Search: “deployment”

Robust Workflow Generation via Adversarial Learning for Audio Deepfake Detection

arXiv:2609.20063v1 Announce Type: cross Abstract: The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security r

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Model Releases

Safety Beyond the Interface: Detecting Harm via Latent States in Large Language Models

DGX agent

arXiv:2609.19472v1 Announce Type: new Abstract: Autonomous systems increasingly rely on Large Language Models (LLMs) yet the safety infrastructure surrounding these models introduces latency and compu

model-releasesarxiv-cs-ai

18 Sept 2026

SeetaPsych v1.0: An Open-source Computer Vision Toolkit for Behavior-based Psychological Measurement

arXiv:2609.19719v1 Announce Type: new Abstract: Automated visual analysis opens new avenues for behavior--based psychological measurement. Nevertheless, existing technological modules are typically sc

researcharxiv-cs-cv

Local Ai

Selective Cotton Boll Localization for Robotic Harvesting: Evaluation of Deep Learning Vision Models Under Field Conditions

arXiv:2609.19592v1 Announce Type: new Abstract: This study developed and evaluated a deep-learning-based perception framework for selective robotic cotton picking. The dataset contained 1,008 annotate

local-aiarxiv-cs-cv

SlugTrails: An Egocentric Benchmark for Floor Plan Localization in Large Buildings

model-releasesarxiv-cs-cv

arXiv:2609.19876v1 Announce Type: new Abstract: Floor-plan-based indoor visual localization enables infrastructure-free positioning, but most methods are developed and evaluated in small residential e

StageGuard: Learning Stage Transitions for Long-Horizon Robot Tasks via Agentic Distillation

arXiv:2609.20791v1 Announce Type: new Abstract: Hierarchical planning frameworks combine skills from multiple robot control policies for long-horizon task execution, where determining when to terminat

Strategic Transformer for Resource-Constrained Multi-Object Navigation in Ultra-Large-Scale Environments

model-releasesarxiv-cs-ro

arXiv:2609.20227v1 Announce Type: new Abstract: Resource-constrained multi-object navigation in vast indoor environments (>2,000ext{ m}^2) poses significant challenges for efficiency and strategic pla

Stress-testing Alignment Midtraining

arXiv:2609.20412v1 Announce Type: cross Abstract: When aligning frontier models through post-training techniques, it is not possible to directly demonstrate all of the behaviours we want a model to ex

TacSushi: Tactile-Grounded World-Action Modeling for Dexterous Sushi Manipulation

arXiv:2609.19613v1 Announce Type: cross Abstract: Dexterous food manipulation requires control under deformation, occlusion, and uncertain contact. We present TacSushi, a tactile-grounded, Cosmos3-bas

Tutorials

Tailored to you: longitudinal effects of personalising language models

arXiv:2609.20077v1 Announce Type: new Abstract: Interest in developing personalised language models is rapidly growing. While personalisation is often viewed as a mechanism to better serve diverse use

tutorialsarxiv-cs-ai

The Neutral Mask: How Alignment Training Provides Shallow Alignment while Leaving Partisan Structure Intact in a Large Language Model

model-releasesarxiv-cs-cl

arXiv:2606.09735v2 Announce Type: replace Abstract: The ambition behind alignment training is to make large language models safe and useful. The primary mechanisms, reinforcement learning from human f

TinyCNN: A 193K-Parameter Network for On-Device Plant Disease Detection, with a Cross-Dataset Robustness Diagnosis

model-releasesarxiv-cs-cv

arXiv:2609.20290v1 Announce Type: new Abstract: Detecting crop disease early is central to sustainable agriculture and food security under United Nations Sustainable Development Goal 2 (Zero Hunger),

Towards High-DoF Dexterous Manipulation through VLA Post-Training

arXiv:2609.19666v1 Announce Type: new Abstract: Imitation-learned vision--language--action (VLA) foundation models acquire broad manipulation capabilities by scaling robot data across tasks and embodi

TRACE: Accountable Agentic Retrieval for Source Discovery in Digital Archives

arXiv:2609.19897v1 Announce Type: new Abstract: Historical archives pose a difficult retrieval problem for retrievalaugmented generation systems: documents are OCR-degraded, heterogeneous across genre

TraceFlow: Guiding Frozen Flow-Matching Robot Policies with Success and Failure Traces

arXiv:2609.20646v1 Announce Type: new Abstract: A vision-language-action (VLA) policy with a flow-matching action expert generates each action chunk (a short command sequence) by integrating a learned

