Search: “models”

GenCAR: Generative Counterfactual Alignment with Risk-Controlled Selection for Out-of-Distribution Recommendation

arXiv:2609.02162v1 Announce Type: cross Abstract: Serving useful recommendations under distribution shift is crucial for balancing utility and risk in out-of-distribution (OOD) recommendation. However

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Research

Generalized Regret Analysis of Thompson Sampling using Fractional Posteriors

DGX agent

arXiv:2309.06349v2 Announce Type: replace-cross Abstract: Thompson sampling (TS) is one of the most popular and earliest algorithms to solve stochastic multi-armed bandit problems. We consider a varia

researcharxiv-cs-lg

3 Sept 2026

Generative Diffusion Surrogates with Analytical Variance Schedule

arXiv:2609.01705v1 Announce Type: new Abstract: Stochastic transport describes physical systems in which an initially structured distribution spreads under unresolved forcing, scattering, or heterogen

tutorialsarxiv-cs-lg

Graph Machine: Towards Better Pretraining via Edges

arXiv:2609.02881v1 Announce Type: new Abstract: We introduce the Graph Machine (GM), an architecture that maintains an O(n)-sized state and accesses it through sparse, dynamic routing. Unlike methods

Handwriting Trajectory Recovery via Autoregressive Ordered Stroke Instance Prediction

arXiv:2609.02251v1 Announce Type: new Abstract: Handwriting trajectory recovery aims to infer the dynamic writing process hidden behind a static handwritten image. Since offline handwriting preserves

Hardware-Accelerated Instance Segmentation for Resource-Constrained Space Robotics with Criticality Analysis

arXiv:2609.02219v1 Announce Type: cross Abstract: Autonomous lunar missions require real-time per- ception under three coupled constraints: extreme low-light conditions, limited onboard compute, and r

HyGRAIL: Cost-Aware and Evidence-Grounded Scientific Hypothesis Discovery over Knowledge Graphs

arXiv:2609.02056v1 Announce Type: new Abstract: Scientific knowledge graphs organize entities and relations extracted from scientific literature, but they remain inherently incomplete. Missing typed l

agentsarxiv-cs-cl

If It Moves, Radar Knows: A Physics-Aware Radar Transformer for Class-Agnostic Moving-Object Detection

arXiv:2609.02289v1 Announce Type: new Abstract: Detectors trained on closed-set annotations can miss rare moving objects outside the training taxonomy. Automotive radar provides category-independent D

Learning-Based Reconstruction Attacks on Coordinate-Obfuscated Point Clouds

arXiv:2609.02568v1 Announce Type: cross Abstract: Volumetric video based on point cloud representations enables immersive virtual and augmented reality applications but introduces significant challeng

Local Ai

Learning to Track from Privileged Target Appearances

arXiv:2609.02471v1 Announce Type: new Abstract: Target templates define what a visual tracker searches for, yet the templates available at inference trade off localization certainty with appearance fr

local-aiarxiv-cs-cv

Applications

Marginal Expected Revenue for Jointly Ranking Auction and Fixed-Price Listings in E-Commerce Sponsored Search

arXiv:2609.01628v1 Announce Type: cross Abstract: E-commerce search ranking must balance multiple objectives--relevance, user engagement, and platform revenue--when allocating impression slots to comp

applicationsarxiv-cs-lg

Median-of-Means as an Extremal Convex Estimator and a Nonconvex Route to the Trimmed Oracle

arXiv:2609.01689v1 Announce Type: new Abstract: We revisit median-of-means estimation from a deterministic optimization viewpoint and develop a family of block-Lp estimators for robust learning with h

MMTryon: Multi-Modal Multi-Reference Control for High-Quality Fashion Generation

arXiv:2405.00448v5 Announce Type: replace Abstract: This paper introduces MMTryon, a multi-modal multi-reference VIrtual Try-ON (VITON) framework, which can generate high-quality compositional try-on

MS-MEM: Multi-Skill Manipulation-Enhanced Mapping via Uncertainty- and Disturbance-Aware Action Selection

arXiv:2609.02493v1 Announce Type: new Abstract: Accurate scene understanding in confined, cluttered spaces such as shelves is essential for service robots, as many everyday tasks require them to locat

researcharxiv-cs-ro

Neural operators approximate strongly continuous convex monotone semigroups

arXiv:2609.02727v1 Announce Type: cross Abstract: We approximate strongly continuous convex monotone semigroups by learning their Chernoff-type one-step operators with neural operators. First, we intr

Online Non-Monotone DR-Submodular Maximization Matching the Offline 0.401 Factor

arXiv:2609.02145v1 Announce Type: cross Abstract: We study online maximization of nonnegative, non-monotone DR-submodular functions over compact convex down-closed subsets of the d-dimensional unit cu

