Search: “models”

Convergence, design and training of continuous-time dropout as a random batch method

arXiv:2510.13134v2 Announce Type: replace Abstract: We study continuous-time dropout in controlled differential equations. We introduce a random-batch approximation of additive vector fields. On each

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Cost Characterization of Vertically Partitioned Federated Knowledge Graphs

DGX agent

arXiv:2609.13664v1 Announce Type: new Abstract: Knowledge graphs are increasingly distributed across autonomous organizations that share an entity space but own disjoint subsets of relations, forming

agentsarxiv-cs-ai

15 Sept 2026

CVSS-X: A Multilingual Speech-to-Speech Translation Corpus for 28 Languages

arXiv:2609.13413v1 Announce Type: new Abstract: We introduce CVSS-X, a large-scale synthetic speech-to-speech translation corpus that extends CVSS by reversing the translation direction. While CVSS tr

researcharxiv-cs-cl

Degraded but Not Entirely Ineffective: PE-Based Deformable Graph Neural Networks

arXiv:2609.13712v1 Announce Type: new Abstract: Many real-world scenarios can be represented using graph-structured data. However, traditional GNNs that transmit messages based on first-order neighbor

applicationsarxiv-cs-ai

Delegating Authorization to Misaligned Agents: Coalitional Alignment and Safe Control

arXiv:2609.15803v1 Announce Type: cross Abstract: Long-running AI agents create a control problem: each action they take changes the state, which in turn affects the trajectory of future actions. If t

Diagnosing Temporal Misalignment in Multichannel Time-Series Classification with Minimum Description Length

arXiv:2609.14595v1 Announce Type: cross Abstract: Multichannel time-series classification commonly assumes synchronized sensor streams, although latency, clock drift, and preprocessing can introduce r

Disentangling Representation Evolution in Transformers through Directional Decomposition

arXiv:2609.15975v1 Announce Type: new Abstract: Transformer representations evolve through learned additive transformations that either preserve their current direction or redirect it. We study this e

researcharxiv-cs-cl

Don't Count the Edits, Judge by the Outcome Alone: Reward-Based Evaluation for Grammatical Error Correction

arXiv:2609.15559v1 Announce Type: cross Abstract: Grammatical error correction (GEC) evaluation has traditionally relied on reference or edit overlap, which can penalize valid rewrites that differ fro

El Agente Potente: High-Throughput Agentic Atomistic Simulations

arXiv:2609.14840v1 Announce Type: new Abstract: Foundational machine-learning interatomic potentials (MLIPs) are transforming atomistic simulations by achieving near-ab initio accuracy across large ch

agentsarxiv-cs-ai

Ergodic Trajectory Planning with Dynamic Sensor Footprints

arXiv:2512.08661v2 Announce Type: replace Abstract: This paper addresses the problem of trajectory planning for information gathering with a dynamic and resolution-varying sensor footprint. Ergodic pl

applicationsarxiv-cs-ro

Exact Spin Elimination for Quadratic and k-Local Ising Optimization

arXiv:2505.07163v2 Announce Type: replace-cross Abstract: Ising solvers have a finite spin budget. Quadratization uses auxiliary spins to replace higher-order interactions by pairwise ones. We show th

Externalizing Requirement-to-Repair Artifacts as Observable Traces for LLM-Based Program Repair

arXiv:2609.14913v1 Announce Type: new Abstract: Repository-level repair requires not only correct patches but also inspectable records that explain how issue requirements are translated into code chan

Flow-Matched Motion Priors: Online Optimal-Transport Rewards for Imitation Learning

arXiv:2609.15631v1 Announce Type: new Abstract: Learning a motion prior requires a reward that guides a policy from its current behavior toward demonstrated motion. Adversarial Motion Priors (AMP) pro

safetyarxiv-cs-ro

Force-Aware Reinforcement Learning with Hybrid Sensorless Force Estimation for Wheeled-Legged Loco-Manipulation

arXiv:2609.13779v1 Announce Type: new Abstract: Force-controlled loco-manipulation requires a whole-body policy to coordinate locomotion and arm motion while regulating end-effector interaction forces

safetyarxiv-cs-ro

Fraglingo: Molecular Design via Attachment-Aware Autoregressive Fragment Generation

arXiv:2609.13519v1 Announce Type: new Abstract: Molecular design is most effective when generation mirrors the edits chemists actually make: extending a scaffold, replacing a substituent, or decoratin

From objective discovery to prediction of global ocean eco-provinces: A pathway for trustworthy learning

arXiv:2609.13206v1 Announce Type: cross Abstract: Marine ecosystems are increasingly impacted by climate change, necessitating tools to identify and predict spatial habitat information. To build such

