Search: “deployment”

RegenHarness: A Robot Agent Harness with Evidence-Gated Recursive Self-Improvement

arXiv:2609.27612v1 Announce Type: new Abstract: Long-horizon robot execution requires a clear distinction between a model's proposal, a controller's termination, and verified task completion. We prese

agentsarxiv-cs-ro

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Local Ai

Repairability of Inexact Solvers in Recursive State Estimation with Machine Learning

DGX agent

arXiv:2609.28425v1 Announce Type: cross Abstract: Recursive state estimation often executes approximate numerical solutions inside a feedback loop, where highly accurate local steps do not guarantee b

local-aiarxiv-cs-lg

24 Sept 2026

Rolling Conformal Prediction in Sequential Model Training

arXiv:2609.26951v1 Announce Type: cross Abstract: We introduce Rolling Conformal Prediction (rolling-CP), a distribution-free predictive inference method for the setting of sequential model training.

Local Ai

Safety-Filtered Distributed Koopman-MPC

arXiv:2609.27463v1 Announce Type: new Abstract: Distributed model predictive control (DMPC) often constructs both predictions and collision constraints from neighbor trajectories, so packet loss can r

local-aiarxiv-cs-ro

Shutdown Sabotage Propensities in Multi-Agent Systems

arXiv:2609.28274v1 Announce Type: new Abstract: The final safeguard against rogue AI behavior is the human ability to shut systems down. It has been theorized that when an AI is instructed to perform

agentsarxiv-cs-ai

SlackDrive: Reclaiming Runtime Slack for Adaptive Driving Inference

arXiv:2609.28064v1 Announce Type: new Abstract: Driving world-action models improve planning by coupling multimodal reasoning with future prediction, but their growing inference cost increasingly conf

safetyarxiv-cs-ai

Text Scores Can Miss Waveform Use: A Qwen2-Audio Quantization Case Study

arXiv:2609.26823v1 Announce Type: cross Abstract: Post-training quantization of speech language models is often summarized with text-output scores and nominal bit widths. Those numbers alone do not es

applicationsarxiv-cs-cl

The Like Trap: Multi-Stage Poisoning against Agents in Similarity-based Recommendation Systems

arXiv:2609.27155v1 Announce Type: cross Abstract: With recent advancements in large language models (LLMs) and LLM-based agents, these agents are becoming increasingly autonomous and gaining broader a

agentsarxiv-cs-ai

UniDataAgent: An Ontology-Grounded Agent for Enterprise Question-to-Report Automation

arXiv:2609.27257v1 Announce Type: new Abstract: Enterprise data agents must preserve organization specific semantics, not just translate questions into queries. We present ChinaUnicom DataAgent (UniDa

agentsarxiv-cs-cl

Validation and Simulation Catch Different Errors: Four Levels of Evaluation for LLM-Generated Circuits

arXiv:2609.26830v1 Announce Type: cross Abstract: Simulation success is not equivalent to structural correctness for LLM-generated circuits. We define and measure four evaluation levels -- schema vali

What Confidence Routing Is Actually Doing: Auditing Routing, Calibration, and Commitment in Multi-Agent Deliberation

model-releasesarxiv-cs-cl

arXiv:2609.27822v1 Announce Type: cross Abstract: A common multi-agent design asks agents to report confidence and lets the highest-scoring agent speak next, implicitly using one scalar both to route

'What's That Sound?': A Versatile, Robust, and Lightweight Convolutional Transformer for Environment Sound Recognition

arXiv:2609.27762v1 Announce Type: cross Abstract: The conventional hearing aid is both costly and lim- ited in usage, as it is not intended to detect non-speech audio. Our objective is to develop a ma

safetyarxiv-cs-lg

When Accuracy Gaps Fail to Certify: Auditing Cross-Domain Recalibration of LLM Judges

arXiv:2609.27954v1 Announce Type: new Abstract: A scalar recalibration map fitted for an LLM judge on one task can fail when the task distribution changes, but the source-target accuracy gap is often

When Adaptation Hurts: Split Sensitivity and Person-Level Negative Transfer in Federated Wearable Onboarding

arXiv:2609.27819v1 Announce Type: new Abstract: Federated wearable models eventually serve people absent from source training, but favorable average accuracy does not establish that unlabeled onboardi

When Clients Are Orchestrated: Strategic Gradient Manipulation to Defeat Federated Learning Servers with Efficient Defense

arXiv:2609.27124v1 Announce Type: cross Abstract: Federated Learning enables decentralized model training by exchanging model updates--rather than raw data--with a central parameter server (PS). While

