Search: “models”

Synthetic Data Characterization via Training Dynamics

arXiv:2609.39447v1 Announce Type: new Abstract: Interpreting properties of LLM-generated data is important for understanding its utility and limitations across learning tasks. In this work, we charact

researcharxiv-cs-cl

TACTIC: Temporal and Context-Aware LLM Tactical Planning for Roadside LiDAR Attacks

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DGX agent

arXiv:2609.39969v1 Announce Type: cross Abstract: Physical LiDAR attacks are often evaluated using fixed primitives and manually selected parameters, despite their strong dependence on surrounding tra

local-aiarxiv-cs-ai

1 Oct 2026

Applications

Taipan: A Query-free Transfer-based Multiple Sensitive Attribute Inference Attack Solely from Auxiliary Graphs

arXiv:2602.06700v2 Announce Type: replace-cross Abstract: Graph-structured data underpin a wide spectrum of modern applications, yet their multiple sensitive attributes are not isolated but deeply cou

applicationsarxiv-cs-lg

TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning

arXiv:2609.39335v1 Announce Type: new Abstract: Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing meth

Tutorials

TSGL: Teacher-Student Graph Learning for 3DGS Compression

arXiv:2609.38635v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) is a popular representation for novel view synthesis. However, 3DGS contains millions of Gaussian primitives, each with r

tutorialsarxiv-cs-cv

TTLab at Daleel 2026: STAR-Ar, Sequence Tagging for Argument Recognition in Arabic

arXiv:2609.39385v1 Announce Type: cross Abstract: Argument Mining (AM) is a critical NLP task that remains significantly under-resourced in Arabic. This paper presents esttt{STAR-Ar}, a BERT-BiLSTM-CR

researcharxiv-cs-ai

URBAN-SPIN: A street-level bikeability index to inform design implementations in historical city centres

arXiv:2602.10124v2 Announce Type: replace-cross Abstract: Cycling is reported by an average of 35% of adults at least once per week across 28 countries, and as vulnerable road users directly exposed t

When Can Text Replace Vision? Structural Bottlenecks in Diagram Reasoning

arXiv:2609.39142v1 Announce Type: new Abstract: Can structured text replace vision for diagram reasoning? A wrong answer after textualization can arise because the representation omits information the

Which Tasks Survive Self-Supervised Learning?

arXiv:2609.38393v1 Announce Type: cross Abstract: Same-instance self-supervised learning (SSL) learns representations by enforcing consistency across two views of the same underlying instance. This pr

researcharxiv-cs-ai

Absorbed in Inertia: Activation Analysis for Computer-Use Agents

arXiv:2609.37176v1 Announce Type: new Abstract: Computer-use agents have become increasingly capable of executing tasks on live desktops through natural-language instructions, based on trajectories of

Accelerated surrogate dynamics for dynamical, stochastic system evolution

arXiv:2609.37184v1 Announce Type: new Abstract: Dynamic simulations are an entrenched way of gaining insight into the evolution of system dynamics. Their computational cost however is often prohibitiv

local-aiarxiv-cs-ai

All You Need Is Low Fidelity: Zero-Shot Sim-to-Real of Learned Robotic Fish Control

arXiv:2609.36993v1 Announce Type: new Abstract: Complex tasks for underwater robots remain limited by the capabilities of their controllers. Learning a better one for a soft, underactuated robotic fis

safetyarxiv-cs-ro

An Efficient Machine Learning Approach for Degradation Forecasting in AEM Water Electrolysis

arXiv:2609.37941v1 Announce Type: new Abstract: This study provides a data-driven analysis of a novel dataset of single-cell Anion Exchange Membrane water electrolyzers (AEMWE), operated under constan

AS^2D: Accelerating On-Demand Audio Understanding on Mobile Devices

arXiv:2609.37617v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive generation by using a smaller drafter to propose tokens for batched verification by a larger target. H

researcharxiv-cs-ai

Audience-Bound Persistent Memory: Authorization Across the Memory Lifecycle

arXiv:2609.36373v1 Announce Type: cross Abstract: A personal language agent that acts for its owner across private and shared conversations can learn a fact from one audience and later place it in the