Transformer fault diagnosis using an efficient simulation-driven variational quantum classifier with domain-aware feature encoding

arXiv:2609.20214v1 Announce Type: cross Abstract: Early transformer fault diagnosis is challenged by nonlinear dissolved-gas interactions, overlapping fault signatures, and limited labeled data, while

ULOHA: An Underwater Bimanual Robot System for Robot Learning

arXiv:2609.19200v1 Announce Type: new Abstract: Underwater visuomotor policy learning has focused primarily on single manipulators, while bimanual imitation learning has been studied largely in air. W

UniExo: Unified Multi-Skill Policies for Musculoskeletal Locomotion and Co-Adaptive Exoskeleton Control

arXiv:2609.19690v1 Announce Type: cross Abstract: Daily locomotion encompasses diverse activities and frequent transitions between them, yet most exoskeleton controllers are designed for a single acti

safetyarxiv-cs-lg

ViLoMan: Learning Visual-Proprioceptive Whole-Body Loco-Manipulation Skills for Humanoid Robots

arXiv:2609.19340v1 Announce Type: new Abstract: Humanoid loco-manipulation requires adaptive whole-body coordination to seamlessly integrate locomotion and physical interaction. Despite recent advance

When Does Retrieval Help Time-Series Forecasting?

arXiv:2609.20193v1 Announce Type: new Abstract: Retrieval plug-ins supply a deep forecaster with information its lookback window cannot carry. Published evaluations report consistent gains, and each c

researcharxiv-cs-lg

Winning a Won Game: Strict Reach-Avoid-Stay Control Barrier Functions for High-Dimensional Black-Box Systems

arXiv:2609.19449v1 Announce Type: new Abstract: Robots must complete their tasks and maintain the achieved outcomes while avoiding safety failures at all times. Strict reach-avoid-stay (sRAS) formaliz

WorldContact: A Contact-Centric World Model for Scalable Robot Learning

arXiv:2609.19600v1 Announce Type: new Abstract: Adapting robots to new objects and tasks requires interaction experience that can be costly to obtain. We present WorldContact, a contact-centric world

Zarya: A Hybrid Autoregressive--Masked Diffusion Language Model with Flexible Training and Dual-Mode Inference

arXiv:2609.19868v1 Announce Type: cross Abstract: Autoregressive language models (ARMs) are constrained by sequential, left-to-right generation, while masked diffusion models (MDMs) enable parallel de

researcharxiv-cs-ai

A Comprehensive Review of Generative Physical Artificial Intelligence

arXiv:2609.18111v1 Announce Type: cross Abstract: The integration of large-scale foundation models with physical embodiments has led to significant advancements in robotics known as Generative Physica

A Convergence Framework for Deep V-Learning: Error Propagation and Sharp Action-Gap Bounds

arXiv:2609.18782v1 Announce Type: new Abstract: We establish convergence bounds for deep V-learning with horizon H. The algorithm fits a scalar value function to targets from executed transitions and

safetyarxiv-cs-lg

Agents

A Study of the Reliability of Agentic AI-Generated Programs

arXiv:2609.18298v1 Announce Type: cross Abstract: Agentic-AI based software development offers the promise of faster completion of the software, greater programmer efficiency, and more reliable code.

agentsarxiv-cs-ai

Hardware

Accelerating Stateful Network Applications with Performance Prediction on SoC SmartNICs

arXiv:2410.22229v2 Announce Type: replace-cross Abstract: Offloading stateful network functions to multi-threaded SoC SmartNICs promises significant performance and cost benefits. However, realizing t

hardwarearxiv-cs-cl

Adaptive hybrid coupling with operator inference, the overlapping Schwarz alternating method and reinforcement learning

arXiv:2609.17837v1 Announce Type: cross Abstract: Hybrid domain decomposition methods provide a flexible framework for coupling full order models (FOMs) and reduced order models (ROMs), but typically

An Empirical Evaluation of Cost-Efficient Large Language Models on Algorithmic Programming Tasks

arXiv:2609.18052v1 Announce Type: cross Abstract: This study empirically evaluates whether cost-efficient Large Language Models (LLMs) can be trusted to generate enterprise code to a written specifica

APGEM: Adaptive Policy-Guided Error Mitigation for Quantum Reinforcement Learning on a Real-World CVRP Case Study

arXiv:2609.18219v1 Announce Type: cross Abstract: Quantum Reinforcement Learning (QRL) represents policies as variational quantum circuits (VQCs), making it attractive for combinatorial optimization s

Ask the Tool, Don't Guess: Agent Tool Calls Hold Their Progress, and the Serving System Should Read It

arXiv:2609.18849v1 Announce Type: cross Abstract: An agentic request spends substantial wall-clock time waiting for tools, and its KV cache holds GPU memory the whole time. Serving systems decide whet

