Search: “benchmark”

Dynamic Time Step Prediction in Inverse Heat Dissipation for Blur-Like Image Restoration Tasks

arXiv:2610.03942v1 Announce Type: new Abstract: When using diffusion models to target image restoration problems, diffusion inversion is typically employed to retain relevant image information from th

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Dynamics-Aware Adaptive Corridors with Feasibility-Perturbed Trust-Region SQP for Certified Nonholonomic Motion Planning

DGX agent

arXiv:2610.05796v1 Announce Type: new Abstract: Optimisation-based parking planners usually impose collision constraints only at the time samples, so a vehicle corner can cut an obstacle between sampl

model-releasesarxiv-cs-ro

6 Oct 2026

EEGDM: Label-Efficient EEG Representation Learning with Generative Diffusion Model

arXiv:2508.14086v4 Announce Type: replace Abstract: Electroencephalography (EEG) is a critical tool for monitoring brain activity and diagnosing neurological disorders such as epilepsy. However, learn

Efficient Graph Generation via Direct Prediction and Flow Matching

arXiv:2610.05397v1 Announce Type: new Abstract: Generative modeling of graph-structured data is crucial for tasks ranging from drug discovery to social network simulation. Among these models, denoisin

tutorialsarxiv-cs-lg

Efficient Secure Federated Learning via Information-Theoretically Secure Key Distribution: A Medical Imaging Case Study

arXiv:2610.06420v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative training of models across institutions without centralizing sensitive data, making it well-suited for priv

Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts

arXiv:2610.06147v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot transferability but remain vulnerable to target-domain shifts at inference time. Test-time adapta

EORestore-Agent: Fidelity-Guided Agentic Restoration of Remote Sensing Images with Composite Degradations

arXiv:2610.06196v1 Announce Type: new Abstract: Remote sensing images often carry composite degradations, in which haze, cloud, noise, blur, low light, and low resolution coexist. Restoring them requi

Event-based Continuous Color Video Decompression from Single Frames

arXiv:2312.00113v4 Announce Type: replace Abstract: We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional ca

Safety

Evolving LLM-Generated Features for Interpretable Classification

arXiv:2610.03951v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as classifiers, yet they operate as opaque systems whose decisions are difficult to interpret, which

safetyarxiv-cs-lg

EvoMem-VLA: State-Evolution Memory for Long-Horizon Robot Manipulation

arXiv:2610.05418v1 Announce Type: cross Abstract: Most vision-language-action (VLA) models rely on current observations and lose task-relevant evidence once it leaves view, limiting performance on lon

EvoState: Closed-Loop Visual State Management for Long-Form Video Generation

arXiv:2606.16184v2 Announce Type: replace Abstract: Multi-shot long-form video generation remains challenging due to identity drift and compounding inconsistencies across shots. Existing methods encod

Extending Dynamic World Surface Water Mapping to Sentinel-1 with AlphaEarth Embeddings

arXiv:2610.06704v1 Announce Type: new Abstract: Dynamic World (DW) maps land use and land cover globally at 10 m from Sentinel-2 (S2) imagery, but only for cloud-free observations, which limits where

F^2 SLAM: Turning Feed-Forward Geometry into Persistent Factors for SLAM

arXiv:2610.05207v1 Announce Type: new Abstract: Feed-forward 3D models provide strong multi-view geometric priors, while on- line simultaneous localization and mapping (SLAM) relies mainly on local me

Hardware

FlashGaze: Training-Free Multi-Scale Patch Pruning For Efficient Video Understanding

arXiv:2610.04225v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong performance in video understanding, yet efficiently processing long, high-resolution v

hardwarearxiv-cs-cv

FOCUS: Fine-Grained Open-Vocabulary Change Detection for Uncertainty-Aware Semi-Static Scenes

model-releasesarxiv-cs-ro

arXiv:2610.05639v1 Announce Type: new Abstract: Autonomous robots operating over long periods must keep their environmental memory up to date as the world changes between visits. In semi-static enviro

Frequency-Decoupled Diffusion Guidance for Non-Blind Image Deblurring

arXiv:2610.06221v1 Announce Type: new Abstract: Pretrained diffusion models provide powerful image priors for training-free posterior sampling in image restoration. To guide this sampling process, fre

tutorialsarxiv-cs-cv

Applications

From Abusive Language Classification to Sequence Labeling Identification

arXiv:2610.06287v1 Announce Type: cross Abstract: Industrial content moderation must process massive message streams under tight latency constraints, yet most abusive language (AL) detection systems r

applicationsarxiv-cs-lg

From Transformation to Target State: Rethinking Query Representation for Zero-Shot Composed Image Retrieval

arXiv:2610.05993v1 Announce Type: new Abstract: Composed image retrieval (CIR) aims to retrieve a desired target image from a query consisting of a reference image and a modification text. This task e