AVIO: Learning to Add and Remove Sounding Objects in Audiovisual Scenes

arXiv:2609.36503v1 Announce Type: new Abstract: Adding or removing a sounding object requires coordinated changes to visual content and sound while preserving the surrounding scene. Yet paired supervi

local-aiarxiv-cs-ai

Can Representation Learning Decouple from Loss Minimization? Polar Updates Have an Answer

arXiv:2609.36240v1 Announce Type: new Abstract: Does representation learning stop when the training loss stops improving? We study this question for matrix Muon, whose polar-normalised updates have a

safetyarxiv-cs-lg

Comparing Utility of Inertial, Occupancy, Semantic, and Intent Information in Human Motion Prediction During Daily Tasks

arXiv:2609.37971v1 Announce Type: new Abstract: Accurate human motion prediction is crucial for robotic systems operating around people, particularly in complex indoor spaces. In this study, we assess

researcharxiv-cs-ro

Concept Direction Reliability Across Languages with Different Tokenizer Fertility

arXiv:2609.36194v1 Announce Type: new Abstract: Extracted sentiment directions can vary across samples even when downstream sentiment classification remains accurate. To evaluate direction reproducibi

researcharxiv-cs-cl

Cryo-EM as a Stochastic Inverse Problem

arXiv:2509.05541v2 Announce Type: replace-cross Abstract: Cryo-electron microscopy (Cryo-EM) enables high-resolution imaging of biomolecules, but structural heterogeneity remains a major challenge in

Hardware

DIET: Deletion-response Expert Trimming for Video Diffusion Transformers

arXiv:2609.37829v1 Announce Type: new Abstract: Video diffusion transformers (DiTs) increasingly adopt mixture-of-experts (MoE) architectures to reduce active computation, but their full expert storag

hardwarearxiv-cs-ai

DimGrow: Memory-Efficient Field-level Embedding Dimension Search

arXiv:2505.12683v2 Announce Type: replace Abstract: Key feature fields need bigger embedding dimensionality, others need smaller. This demands automated dimension allocation. Existing approaches, such

DispFlow-GS: Displacement Flow Supervision with Motion Disentangling for Monocular Deformable 3D Gaussian Splatting

arXiv:2609.36940v1 Announce Type: new Abstract: Accurate dynamic scene reconstruction is important for robotic perception, where temporally consistent representations of dynamic environments are essen

safetyarxiv-cs-cv

doPlan: A Variable-Horizon Dataset for Multi-Stage Language-Conditioned Planning in Autonomous Driving

arXiv:2609.38028v1 Announce Type: cross Abstract: Autonomous vehicles interacting with passengers through natural language must reason beyond immediate commands. Passenger intent may span multiple sta

DROM: A Language-Guided Diffusion Framework for Multi-Skill Robotic Manipulation

arXiv:2609.37348v1 Announce Type: new Abstract: Learning robust manipulation policies for diverse, long-horizon tasks from limited demonstrations remains a fundamental challenge in robotics. We presen

safetyarxiv-cs-ro

DynamicHOI: Coupled Dynamics for Physics-aware HOI Reconstruction

arXiv:2609.36454v1 Announce Type: new Abstract: We study hand-object interaction (HOI) reconstruction from monocular RGB videos, where partial observations can produce visually plausible yet mechanica

EasyPPO: Stabilizing the Critic Is Key

arXiv:2609.36802v1 Announce Type: new Abstract: A key strength of Proximal Policy Optimization (PPO) is its learned critic, which uses historical trajectories collected during reinforcement learning t

safetyarxiv-cs-lg

Efficient and Scalable Physics-Guided Fully Convolutional Spatiotemporal Learning for 3D Microstructure Evolution Prediction

arXiv:2609.36504v1 Announce Type: new Abstract: Accurate prediction of three-dimensional (3D) microstructure evolution remains computationally demanding because high-fidelity phase-field simulations r

local-aiarxiv-cs-lg

EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation

arXiv:2609.38046v1 Announce Type: new Abstract: Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with miss

safetyarxiv-cs-ro

Environment Steering: Using Data Flow Control to Improve Agent Utility and Safety

arXiv:2609.35807v1 Announce Type: cross Abstract: LLM agents can make unsafe tool calls even when instructed to behave safely. Existing defenses constrain agents before execution, modify tool inputs/o

FLASH: A 'Generate Once, Synthesize Many' Framework for Synthetic Anomaly Generation in Industrial Anomaly Detection

arXiv:2609.37314v1 Announce Type: new Abstract: Synthetic anomaly generation helps expand industrial anomaly datasets when real defects are scarce or unavailable. Existing approaches lie at two extrem

FM-ReID: Selective Competitive Token Routing for Object Re-Identification

arXiv:2609.36560v1 Announce Type: cross Abstract: Object re-identification (ReID) faces a recurring challenge: different identities can share highly similar global appearances, while the cues that dis

local-aiarxiv-cs-ai

FORM: Robot Manipulation through Direct Material Law Identification

arXiv:2609.38105v1 Announce Type: new Abstract: When interacting with an unfamiliar deformable material, a robot lacks prior knowledge of its physical properties and how it will respond to applied for

researcharxiv-cs-ro

Foundations of Proactive Agents: Principles, Technical Layers, and Proactivity-Gym

arXiv:2609.37267v1 Announce Type: new Abstract: Proactive LLM agents can turn idle compute into useful support before users ask. Yet even correct work can misread user context, impose review costs, or

