Search: “models”

The Topological Dual of a Dataset: A Logic-to-Topology Encoding for AlphaGeometry-Style Data

arXiv:2604.18050v2 Announce Type: replace Abstract: AlphaGeometry represents a milestone in neuro-symbolic reasoning, yet its architecture faces a log-linear scaling bottleneck within its symbolic ded

researcharxiv-cs-ai

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Topological Neural Operators

DGX agent

arXiv:2606.09806v1 Announce Type: cross Abstract: We introduce Topological Neural Operators (TNOs), a principled framework for operator learning on cell complexes that lifts neural operators (NOs) fro

researcharxiv-cs-ai

9 Jun 2026

Toward Scalable Co-located Practical Learning: Assisting with Computer Vision and Multimodal Analytics

arXiv:2603.13679v2 Announce Type: replace-cross Abstract: Co-located practical learning leaves evidence in visible actions around patients, task resources and room zones, but these traces are often re

Hardware

Towards Automated Kernel Generation in the Era of LLMs

arXiv:2601.15727v3 Announce Type: replace Abstract: The performance of modern AI systems is fundamentally constrained by the quality of their underlying GPU kernels, which translate high-level algorit

hardwarearxiv-cs-lg

Trajectory Geometry of Transformer Representations Across Layers

arXiv:2606.09287v1 Announce Type: new Abstract: Understanding how transformer representations evolve across layers, not merely what they encode, remains an open problem in mechanistic interpretability

UniADC: A Unified Framework for Anomaly Detection and Classification

arXiv:2511.06644v3 Announce Type: replace Abstract: In this paper, we introduce a novel task termed unified anomaly detection and classification, which aims to simultaneously detect anomalous regions

Vessel Traffic Flow Prediction on Sparse Data via Spatio-Temporal Graph Neural Networks with a Learnable Tweedie Head

arXiv:2606.07694v1 Announce Type: new Abstract: Accurate vessel traffic flow prediction is crucial for smart port operations and navigational safety. However, maritime traffic flow data are often high

Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision

arXiv:2606.09670v1 Announce Type: cross Abstract: Recent Anomaly Detection methods achieve perfect detection and segmentation scores on well-established datasets, such as MVTec. However, many of these

applicationsarxiv-cs-ai

WaveDiT: Distribution-Aware Wavelet Flow Matching for Efficient 3D Brain MRI Synthesis

arXiv:2606.08670v1 Announce Type: new Abstract: Large and demographically balanced datasets are essential for reliable neuroimaging biomarkers. Full-resolution 3D brain MRI synthesis can support data

safetyarxiv-cs-cv

Wedge Sampling: Efficient Tensor Completion with Nearly-Linear Sample Complexity

arXiv:2602.05869v2 Announce Type: replace-cross Abstract: We introduce Wedge Sampling, a new non-adaptive sampling scheme for low-rank tensor completion. We study recovery of an order-k low-rank tenso

Tutorials

A Mechanism-Coupled Split Window Network for Medium- to High-Resolution Land Surface Temperature Retrieval

arXiv:2509.04991v2 Announce Type: replace-cross Abstract: Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate process

tutorialsarxiv-cs-ai

Ablation Study of Block Size, Weight Precision, and Scale Precision in NVFP4 Inference for Low-Power Edge-Efficient Neural Networks

arXiv:2606.06527v1 Announce Type: cross Abstract: Energy-efficient edge inference requires reducing arithmetic cost, memory traffic, and hardware overhead. This paper presents an ablation-focused stud

Amortized Neural Optimization for Pre-Layout Signal Integrity Design Space Exploration using Differentiable Surrogates

arXiv:2606.07463v1 Announce Type: cross Abstract: Pre-layout design space exploration (DSE) for high-speed signal integrity (SI) analysis is often limited by the computational cost of simulations and

An Adaptive Data cleaning Framework for Noisy Label Detection

arXiv:2606.07086v1 Announce Type: new Abstract: Deep neural networks (DNNs) excel in computer vision tasks given large annotated datasets. In real-world applications, however, labels are often corrupt

applicationsarxiv-cs-cv

Architecture-Adaptive Uncertainty Fusion for Deepfake Detection

arXiv:2606.06666v1 Announce Type: new Abstract: Deepfake detection systems achieve near-perfect accuracy on benchmarks, yet forensic deployment demands reliable prediction uncertainty. Existing uncert

Bias in Filter Feature Selection Evaluation: A Meta-Analysis of Datasets, Baselines, and Experimental Design Choices

arXiv:2606.07068v1 Announce Type: new Abstract: Background: Since 1990 many feature selection methods have been proposed across heterogeneous applications. To validate the usefulness of a new method,