Frozen in a Frame: The Velocity Blind Spot in JEPA World Models

arXiv:2610.04585v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPAs) for world modeling train an encoder so a predictor maps a current embedding and action to the next fram

Gated Graph Neural Networks for Learning Hidden Independent Cascade Dynamics

arXiv:2610.04033v1 Announce Type: cross Abstract: Information and infectious diseases spread through social networks, but the spreading probabilities driving them are hard to estimate without per-node

Gaussian Flow Dynamics: Simulation-Free Neural SDE Learning Beyond One-Time Marginals

arXiv:2610.04390v1 Announce Type: cross Abstract: Simulation-free training of latent Stochastic Differential Equations (SDEs) relies on a variational posterior process whose one-time marginals are tra

GeoFunFlow: Geometric function flow matching for joint probabilistic inference of physical fields and complex geometries

arXiv:2509.24117v2 Announce Type: replace Abstract: Inverse problems governed by partial differential equations (PDEs) arise widely in science and engineering, but are often ill-posed and limited by s

tutorialsarxiv-cs-lg

Safety

Geometry-Aware Preference Optimization for Text-to-Image Diffusion Models

arXiv:2610.04980v1 Announce Type: new Abstract: Preference alignment has become a standard practice for text-to-image diffusion models. Direct Preference Optimization (DPO) simplifies this process by

safetyarxiv-cs-cv

GPT-6.1 Sol looped 'leak' hints at nested models serving architecture

model-releasesr-localllama

Hello llamas. I am posting this because I believe that, despite it being closed source models, the discussion will bring value to the local AI community. As many of you probably heard, GPT-6 Astra is

GPU-Accelerated Bregman Douglas-Rachford Splitting for Discrete Optimal Transport

arXiv:2610.04715v1 Announce Type: cross Abstract: We present GPU-accelerated Bregman Douglas--Rachford splitting algorithm (BDRS) for discrete optimal transport problem in three input formats: an expl

GR-LIO: A Local Ground-Aware LiDAR-Inertial Odometry System Using Body-to-Ground Height

model-releasesarxiv-cs-ro

arXiv:2610.05546v1 Announce Type: new Abstract: LiDAR-inertial odometry (LIO) is widely used for state estimation in ground-based autonomous mobile robots. However, the geometric constraints provided

Graph-Based Floor Separation Using Node Embeddings and Clustering of WiFi Trajectories

arXiv:2505.08088v4 Announce Type: replace-cross Abstract: Vertical localization, particularly floor separation, remains a major challenge in indoor positioning systems operating in GPS-denied multisto

Hamiltonian Metric Learning and Energy-Based Training: A Dissipative Geometric Framework for Optimization

arXiv:2610.04969v1 Announce Type: new Abstract: Optimization in machine learning is usually expressed through iterative rules that update model parameters using information from the loss landscape. In

Hierarchical Credit Assignment for RLVR on Fused Gromov-Wasserstein Geometry

arXiv:2610.04344v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has been shown to improve the reasoning capability of large language models (LLMs) across diverse

local-aiarxiv-cs-lg

Safety

How Should Teachers Be Prepared? RL on Student-Induced States for On-Policy Distillation

arXiv:2610.04950v1 Announce Type: new Abstract: On-policy distillation (OPD) improves the reasoning capabilities of small language models through token-level teacher supervision on student-generated t

safetyarxiv-cs-lg

I made a Chrome extension that filters your YouTube feed with a small local model running in the browser (WebGPU, no server)

My YouTube feed was mostly songs, pranks and celebrity clips, so I built a filter that judges each video title with a small decision model running inside Chrome. Nothing is sent anywhere: no server, n

local-air-localllama

IdeaLens: Detecting AI Ideas in Long-form Writing

arXiv:2610.06778v1 Announce Type: cross Abstract: While modern AI detectors identify who wrote the words, emerging policies on AI use increasingly hinge on a different question: who came up with the i