Annual Earth-observation embeddings encode wildfire disturbance and support simplified burned area mapping

model-releasesarxiv-cs-cv

arXiv:2609.25731v1 Announce Type: new Abstract: Medium-resolution (10-30 m) burned area mapping is vital for monitoring wildfires and their impacts, but remains difficult to scale. Existing methods re

'As a Language Model...': Chat Template Switches LLM Self-Referential Voice and Activation Steering Reproduces It

arXiv:2609.25021v1 Announce Type: cross Abstract: Large Language Models (LLMs) tend to add disclaimers like 'I'm just an AI' when asked about something related to themselves. The self-reports from suc

safetyarxiv-cs-cl

BDSLI: A hybrid CNN-Transformer model for Bengali Sign Language interpretation

arXiv:2609.26088v1 Announce Type: new Abstract: This study introduces a novel hybrid CNN-Transformer architecture to address the limited progress in Bengali SLR, focusing on isolated sign word recogni

applicationsarxiv-cs-cv

Beyond Raw Engagement: A Counterfactual Observability Framework for Recommender Systems at Netflix

arXiv:2609.22747v1 Announce Type: cross Abstract: Understanding the performance of large-scale recommender systems remains an underexplored challenge, especially for content creators and model develop

safetyarxiv-cs-ai

CableVLA: Simulation-Privileged Global-Local Representation Learning for Cable Routing

model-releasesarxiv-cs-ro

arXiv:2609.25606v1 Announce Type: new Abstract: Cable routing requires coordinated control of global cable topology and changing local contacts. We present CableVLA, an end-to-end multimodal vision-la

Calibration as a First-Class Criterion in LLM Evaluation

arXiv:2609.26489v1 Announce Type: new Abstract: Calibration of language models -- the alignment between expressed or implicit confidence and empirical correctness -- is a well-studied subfield within

safetyarxiv-cs-cl

CompKV: Compensation-Aware KV Selection for Long-Context LLM Inference

arXiv:2609.26300v1 Announce Type: new Abstract: Despite their strong performance, large language models (LLMs) are bottlenecked by KV cache memory traffic during long-context inference. Sparse attenti

Controlling risks of AI in chemical science with agents

arXiv:2312.06632v2 Announce Type: replace Abstract: Artificial intelligence is rapidly advancing scientific discovery, but this progress carries risks of misuse, such as the creation of harmful substa

Diffusion Drafts, AR Verifies: Accelerating Document OCR with Self-Speculative Decoding

model-releasesarxiv-cs-cl

arXiv:2609.26638v1 Announce Type: new Abstract: Autoregressive OCR vision-language models accurately convert document images into text and structured markup, but require one sequential decoding step p

DUMA-Bench: A Dual-Control Multi-Agent Benchmark for Evaluating LLM Agent Security

arXiv:2609.24662v1 Announce Type: new Abstract: LLM-based agents increasingly operate in environments where they interact with users, tools, and external systems. Yet most security evaluations assume

DVA-Neurons: Design and Verification of Adaptive LIF Neurons: From Single-Neuron Dynamics to Multi-Neuron Spiking Networks

arXiv:2609.22775v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer a promising path toward ultra-low-power artificial intelligence inference by emulating the event-driven computation

Efficient Iterative Retrieval with Heterogeneous Batching

model-releasesarxiv-cs-cl

arXiv:2609.25405v1 Announce Type: cross Abstract: Modern information retrieval increasingly employs both embedding and generative models to handle complex queries. However, current serving systems suf

ENPIRE: Agentic Robot Policy Self-Improvement in the Real World

arXiv:2606.19980v2 Announce Type: replace Abstract: Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bo

Evaluating Accuracy and Probabilistic Reliability of Zero-Shot Time Series Foundation Models

arXiv:2609.25788v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) promise a paradigm shift toward zero-shot forecasting by eliminating task-specific training. However, existing wor

Explainable Recommendations at Scale: LLM Rationales for YouTube Music Artist Discovery

arXiv:2609.23877v1 Announce Type: new Abstract: Modern music streaming platforms face a persistent tradeoff: exploiting familiar content versus driving the exploration of novel items. While users freq

applicationsarxiv-cs-ai

Federating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach

arXiv:2609.25082v1 Announce Type: new Abstract: Quantum machine learning (QML) is increasingly recognized as one of the most promising near-term applications of quantum computing, viewed as a next-fro

Hardware

Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs

arXiv:2609.26796v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to autoregressive LLMs by enabling non-autoregressive text gene

hardwarearxiv-cs-cl

From Code to Requirements: Agentic Reverse Engineering of Business Rules at Enterprise Scale

arXiv:2609.22719v1 Announce Type: cross Abstract: Business requirements for enterprise software systems are rarely captured in structured form; the logic resides instead in source code, configuration