Generating Edit-Inducing Questions for AI Research Manuscripts

arXiv:2609.36617v1 Announce Type: new Abstract: We study the ability of LLMs to generate edit-inducing questions whose answer will improve a paper draft. On a dataset of paired submission and camera-r

researcharxiv-cs-cl

Tutorials

GenLimitLib: A Formal Library for Language Generation in the Limit and AI-Assisted Mathematical Research

arXiv:2609.36663v1 Announce Type: new Abstract: We present GenLimitLib, a source-aligned Lean 4 library for language generation in the limit. Introduced by Kleinberg and Mullainathan at NeurIPS 2024,

tutorialsarxiv-cs-lg

GNA: Granular Neighbor Assembly for Retrieval-Augmented Multivariate Time-Series Forecasting

arXiv:2609.36281v1 Announce Type: new Abstract: Deep forecasters predict from a fixed-length lookback window, and lengthening it gives diminishing returns at a growing cost. Retrieval augmentation ins

Industry

Google finds vulnerability disclosures doubled as AI changes which flaws get discovered

A new report out today from Google LLC’s Google Threat Intelligence Group finds that monthly software vulnerability disclosures doubled between January and August. Not surprisingly, artificial intelli

industrysiliconangle

HaPRL: Human-Anchored Process Reinforcement Learning for Visual Search Agent

arXiv:2609.37190v1 Announce Type: new Abstract: Multi-turn visual search agents answer questions about high-resolution images by iteratively deciding where to look. Reinforcement learning for these ag

agentsarxiv-cs-cv

HiRAE: Hierarchical Representation Autoencoding with Residual Budgets

arXiv:2609.37775v1 Announce Type: cross Abstract: Pretrained visual representations support image generation, but may not fully preserve the fine-grained details needed for faithful reconstruction. Me

Hybrid Neural Simulation-Based Inference for Robust Applications and Limited-Budget Scenarios

arXiv:2609.36044v1 Announce Type: cross Abstract: We develop two hybrid techniques that approach the performance of neural simulation-based inference (NSBI) analyses while substantially reducing the c

Tutorials

HybridCUA: Learning to Orchestrate GUI and CLI for Computer-Use Agents

arXiv:2609.38008v1 Announce Type: new Abstract: Computer use agents (CUAs) have demonstrated strong capabilities in completing digital tasks. However, existing CUAs either rely solely on graphical use

tutorialsarxiv-cs-cv

Hardware

I got thousands of DMs and it looks like @bot can't automatically analyze DMs (when @elonmusk?) so it will take me a few days to go through …

I got thousands of DMs and it looks like @bot can't automatically analyze DMs (when @elonmusk?) so it will take me a few days to go through all of them, sorry! If you don't get an answer, don't take i

hardwareclem-delangue--x

Information-theoretic receding-horizon active learning of nonlinear dynamical systems

arXiv:2609.36712v1 Announce Type: cross Abstract: Accurately learning nonlinear dynamics from a finite-duration experiment requires the efficient collection of informative data. We address this challe

Inter-patient ECG Arrhythmia Classification with LGNs and LUTNs

arXiv:2601.11433v2 Announce Type: replace Abstract: Deep Differentiable Logic Gate Networks (LGNs) and Lookup Table Networks (LUTNs) are demonstrated to be suitable for the automatic classification of

KUPAS MASTER: Distilling the Tacit Expertise of Master Practitioners into Agent-Ready Experience Corpora

arXiv:2609.37673v1 Announce Type: new Abstract: Experienced professionals know more than just facts and conclusions. They know which cues matter, why a judgment is reasonable, and which action to take

Applications

LAURA: Knowledge Distillation for Interpretable Ambiguous Clause Identification in Legal Contracts

arXiv:2609.36707v1 Announce Type: new Abstract: Legal contracts contain ambiguities that expose enterprises to financial and legal risks. Some ambiguities allow flexible interpretation without trigger

applicationsarxiv-cs-cl

Learning Meta-Skills for Agent Harness Design in Test-Time AI4AI

arXiv:2609.38143v1 Announce Type: new Abstract: Agent performance depends on both reasoning ability and the environment in which it acts. We study test-time AI-for-AI, asking how a Builder can learn t