Orthogonal Ensembles and Tested Explanations for Performer-Independent Body-Motion Emotion Recognition

arXiv:2609.02510v1 Announce Type: new Abstract: We study body-only, 12-class acted-emotion classification from skeleton motion under leave-performer-out (LPO) evaluation, a hard, underdetermined setti

Passivity-Centric Safe Reinforcement Learning for Contact-Rich Robotic Tasks

arXiv:2503.00287v3 Announce Type: replace Abstract: Reinforcement learning (RL) has achieved remarkable success in various robotic tasks; however, its deployment in real-world scenarios, particularly

safetyarxiv-cs-ro

PIE-APT: Abductive Planning over Temporal Dynamic Knowledge Graphs via Incremental Reasoning

arXiv:2607.27287v2 Announce Type: replace Abstract: Planning over Temporal Dynamic Knowledge Graphs (TDKGs) presents theoretical challenges in open-world environments with incomplete information. Exis

Query Rewriting for Complex Object Segmentation in 4D Gaussian Representations

arXiv:2609.02664v1 Announce Type: new Abstract: Recent 4D Gaussian representation frameworks have demonstrated strong performance in language-guided dynamic scene understanding. However, these methods

Local Ai

RAFT-DVC: Resolution-Aware Machine Learning-Based Digital Volume Correlation

arXiv:2609.01876v1 Announce Type: new Abstract: Digital volume correlation (DVC) provides three-dimensional full-field displacement measurements from volumetric images, but how the internal resolution

local-aiarxiv-cs-cv

READY or Not: Reliable Enterprise Agent Deployment

arXiv:2609.02095v1 Announce Type: new Abstract: An AI agent can perform well on benchmarks and still be unsuitable for deployment. Existing AI-agent benchmarks measure whether an agent can complete re

safetyarxiv-cs-ai

SelfMOTR: Revisiting MOTR with Self-Generating Detection Priors

arXiv:2511.20279v3 Announce Type: replace Abstract: End-to-end transformer architectures have driven significant progress in multi-object tracking by unifying detection and association into a single,

Shiva-DiT: Residual-Based Differentiable Top-k Selection for Efficient Diffusion Transformers

arXiv:2602.05605v2 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) are costly at high resolution because self-attention scales quadratically with token sequence length. Existing p

safetyarxiv-cs-ai

SkillGLoW: Procedural-Family Skill Consolidation for Self-Improving Agents on Long-Horizon Task Streams

arXiv:2609.02217v1 Announce Type: new Abstract: LLM agents increasingly self-improve by writing and reusing textual skills, kept either as one global document or as a flat pool of per-task entries, th

SMart: A Multi-source Multi-phase Time Series Representation Transfer Framework

arXiv:2609.02203v1 Announce Type: cross Abstract: Time series representation learning (TSRL) has attracted growing research interests in recent years. Two recent explorations in TSRL are: i) exploitin

tutorialsarxiv-cs-ai

SSAKG 2.0: An Open-Source Package for Structural Associative Sequence Memory and Context-Based Retrieval

arXiv:2609.01849v1 Announce Type: new Abstract: This article presents SSAKG 2.0, an open-source software package for constructing and operating Structural Sequential Associative Knowledge Graphs (SSAK

Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets

arXiv:2609.01765v1 Announce Type: new Abstract: Carbon markets put a price on emissions, yet that price remains hard to forecast. Work in this area clusters on the EU and Chinese schemes, compresses r

safetyarxiv-cs-lg

Tri-Band Channel Measurement-Enabled Multi-Layer Digital Twin for Terahertz Wireless Data Centers

arXiv:2609.01699v1 Announce Type: new Abstract: The rapid growth of AI computing has driven increasing demands for flexible and high-capacity data-center interconnections. Owing to its ultra-wide band

Applications

UnCapsTSR: An Unsupervised Transformer-based Image Super-Resolution Approach for Capsule Endoscopy Images

arXiv:2609.02476v1 Announce Type: new Abstract: Wireless Capsule Endoscopy (WCE) captures and streams video while passing through a patient's Gastrointestinal (GI) tract and is used to examine its irr

applicationsarxiv-cs-cv

ViSAR: Training-Free Adaptive-k Retrieval for Visual Document Question Answering

arXiv:2609.02486v1 Announce Type: cross Abstract: Document Visual Question Answering (DocVQA) often leverages Retrieval-Augmented Generation (RAG), where late-interaction encoders are commonly used to

VoRTeC: Taming Foundation Flow for One-step Real time Video Compression

arXiv:2609.02291v1 Announce Type: cross Abstract: Ultra-low bitrate video compression still faces critical challenges: traditional neural video compression inevitably introduces blurring artifacts, wh

