Search: “deployment”

QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training

arXiv:2609.19513v1 Announce Type: new Abstract: High-quality pre-training data is a critical bottleneck for educational and STEM-specific language models targeting edge AI and on-device deployment whe

18 Sept 2026

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Hardware

RoboGPU: Accelerating GPU Collision Detection for Robotics

DGX agent

arXiv:2603.01517v2 Announce Type: replace-cross Abstract: Autonomous robots are anticipated to be deployed soon in domains ranging from transportation to healthcare and home assistance. Enabling auton

hardwarearxiv-cs-ro

18 Sept 2026

TripScore: Aligning LLMs for Real-World Travel Planning via Expert-Calibrated Reward

arXiv:2510.09011v4 Announce Type: replace Abstract: In our deployed travel-planning service, most users give minimal inputs or free-form requests rather than the structured constraint checklists assum

18 Sept 2026

Bias Amplification in Multi-Agent Network: How Biased Agents Shape Opinions and Rhetoric

model-releasesarxiv-cs-lg

arXiv:2609.18306v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in applications involving interaction between agents, where their output plays a role in collecti

Local Ai

BLADE: ReliaBle Dynamic Hardware-Aware SNN-ANN Boundary SeLection for Event-BAseD Object DEtection

arXiv:2609.17562v1 Announce Type: cross Abstract: Hybrid Spiking Neural Network (SNN)-Artificial Neural Network (ANN) architectures combine the energy efficiency of SNNs with the superior detection ac

local-aiarxiv-cs-ai

Cactus Needle 3: A Sliceable 8-29MB Automation Foundation Model That Matches DeepSeek v4 Flash

model-releasesr-localllama

Hey all, Henry from Cactus Compute here, I kinda wanted to share our latest model and get feedback from the family :) Needle 3 is a small foundation model for automation: you give it the functions you

Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents

arXiv:2609.17708v1 Announce Type: cross Abstract: Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that

Do Frontier Models Seek Safety Evidence Before Acting?

arXiv:2609.17865v1 Announce Type: new Abstract: Frontier models are often evaluated on how they respond to safety information once it is already in context. We study an earlier decision point: whether

ERPBench: A State-Grounded Evaluation Paradigm for Computer-Use Agents in Enterprise Software

arXiv:2609.17885v1 Announce Type: new Abstract: Computer-use agents that operate through screenshots and simulated actions are advancing rapidly, yet their evaluation remains anchored to general deskt

Faithful yet Collusive: Why Chain-of-Thought Monitoring Cannot Detect Collusion in LLM Pricing Agents under Oligopolistic Competition

arXiv:2609.18346v1 Announce Type: new Abstract: Large language models (LLM) deployed as autonomous pricing agents may sustain supracompetitive prices through tacit coordination. We develop a causal gr

Flexible-body Modeling, Kinematic Identification, and Assembly Accuracy of Overconstrained Spatial Linkages

model-releasesarxiv-cs-ro

arXiv:2609.17627v1 Announce Type: new Abstract: Overconstrained rational single-loop linkages are efficient, compact, and low-cost custom mechanisms, yet their deployment in industrial settings is lim

From a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale

arXiv:2609.18068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains such as housing screening. While alignment techniques mitigate explicit

safetyarxiv-cs-ai

Imitation Learning for Autonomous Driving in CARLA

arXiv:2609.17757v1 Announce Type: new Abstract: Behavioral cloning trains a policy offline on expert demonstrations, but deployment is closed loop: each action affects the observations the policy rece

Long-Lived Characters, Local Inference: Incremental Memory Maintenance for Game NPCs

model-releasesarxiv-cs-cl

arXiv:2609.18935v1 Announce Type: new Abstract: A game character should not have to reread its entire life before every conversation. For locally deployed language-model characters, however, revising

M-SQE: Multilingual Skill Quality Estimation for Enhancing Language Equality in Agentic Skill Use

arXiv:2609.18445v1 Announce Type: new Abstract: Agent skills, reusable procedural documents that extend LLM agents beyond their parametric memory, have become an important interface for deploying agen

agentsarxiv-cs-cl

PACT: Can Enterprise AI Assistants Be Trusted Under Pressure?

arXiv:2609.18605v1 Announce Type: cross Abstract: As corporate AI adoption continues to grow, enterprise-grade LLM agents are being deployed into sensitive contexts such as hiring, healthcare, and fin

Reinforcement Learning for Real-Time Vision-Language-Action Policies

model-releasesarxiv-cs-lg

arXiv:2609.18207v1 Announce Type: cross Abstract: Reinforcement learning fine-tuning on top of large, pretrained Vision-Language-Action (VLA) models offers promise for highly reliable robot deployment

REQAP: Resilient Weight Packing and Quantization for Edge DNN Acceleration

arXiv:2609.17555v1 Announce Type: cross Abstract: Efficient deployment of Deep Neural Networks (DNNs) on edge accelerators requires aggressive model compression while maintaining reliability in fault-

Selective Prediction and Uncertainty-Aware Referral for Pap Smear Classification

arXiv:2609.17545v1 Announce Type: new Abstract: Deep learning models for cervical cytology are almost always evaluated as if every prediction must be acted upon, yet a screening system deployed alongs

researcharxiv-cs-cv

Taming the Agentic RAN: Stability-Guaranteed Arbitration of Autonomous AI Agents in O-RAN

arXiv:2609.18857v1 Announce Type: cross Abstract: The O-RAN control plane is becoming agentic: autonomous AI agents, deployed as rApps by different vendors, independently close control loops over shar

A Decision-Support Audit Protocol for Supervision Drift in Proxy-Labeled Credit-Risk Prediction

arXiv:2609.16102v1 Announce Type: cross Abstract: Credit-risk models are trained on proxy labels and deployed under temporal and segment change, yet no single transfer metric separates base-rate shift