From IceCube to IT-Sphere: A Hybrid Quantum-Classical GNN for Banking IT Root Cause Analysis

arXiv:2609.22822v1 Announce Type: cross Abstract: We present Hybrid Quantum Root Cause Analysis (HQ-RCA), an industrially grounded workflow for root cause analysis in banking IT operations, built on a

From Research Frontier to Laboratory Bench: Design of a Four-Tier Experimental Teaching System for Multimodal Medical Image Intelligent Diagnosis

arXiv:2609.22790v1 Announce Type: new Abstract: Undergraduate programmes in intelligent medical engineering are expanding, yet laboratory curricula lag behind the multimodal, long-tailed, and distribu

safetyarxiv-cs-ai

Local Ai

Generalizing Manipulation Skills with a Local Coding Agent

arXiv:2609.26499v1 Announce Type: new Abstract: Today, progress in open-weight language models enables systems capable of writing, executing and debugging code while still running on a single workstat

local-aiarxiv-cs-ro

GTR: Gated Token Recurrence for Efficient Dense Prediction

arXiv:2609.26590v1 Announce Type: cross Abstract: Self-attention-based vision backbones perform well on dense prediction, but the quadratic computational cost of global softmax attention limits their

Hierarchical Floorplan-Guided Vision-Language Exploration for Embodied Question Answering

arXiv:2609.26360v1 Announce Type: new Abstract: Embodied Question Answering (EQA) requires an agent to explore a previously unseen environment, gather relevant information, and answer questions about

agentsarxiv-cs-ro

How Many Pixels Is a Digit Worth? Place-Aware Coordinate Entropy for GUI Agent Confidence Estimation

arXiv:2609.24277v1 Announce Type: new Abstract: GUI agents predict click coordinates as digit-token sequences, but standard text-LLM confidence estimation methods rank correct clicks from wrong ones o

agentsarxiv-cs-ai

Impact Is Not Invalidation: Ask About the Claim, Not the Diff

arXiv:2609.25130v1 Announce Type: new Abstract: Memory systems for coding agents must decide, when a repository changes, which of their stored claims have become false. Content anchoring invalidates a

researcharxiv-cs-cl

IndustrialVLA-Bench: A Traceable Multi-Axis Evaluation of Open Robot Policy Models

model-releasesarxiv-cs-ro

arXiv:2609.25562v1 Announce Type: new Abstract: Open robot policies increasingly follow two paradigms: vision-language-action models (VLAs) directly map observations and instructions to actions, where

Leaky-integrator reconstruction: taming error accumulation in recursive differenced time-series forecasting

arXiv:2609.23378v1 Announce Type: new Abstract: We introduce leaky-integrator reconstruction, a training-free method that cures the error accumulation of recursive differenced forecasting. Our first c

researcharxiv-cs-ai

Local Ai

Leveraging Vision-Based Point Cloud Map Priors for Camera-Based 3D Object Detection and Online Vectorized HD Mapping

arXiv:2609.26325v1 Announce Type: cross Abstract: Camera-based 3D object detection and online vectorized HD mapping provide compact scene representations for autonomous driving, but both depend on acc

local-aiarxiv-cs-ro

LiDAS: Lighting-driven Dynamic Active Sensing for Nighttime Perception

arXiv:2512.08912v2 Announce Type: replace-cross Abstract: Nighttime environments pose significant challenges for camera-based perception, as existing methods passively rely on the scene lighting. We i

applicationsarxiv-cs-ro

Tutorials

Lifelong Learning of Video Diffusion Models From a Single Video Stream

arXiv:2406.04814v4 Announce Type: replace-cross Abstract: Video diffusion models can enable embodied agents to anticipate plausible futures from the recent past, but they are typically trained offline

tutorialsarxiv-cs-lg

Linear probing enables Ship-Radiated Noise recognition with pretrained audio embeddings

arXiv:2601.08358v2 Announce Type: replace Abstract: Even though the ocean covers the majority of the planet's surface, it remains the least explored ecosystem. As light and radio waves do not propagat

LoRango: It Takes Two LoRAs to Unlock Hidden Behaviors in Diffusion Models

arXiv:2609.25884v1 Announce Type: cross Abstract: Users commonly combine multiple Low-Rank Adaptation (LoRA) adapters to personalize images with different subjects, styles, and visual attributes. Yet

safetyarxiv-cs-cv

MedVLA: A Hierarchical Vision-Language-Action Framework for Closed-Loop Precision Medical Robot Manipulation

arXiv:2609.25756v1 Announce Type: new Abstract: Precision medical robotics demands adaptive decision-making under strict safety, interpretability, and execution constraints. Although recent Vision-Lan

safetyarxiv-cs-ro