WaveSync: Constrained Wavefront Optimization for Synchronized Co-Speech Gestures in Humanoid Robots

arXiv:2606.16600v2 Announce Type: replace Abstract: Expressive co-speech gestures are crucial for natural human--robot interaction, yet generating them on physical humanoid robots remains challenging

safetyarxiv-cs-ro

WiFlow: Estimating Optical Flow using WiFi Channel State Information

arXiv:2609.02452v1 Announce Type: new Abstract: Knowing where and how fast objects are moving within a scene is important across various domains. Usually, cameras are used to capture the data necessar

A Sensor-Adaptive Incremental Learning Framework for Artifact Detection in Satellite Precipitation Data

arXiv:2609.01514v1 Announce Type: cross Abstract: Historically, retrieving rainfall data from satellite imagery has been the domain of space agencies. However, in recent years, the development of chea

Local Ai

A Study of Hidden-State Optimization Order in Predictive Coding Networks

arXiv:2609.00686v1 Announce Type: cross Abstract: Local learning methods offer an alternative to end-to-end backpropagation, but their unstructured local objectives can produce weak feature learning i

local-aiarxiv-cs-ai

Agentic programs: an emerging form of scientific software in computational materials science

arXiv:2609.00795v1 Announce Type: cross Abstract: Computational materials science has traditionally delegated algorithmic tasks to computers while leaving scientific judgments to humans. We argue that

agentsarxiv-cs-ai

AutoConcept: Training-Free Concept-Guided Reranking for Metadata-Available Composed Image Retrieval

arXiv:2609.01456v1 Announce Type: cross Abstract: Composed image retrieval (CIR) retrieves a target image from a reference image and a text modification. This paper studies metadata-available CIR rera

safetyarxiv-cs-cl

Beneath the Diff: Diagnosing and Mitigating Algorithmic Mode Collapse in Code-Level Autonomous Research Loops

arXiv:2609.00077v1 Announce Type: new Abstract: Code-level autonomous research loops (ARLs) have recently emerged as a concrete object of study in automated machine learning research. In such loops, a

agentsarxiv-cs-cl

Beyond AHI: An Interpretable Causal-Discovery-Guided Framework for Sleep Recovery in Connected Health

arXiv:2606.18506v2 Announce Type: replace Abstract: Objective sleep assessment relies on polysomnography (PSG), yet clinical impact is often better reflected in patient-reported outcomes (PROs) such a

safetyarxiv-cs-lg

Beyond Landmark Extraction: A Framework for Robust Geometric Feature Construction in Structured Image Classification

arXiv:2609.00634v1 Announce Type: new Abstract: Much of the literature on structured image recognition has disproportionately focused on the comparison of classification algorithms. Rather than invest

tutorialsarxiv-cs-cv

Causal Evidentiary Governance for High-Risk Machine Learning Systems

arXiv:2609.01040v1 Announce Type: cross Abstract: Machine learning systems deployed for credit, hiring, and resource distribution are increasingly subject to regulatory oversight from policies such as

safetyarxiv-cs-ai

CERF: Communication-Efficient and Retraining-Free Collaborative Perception

arXiv:2609.00951v1 Announce Type: new Abstract: Collaborative perception shares information among multiple agents to obtain a comprehensive scene representation, enhancing the perceptual capability of

agentsarxiv-cs-cv

CrossFeat: Bridging Imaging Modalities in Feature Descriptor Space

arXiv:2609.00272v1 Announce Type: new Abstract: Most advances in keypoint descriptions address monomodal settings, where image variations arise from viewpoint, illumination, or contrast changes. Multi

CWoMP: Morpheme Representation Learning for Interlinear Glossing

arXiv:2603.18184v2 Announce Type: replace Abstract: Interlinear glossed text (IGT) is a standard notation for language documentation which is linguistically rich but laborious to produce manually. Rec

researcharxiv-cs-cl

Dense Process Supervision for Search Agents via Fact Utility Estimation

arXiv:2609.00833v1 Announce Type: new Abstract: Reinforcement learning (RL) for search agents typically relies on outcome rewards. However, it often fails to achieve effective credit assignment, due t

tutorialsarxiv-cs-cl

Design and Implementation of a Kalman Filter-Infused Algorithm for Tilt Estimation

arXiv:2609.00730v1 Announce Type: new Abstract: Accurate tilt angle estimation is important in many engineering applications, such as robotics, motion tracking, and embedded control systems. However,

Detoxifying Toxic Communication: A Design Science Approach to Responsible AI

arXiv:2609.00361v1 Announce Type: cross Abstract: Toxic language in digital workplaces such as pejoratives, sarcasm, condescension, and subtle incivility can erode trust, morale, and collaboration. Ex

safetyarxiv-cs-cl