From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go

arXiv:2412.05445v3 Announce Type: replace-cross Abstract: Online reviews help people make better decisions. Review platforms usually depend on typed input, where leaving a good review requires signifi

agentsarxiv-cs-ai

GaugeDefect: Detecting Surface Anomalies by Curvature of Feature Transport

arXiv:2609.13282v1 Announce Type: new Abstract: Industrial anomaly localization has advanced rapidly with feature-based, reconstruction-based, and distillation-based methods. Most of these methods sco

GeoTTER: Leveraging Local Geometry of Optimal Transport for Zero-Shot Classification

arXiv:2609.13518v1 Announce Type: new Abstract: We present GeoTTER, a novel framework that redefines optimal transport in the realm of zero-shot classification. Conventional methods often suffer from

safetyarxiv-cs-lg

Hardware

Goal-Oriented Communications for Physical AI: Design and Testbed

arXiv:2609.15895v1 Announce Type: new Abstract: Physical AI relies on frequently-updated, latency-sensitive video stream to perceive, reason, and interact with the physical world, resulting in strict

hardwarearxiv-cs-ro

GraMRAG: Orchestrating Multi-Agent Multi-Step Reasoning via Graph Memory with Reinforcement Learning

arXiv:2609.14066v1 Announce Type: cross Abstract: Although existing multi-agent Retrieval-Augmented Generation (RAG) systems have demonstrated promise on complex multimodal reasoning tasks, they remai

HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness

arXiv:2609.15195v1 Announce Type: new Abstract: Embodied navigation requires agents to interpret visual observations, accumulate spatial knowledge, and execute actions to follow instructions or locate

agentsarxiv-cs-ro

Industry

Have it both ways: stay discoverable in search while disallowing AI training

The post explains how site owners can keep their content visible in search engines while blocking its use for AI training datasets. It details technical approaches—such as specific robots.txt rules, m

industrycloudflare-ai

HGSQ: Heatmap-Guided Sparse Query Detector for Real-Time Aerial Small Object Detection

arXiv:2609.13306v1 Announce Type: new Abstract: Real-time aerial small object detection is an important visual signal and image processing problem, requiring a detector to preserve fine-grained locali

How broad is that claim? Mapping Generalisation in NLP Research

arXiv:2609.14770v1 Announce Type: cross Abstract: Generalisations are common in scientific communication, even though they are semantically ambiguous. An automated method is needed to identify and cat

(How) Do MLLMs Report Bistable Images Like Humans?

arXiv:2609.13254v1 Announce Type: cross Abstract: Bistable images such as the duck-rabbit are classic stimuli in which one image supports multiple mutually incompatible interpretations, typically repo

Hardware

How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin

The NVIDIA Vera Rubin platform attains superior performance‑per‑watt by combining factory‑level DSX MaxLPS power shifting, rack‑level capacitors with Intelligent Power Smoothing, and the Groq 3 LPX de

hardwarenvidia-developer

Tutorials

How to Better Train VLAs: Lessons Learned From the REAL-I Challenge at ICRA 2026

arXiv:2609.13679v1 Announce Type: new Abstract: How can robot policies learn more effectively from a fixed demonstration budget? The first Real-world Embodied AI Learning (REAL-I) Challenge at ICRA 20

tutorialsarxiv-cs-ro

Hypergraph-Regularized Gramian Volumes for Multimodal Retrieval

arXiv:2609.15320v1 Announce Type: new Abstract: Volume-based multimodal retrieval jointly scores a text query with a candidate's video, audio, and subtitle embeddings. While this approach captures hig

safetyarxiv-cs-cv

Interpolation Is Not Invariance: Pair Count Is Not Coverage in Transformation Audits

arXiv:2609.14870v1 Announce Type: cross Abstract: Counting equivalent pairs is a common way to report transformation-audit coverage, but it can substantially overstate the constraints imposed by an au

JEPLO: Joint-Embedding Predictive Learning for LiDAR-Based Legged Locomotion

arXiv:2609.15770v1 Announce Type: new Abstract: Light detection and ranging (LiDAR) remains less explored than RGB-D sensing for perceptive legged locomotion, and existing LiDAR-based approaches often

safetyarxiv-cs-ro

Local Ai

Learning-Based Dynamic Obstacle Avoidance for a UAV Using Only Three Range Sensors

arXiv:2609.14426v1 Announce Type: new Abstract: We present a learning-based approach to kinodynamic online motion planning for an Unmanned Aerial Vehicle (UAV) operating at a fixed altitude in unknown

local-aiarxiv-cs-ro

Learning Continuous Source Responses For Generalizable AI-Generated Image Detection

arXiv:2609.14316v1 Announce Type: new Abstract: Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustwor

