs still str

Position: EU AI Act's Research Exemptions Can Break the Publication Norms of Major AI Conferences

arXiv:2506.03218v2 Announce Type: replace-cross Abstract: The EU has become one of the vanguards in regulating the digital age. A particularly important regulation in the Artificial Intelligence (AI)

Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety

arXiv:2607.05407v1 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems present profound new risks to child safety. AI is increasingly being misused to create AI-generated child

Prior-First, Condition-Second: Scalable and Controllable Hand Motion Completion

arXiv:2607.05938v1 Announce Type: cross Abstract: Synthesizing hand motion that matches the full body motion and the semantic labels is a difficult task due to their high degrees of freedom and the la

applicationsarxiv-cs-ro

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

Tutorials

Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps

arXiv:2512.17143v3 Announce Type: replace Abstract: Photographs of people taken by professional photographers typically present the person in beautiful lighting, with an interesting pose, and flatteri

tutorialsarxiv-cs-cv

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

researcharxiv-cs-cv

Prompt-Adapter Context Routing for Parameter-Efficient Multi-Shot Long Video Extrapolation

arXiv:2607.06481v1 Announce Type: cross Abstract: We present PACR-Video, a parameter-efficient framework for multi-shot long video extrapolation that preserves recurring entities, scene structure, vis

Prompt Coach: An Empirical Evaluation of an Agentic Tutor for Learning Prompt Engineering in Software Development

arXiv:2607.06074v1 Announce Type: cross Abstract: Prompt engineering has emerged as a critical yet undertaught skill for software developers, one that traditional learning approaches are ill-equipped

agentsarxiv-cs-ai

Prompt Robustness Is Task-Dependent: Comparing Objective and Belief-Style Questions in LLM Evaluation

arXiv:2607.05554v1 Announce Type: cross Abstract: Survey-style evaluations of large language models often treat a prompted response as a measure of a model's values or beliefs. This assumption is part

Prompt-to-Paper: Agentic AI System for Bioinformatics

arXiv:2607.05456v1 Announce Type: new Abstract: While recent advances in large language models have enabled end-to-end automated manuscript generation, existing systems suffer from three critical defi

agentsarxiv-cs-ai