Bounded-Abstention Pairwise Learning to Rank

arXiv:2505.23437v2 Announce Type: replace-cross Abstract: Ranking systems influence decision-making in high-stakes domains like health, education, and employment, where they can have substantial econo

Breaking the Ice: Analyzing Cold Start Latency in vLLM

arXiv:2606.07362v1 Announce Type: new Abstract: As scalable inference services become popular, the cold start latency of an inference engine becomes important. Today, vLLM has evolved into the de fact

CHDP: Cooperative Hybrid Diffusion Policies for Reinforcement Learning in Parameterized Action Space

arXiv:2601.05675v2 Announce Type: replace Abstract: Hybrid action space, which combines discrete choices and continuous parameters, is prevalent in domains such as robot control and game AI. However,

Consistency-Preserving Diverse Video Generation

arXiv:2602.15287v2 Announce Type: replace Abstract: Text-to-video generation is expensive, so only a few samples are typically produced per prompt. In this low-sample regime, maximizing the value of e

DIFFRACT: Neuralized Utility Maximization for Wireless Networks by Differentiable Programming

arXiv:2606.07114v1 Announce Type: cross Abstract: Next-generation wireless networks, including satellite-to-Open RAN systems, demand agile and intelligent resource management capable of handling dynam

researcharxiv-cs-ai

Discovering Multiscale Deep Formulas in Complex Systems via Neural-Guided Lambda Calculus

arXiv:2606.07426v1 Announce Type: new Abstract: A fundamental problem in science is identifying underlying patterns of complex systems in the form of concise mathematical formulas. Current Artificial

Enhancing Conformal Prediction via Class Similarity

arXiv:2511.19359v2 Announce Type: replace Abstract: Conformal Prediction (CP) has emerged as a powerful statistical framework for high-stakes classification applications. Instead of predicting a singl

Hardware

FP8 is All You Need (Part 1): Debunking Hardware FP64 as the HPC Holy Grail

arXiv:2606.06510v1 Announce Type: cross Abstract: Conventional HPC dogma holds that native hardware FP64 silicon is the irreducible foundation of scientific computing -- the 'holy grail' of double-pre

hardwarearxiv-cs-ai

From Pixels to Newtons: Predicting In Vivo Joint Contact Forces from Monocular Video

arXiv:2606.06631v1 Announce Type: new Abstract: Joint contact forces govern implant longevity, cartilage health, and rehabilitation outcomes, shaping who develops osteoarthritis, who recovers well fro

Agents

From Pixels to Shelf: An Integrated Robotic System for Autonomous Supermarket Stocking with a Mobile Manipulator

arXiv:2509.11740v2 Announce Type: replace Abstract: Autonomous stocking in retail environments, particularly supermarkets, presents challenges due to dynamic human interactions, constrained spaces, an

agentsarxiv-cs-ro

Geodesics of Dynamic Graphs for Regime Change Detection

arXiv:2606.07151v1 Announce Type: new Abstract: Traditional change point detection in dynamic networks assumes abrupt transitions between stationary states, overlooking scenarios of continuous evoluti

applicationsarxiv-cs-lg

GRASP: Geometry-aware Residual Alignment for Scalable Pretraining Data Attribution

arXiv:2606.06892v1 Announce Type: new Abstract: Scalable data attribution methods typically assign isolated utility scores to individual training examples. This prevalent additive assumption fundament

Mind the Gap: Bridging Behavioral Silos with LLMs in Multi-Vertical Recommendations

arXiv:2606.06779v1 Announce Type: cross Abstract: In multi-vertical e-commerce platforms like DoorDash, relatively newer product verticals such as grocery and retail present a significant opportunity

applicationsarxiv-cs-ai

Mitosis Detection in the Wild: Multi-Tumor and Context-Aware Generalization in the MIDOG 2025 Challenge

arXiv:2606.07368v1 Announce Type: cross Abstract: Automated mitosis detection is a well-established task in computational pathology. While previous benchmarks focused on scanner-induced domain shift,

applicationsarxiv-cs-ai

Multi-Scale Feature Attention Network for Polymer Classification using THz Dual-Comb Spectroscopy

arXiv:2606.06554v1 Announce Type: cross Abstract: Reliable polymer identification is essential for ensuring the quality and safety of recycled plastics, yet conventional sorting and spectroscopic tech