CALOS: Control-Affine Lyapunov On-manifold Safety Layer for Safe Deep Reinforcement Learning for Quadrotors

arXiv:2609.17758v1 Announce Type: cross Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety

Characterizing Replay Retention Under Dynamics Shift in Model-Based Reinforcement Learning

arXiv:2609.18167v1 Announce Type: cross Abstract: Adapting to changes in robot dynamics requires learning from new data without discarding experience that may still be useful. In continual model-based

Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery

arXiv:2609.18460v1 Announce Type: new Abstract: How does a multi-agent system evolve from a local deviation into collective loss of control? We propose an epidemic explanation organized around acciden

Decodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition

arXiv:2609.18080v1 Announce Type: new Abstract: Linear probes can decode safety-relevant concepts such as truthfulness from language-model activations, but probe accuracy may show only decodability, n

Decoder-Agnostic Token Merging for Vision Transformers: A Systematic Study of G2TM

arXiv:2609.18279v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved state-of-the-art performance across a range of computer vision tasks, mainly thanks to the self-attention mecha

researcharxiv-cs-cv

Designing Agentic AI Workflow Portfolios under Imperfect Selection and Compute Cost

arXiv:2609.18126v1 Announce Type: new Abstract: Agentic AI systems often approach the same task through multiple workflows that differ in reasoning strategy, verification structure, and compute cost.

DistAL: Distance-based Advantage Learning for VLA Fine-Tuning

arXiv:2609.18392v1 Announce Type: new Abstract: Vision-language-action models (VLAs) have trans- formed the field of robotic manipulation in recent years by combining the semantic understanding of LLM

DRT&R: Direct Radar Teach & Repeat

arXiv:2609.17766v1 Announce Type: new Abstract: Radar-based navigation is appealing for its robustness to adverse conditions involving airborne particles, such as precipitation, dust, fog, and smoke,

researcharxiv-cs-ro

EdgeReMIND: A Scalable, Top-Ranked Memorization Baseline for Temporal Multi-Relational Link Prediction

arXiv:2609.17916v1 Announce Type: new Abstract: Temporal link prediction on the Temporal Graph Benchmark 2.0 (TGB 2.0) faces a scalability ceiling: on the benchmark's three largest datasets, every exi

Evidence-Grounded Agentic Formulation Development in an Autonomous Laboratory

arXiv:2609.19099v1 Announce Type: new Abstract: Self-emulsifying drug delivery systems (SEDDS) can improve the oral bioavailability of poorly soluble drugs, but identifying high-performing formulation

EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents

arXiv:2609.17632v1 Announce Type: new Abstract: Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-

Agents

EvoUndo: Recoverability-Constrained Self-Evolution for LLM Agent Harnesses

arXiv:2608.28363v2 Announce Type: replace Abstract: LLM agents increasingly modify their own prompts, tools, middleware, resources, and execution harnesses at runtime. Such self-evolution can improve

agentsarxiv-cs-ai

FedASAP: Activation Statistics-driven Structured Adaptive Pruning for Efficient Personalized Federated Learning for Lesion Segmentation on brain MRI

model-releasesarxiv-cs-cv

arXiv:2609.19042v1 Announce Type: cross Abstract: In medical imaging, developing robust deep learning models requires data from various domains. However, regulatory policies protecting patient privacy

FRAUDSkill: Structured Frozen-Weight Skill Optimization for Audio Anti-Fraud Detection

model-releasesarxiv-cs-cl

arXiv:2609.18766v1 Announce Type: cross Abstract: Large audio-language models have shown promise for anti-fraud detection by directly processing speech and reasoning over fraud-related evidence. Their

From Gameplay to Policy: Towards Scalable Robot Data Collection via Gamified Robot-Free Interaction

model-releasesarxiv-cs-ro

arXiv:2609.18650v1 Announce Type: new Abstract: Learning generalizable robot manipulation policies requires large-scale and diverse interaction data, yet collecting real-world demonstrations remains c

From Pixels to Pairs: A Comprehensive Benchmark of LLM-Based Key-Value Extraction in Noisy Document Settings

model-releasesarxiv-cs-cl

arXiv:2609.17538v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for structured information extraction from documents, yet their behavior under realistic OCR noise re

Function-Preserving Data Generation for Zero-Shot Real-to-Sim-to-Real Manipulation

arXiv:2609.18293v1 Announce Type: new Abstract: Robotic data generation is a promising paradigm for scaling robot learning without collecting large-scale real-world data. However, generating geometric