IGA-KAN: Isogeometric Analysis with Physics-Informed Closed-Form Kolmogorov-Arnold Networks for Forward and Inverse PDEs

arXiv:2610.06348v1 Announce Type: cross Abstract: Isogeometric analysis (IGA) solves partial differential equations accurately on exact NURBS geometry, whereas neural solvers are mesh-free but often o

local-aiarxiv-cs-lg

Agents

Imagine to Act: High-Fidelity Data Synthesis via Image Editing World Model for Scalable GUI Agent Training

arXiv:2610.05861v1 Announce Type: new Abstract: Graphical User Interface (GUI) agents have emerged as a promising paradigm for automating complex digital workflows across diverse applications. However

agentsarxiv-cs-cv

Applications

Isotropic Gaussian Processes Improve Vanilla Bayesian Optimization in High Dimensions

arXiv:2610.05780v1 Announce Type: cross Abstract: High-dimensional Bayesian optimization (BO) often fits Gaussian process (GP) surrogates from far fewer observations than input dimensions. Modern Vani

applicationsarxiv-cs-lg

Joint Class-Time Learning for Video Classification with Multi-Instance Partial-Label Learning

arXiv:2610.06234v1 Announce Type: new Abstract: Multi-instance partial-label learning (MIPL) addresses inexact supervision in both the instance and label spaces, which can be applied to video classifi

Kinematics-Centric Continuous Sign Language Retrieval with Gloss-Guided Boundary-Aware Alignment

arXiv:2610.05306v1 Announce Type: new Abstract: Sign language-text alignment remains a fundamental challenge for text-driven sign language understanding. Existing methods predominantly rely on appeara

local-aiarxiv-cs-cv

KVE-KD: Key Visual Evidence-Guided Knowledge Distillation for Vision-Language Models

arXiv:2610.03842v1 Announce Type: new Abstract: Knowledge distillation is crucial for deploying vision-language models on resource-constrained devices. However, existing methods typically impose unifo

Label-Free Coreset Selection with Foundation Models for Efficient Annotation in Computational Pathology

arXiv:2610.05987v1 Announce Type: new Abstract: Computational pathology has the potential to improve clinical outcomes through a demonstrated increase in diagnostic and prognostic accuracy. However, t

Latent Flow Matching for Molecular Graph Generation

arXiv:2610.06468v1 Announce Type: new Abstract: Modern graph generative models typically operate directly in the discrete graph space, explicitly generating node and edge variables, which can become c

LD-EnFF: Latent-Dynamics Ensemble Flow Filtering for Data Assimilation with Sparse Observations

arXiv:2610.04034v1 Announce Type: new Abstract: Data assimilation combines model forecasts with noisy, incomplete observations to estimate the evolving state of a dynamical system. Existing methods fa

Learning in Continuous Games from Pairwise Preference Feedback

arXiv:2610.05428v1 Announce Type: cross Abstract: We study learning in continuous games when players receive only pairwise preference feedback, revealing which of two actions is preferred but neither

Learning Interpretable Differentiable Logic Networks for Tabular Regression

arXiv:2505.23615v2 Announce Type: replace Abstract: Neural networks (NNs) achieve outstanding performance in many domains; however, their decision processes are often opaque and their inference can be

Learning Interpretable Differentiable Logic Networks for Time-Series Classification

arXiv:2508.17512v2 Announce Type: replace Abstract: Differentiable logic networks (DLNs) have shown promising results in tabular domains by combining accuracy, interpretability, and computational effi

Learning under Localized Minority Imbalance

arXiv:2610.04936v1 Announce Type: new Abstract: Class-imbalance methods implicitly assume that the minority class is uniformly undersampled relative to the majority class. However, in many real-world

LEON: Location Embeddings from OSM Neighborhoods via Hexagonal Graph Masked Autoencoders

arXiv:2610.05497v1 Announce Type: new Abstract: Geographic information systems increasingly rely on sophisticated spatial representation learning techniques to extract meaningful patterns from complex

tutorialsarxiv-cs-lg

Less Context, Better Geometry: Masked Geometric Encoder for Robust 3D Foundation Models

arXiv:2610.06813v1 Announce Type: new Abstract: Recent progress in 3D foundation models has enabled rapid 3D reconstruction and camera calibration by leveraging learned 3D priors from vast amount of s

tutorialsarxiv-cs-cv

Local AI World Model Part 2 - Deep NN to turn Images into Playable Characters, with prompt switching mid rollout

model-releasesr-localllama

Last time when I posted on this subReddit to share my work, the response almost made me cry because a tiny demo got so many people talking about this In the past 2 months Ive been training a new model