Hardware

MVSegNet: A Lightweight Boundary-Aware Network for Fetal Lateral Ventricle Segmentation and Atrial Width Estimation in Prenatal Ultrasound

arXiv:2606.06958v1 Announce Type: new Abstract: Fetal ventriculomegaly is assessed by measuring the atrial width of the lateral ventricle in prenatal ultrasound. Accurate segmentation is essential for

hardwarearxiv-cs-cv

Agents

On the Hardness of Optimal Motion on Trees

arXiv:2606.06686v1 Announce Type: new Abstract: This paper presents a simple framework that settles the complexity of Multi-Agent Path Finding (MAPF) on trees across standard objectives--distance, mak

agentsarxiv-cs-ro

Agents

OpenSkill: Open-World Self-Evolution for LLM Agents

arXiv:2606.06741v1 Announce Type: new Abstract: Self-evolving agents requires adaptation after deployment, but existing approaches assume a usable learning loop, such as curated skills, successful tra

agentsarxiv-cs-ai

Privacy Implies Stability: Information-Theoretic Generalization Bounds for Quantum Learning

arXiv:2602.01177v3 Announce Type: replace-cross Abstract: We develop an information-theoretic framework connecting stability, privacy, and generalization for quantum learning algorithms. Learning proc

Reconstructing Multi-Decadal Forest Disturbances: A Spatio-Temporal Transformer Approach

arXiv:2606.07249v1 Announce Type: new Abstract: Accurate monitoring of forest disturbances is essential for understanding carbon dynamics and land management, yet traditional approaches typically rely

Shield-Loco: Shielding Locomotion Policies with Predictive Safety Filtering

arXiv:2606.07193v1 Announce Type: new Abstract: Reinforcement learning (RL) policies enable dynamic legged locomotion but lack mechanisms to avoid violations of safety constraints that are absent duri

safetyarxiv-cs-ro

SlimSearcher: Training Efficiency-Aware Web Agents via Adaptive Reward Gating

arXiv:2606.07074v1 Announce Type: cross Abstract: Deep research agents have demonstrated remarkable capabilities in complex information-seeking tasks, yet this power comes at a steep computational cos

Spatiotemporal Imputation with Graph-Informed Flow Matching

arXiv:2606.06682v1 Announce Type: new Abstract: Missing data is a common challenge in spatiotemporal systems, arising in applications such as air quality monitoring and urban traffic management. Tradi

applicationsarxiv-cs-lg

Local Ai

StainFlow: Entity-Stain Tracking and Evidence Linking for Process Rewards in GUI Agents

arXiv:2606.07027v1 Announce Type: new Abstract: Reinforcement Learning (RL) has become a promising approach for improving GUI Agents in long-horizon, stochastic digital environments, but trajectory-le

local-aiarxiv-cs-ai

Tutorials

Structure-Preserving Correction Learning for Sparse Bayesian Inference in Brain Source Imaging

arXiv:2606.07196v1 Announce Type: new Abstract: Classical sparse Type-II Bayesian methods for M/EEG brain imaging support joint estimation of source and noise hyperparameters, but rely on fixed iterat

tutorialsarxiv-cs-lg

T2LM: Long-Term 3D Human Motion Generation from Multiple Sentences

arXiv:2406.00636v2 Announce Type: replace Abstract: In this paper, we address the challenging problem of long-term 3D human motion generation. Specifically, we aim to generate a long sequence of smoot

Local Ai

Task Editing for Generalizable 3D Visuomotor Policy Learning

arXiv:2606.07012v1 Announce Type: new Abstract: 3D visuomotor policies offer a promising direction for complex robotic manipulation, as depth maps and point clouds provide rich geometric information f

local-aiarxiv-cs-ro

Teaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization

arXiv:2606.07000v1 Announce Type: new Abstract: Recent post-training methods, particularly Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced the reasoning ability of L

Terastal: Layer-Variant-based Scheduling for Real-Time Multi-DNN Workloads on Heterogeneous Accelerators

arXiv:2606.06818v1 Announce Type: cross Abstract: Heterogeneous DNN accelerators improve soft real-time multi-DNN execution by mapping each layer to its preferred accelerator to reduce latency. Howeve

Local Ai

Towards Serverless Semi-Decentralized Federated Learning with Heterogeneous Optimizers

arXiv:2606.06687v1 Announce Type: new Abstract: We investigate cluster formation, involving the number and composition of clusters, in decentralized federated learning (FL) with heterogeneous machine

local-aiarxiv-cs-lg

USU-Corn-WeedDB: A UAV RGB Image Dataset for Multi-Species Weed Detection in Forage Corn

arXiv:2606.06709v1 Announce Type: new Abstract: Weed pressure in forage corn production causes yield losses of up to 31.5%, yet site-specific weed management (SSWM) systems built on UAV imagery and de

applicationsarxiv-cs-cv

Video-Based Prediction of In-Flight Particle Characteristics in Atmospheric Plasma Spraying

arXiv:2606.07416v1 Announce Type: new Abstract: Atmospheric plasma spraying (APS) is a widely used coating process in which in-flight particle temperature and velocity strongly influence coating quali