Learning to Solve Stochastic Controls with Unknown Drifts and Running Rewards: Theory, Algorithms and Convergence

arXiv:2609.14972v1 Announce Type: new Abstract: We study continuous-time and possibly high-dimensional stochastic control problems where drift coefficients and running reward functions are unknown. Du

safetyarxiv-cs-lg

LIMODENet: Attention-Free Compact Encoders for Information-Preserving Onboard Satellite Image Restoration

arXiv:2609.14690v1 Announce Type: new Abstract: Onboard satellites must restore a channel-degraded image on a few watts, using neuromorphic accelerators (e.g., BrainChip Akida, Intel Loihi-2) that sup

applicationsarxiv-cs-cv

LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordinal Data

arXiv:2602.04192v3 Announce Type: replace Abstract: Learning the intrinsic dimensionality of subjective perceptual spaces such as taste, smell, or aesthetics from ordinal data is a challenging problem

applicationsarxiv-cs-lg

Machine Learning in Fish Farming

arXiv:2609.13919v1 Announce Type: new Abstract: This chapter explores how machine learning (ML) is transforming aquaculture, with a particular focus on enhancing decision-making processes and improvin

applicationsarxiv-cs-lg

Map Users and Mapmakers: The Scope of Cognitive Attribution from Acquired Representations

arXiv:2609.13879v1 Announce Type: new Abstract: An acquired representation can enlarge a system's cognitive repertoire without transferring the capacities exercised in producing that representation. T

Measuring the Creativity of Frontier LLMs in Automated Research

arXiv:2609.14057v1 Announce Type: new Abstract: Frontier LLMs are increasingly capable of conducting automated research, yet their creativity in this setting has not been systematically evaluated. In

researcharxiv-cs-cl

MedTRACE: Tool-Augmented Multimodal Clinical Reasoning Agents for Evidence-Grounded Decision-Making

arXiv:2609.14823v1 Announce Type: new Abstract: Multimodal clinical decision-making requires reliable reasoning over heterogeneous evidence from electronic health records, medical images, and physiolo

agentsarxiv-cs-cl

Mobile CT Services for Rural, Regional, and Remote Areas: Current Practice and Future Integration with Telehealth and Regulatory-Authorised AI

arXiv:2609.14347v1 Announce Type: new Abstract: Computed tomography (CT) plays an essential role in clinical workflow to improve patient outcomes. However, access to CT imaging and specialist interpre

applicationsarxiv-cs-cv

Multi-Task Visual Perception Network with LLM Conditioning for Autonomous Navigation

arXiv:2609.14297v1 Announce Type: new Abstract: Long-term navigation for service robots faces crit- ical challenges like the accumulation of odometry drift and sensor error, which progressively degrad

agentsarxiv-cs-ro

Multi-View Structure-from-Motion Enables Oriented Projective Shape Analysis in Three Dimensions

arXiv:2609.13263v1 Announce Type: new Abstract: Projective shape analysis provides a geometric framework for studying landmark configurations in digital images acquired by pinhole cameras. In the clas

Multilingual Agent System for Inclusive Wildfire Evacuation Guidance

arXiv:2609.03301v1 Announce Type: cross Abstract: Wildfire seasons have become 84 days longer in the current days than in the 1970s, causing enormous threats to one's financial status and short- and l

agentsarxiv-cs-ai

Multimodal deep learning from spectra for small-molecule structure identification: enhancing robustness with mixed-condition training

arXiv:2609.14360v1 Announce Type: new Abstract: In practical molecular characterization, small-molecule structure identification benefits from complementary spectroscopic evidence, but missing, degrad

New Conditions for Philosophers to Catch the Wave of Citizen Deliberation in the Age of Artificial Intelligence in advance

arXiv:2609.15707v1 Announce Type: new Abstract: Powerful technologies labeled ``AI''-without sufficient epistemic caution-are already reshaping political and private life, bringing both new dangers an

Noise-Adaptive Conformal Classification with Marginal Coverage

arXiv:2501.18060v2 Announce Type: replace-cross Abstract: Conformal inference provides a rigorous statistical framework for uncertainty quantification in machine learning, enabling well-calibrated pre

applicationsarxiv-cs-lg

Local Ai

Noise-Aware and Dynamically Adaptive Federated Defense Framework for SAR Image Target Recognition

arXiv:2601.00900v2 Announce Type: replace-cross Abstract: As a critical application of computational intelligence in remote sensing, deep learning-based synthetic aperture radar (SAR) image target rec

local-aiarxiv-cs-cv