Carry-Through Checksum: A Lightweight Fault-Detection for CNN Inference at the Edge

arXiv:2609.16742v1 Announce Type: cross Abstract: Convolutional Neural Networks (CNNs) are increasingly deployed in safety-critical edge applications, where soft errors can silently corrupt inference

safetyarxiv-cs-lg

End-to-End Latency-Minimizing and Load-Balanced Request Scheduling for Edge LLM Inference in Agentic AI Services

arXiv:2609.17193v1 Announce Type: new Abstract: Large language model (LLM)-powered agentic AI services increasingly demand low-latency inference, motivating the deployment of LLMs across distributed e

Fleet-To-Lab: A Transfer Learning Framework For Lunar Rover Slippage Estimation Via Model Fusion

arXiv:2609.17187v1 Announce Type: new Abstract: Accurate wheel slip estimation is essential for autonomous lunar rover mobility and navigation. Machine Learning models trained on terrestrial data gene

agentsarxiv-cs-ro

FlexEE: Self-Speculative and KV-Compatible Early Exiting for Offloading-Aware LLM Inference

arXiv:2609.17008v1 Announce Type: new Abstract: Large language model (LLM) inference is often constrained by both computation and memory, especially in offloading-based deployments where model weights

GRACE: Geometry- and Ray-Aware Camera-Efficient Multi-View Pedestrian Tracking

arXiv:2609.16872v1 Announce Type: new Abstract: Reducing the number of cameras reduces the deployment cost but removes views that correct BEV responses stretched away from true pedestrian positions by

researcharxiv-cs-cv

LCAP: Population-Informed Latent Chip Adaptation from Few Output Probes for Photonic Neural Networks

arXiv:2609.16823v1 Announce Type: new Abstract: Photonic neural networks (PNNs) offer efficient analog inference, but parameters optimized under ideal device models can degrade after fabrication, crea

researcharxiv-cs-lg

MLCommons Sets Participation Record with New MLPerf Inference v6.1 Benchmark Results

Latest version of the benchmark introduces two new tests for emerging AI deployment patterns, including Agentic Inference The post MLCommons Sets Participation Record with New MLPerf Inference v6.1 Be

model-releasesmlcommons

Nationally Consistent, Locally Incomplete: A Bayesian Remote-Sensing Audit of Rooftop Photovoltaic Registries

arXiv:2609.16294v1 Announce Type: cross Abstract: Tracking the energy transition requires reliable statistics on renewable deployment. Rooftop photovoltaics (PV) are especially hard to track, owing to

safetyarxiv-cs-lg

Online Geometric Change Detection via Scene Decomposition

arXiv:2609.17302v1 Announce Type: new Abstract: Autonomous robots are increasingly deployed on long duration single- and multi-session missions in dynamic environments, where the ability to identify e

agentsarxiv-cs-ro

Residual Fault Adaptation for Dexterous In-Hand Manipulation Under Runtime Joint Faults

arXiv:2609.17404v1 Announce Type: new Abstract: Dexterous in-hand manipulation requires coordinated control of multiple actuated joints, and a runtime joint fault can abruptly disrupt the contact conf

safetyarxiv-cs-ro

Schema-Adaptive Action-Conditioned JEPA for Cross-Machine CNC Transfer under Partial Sensor Overlap

arXiv:2609.16071v1 Announce Type: cross Abstract: Cross-machine deployment of industrial world models requires transfer across changes in dynamics, sensing interfaces, sampling regimes, and control un

Shared-Prefix KV Reuse Across Standard LoRA Adapters: Quality and Serving Tradeoffs

arXiv:2609.17109v1 Announce Type: new Abstract: A common small-model deployment runs one shared backbone with several LoRA specialists that answer over the same context. Serving them naively re-prefil

What Breaks Under Pruning in Smart Homes, and When? Evaluating LLM Degradation Across Architectures and Task Complexity

arXiv:2609.17515v1 Announce Type: new Abstract: Pruning can reduce the deployment cost of large language models (LLMs), but its impact on context-grounded tool calling remains poorly understood. We sy

researcharxiv-cs-cl

A Lifecycle Cost Analysis of Smart-Contract-Coordinated Federated Learning Marketplaces

arXiv:2609.13170v1 Announce Type: cross Abstract: Blockchain-enabled Federated Learning (FL) marketplaces enable collaborative model training among mutually distrustful participants through smart cont

researcharxiv-cs-lg

Tutorials

Aerial Wildfire Suppression Planning with a Hybrid CNN-Cellular Automata Fire Model

arXiv:2606.13633v2 Announce Type: replace-cross Abstract: Aerial wildfire suppression requires decisions about when, where, and how to deploy limited aircraft. We present an intervention-design framew

tutorialsarxiv-cs-lg

Assistance Torque Estimation via Dynamics-Aware Optimization for Lower-Limb Exoskeleton in Complex Environments

arXiv:2609.15352v1 Announce Type: new Abstract: Ground-truth human joint torque estimation relies on motion capture systems, which suffer from limited outdoor usability and significant deployment expe

safetyarxiv-cs-ro

Beyond Noise: Understanding and Overcoming Temperature Effects in Analog DNN Inference

arXiv:2609.15527v1 Announce Type: new Abstract: The energy efficiency of analog computing makes it one of the most promising candidates for deploying resource-intensive machine learning workloads on c

researcharxiv-cs-lg

Carbon-Aware Routing for Function Calling in Edge-Cloud LLM Systems

arXiv:2609.13559v1 Announce Type: new Abstract: Large Language Models (LLMs) with function-calling capabilities are becoming critical for modern agentic AI systems. Nevertheless, current deployments t

Data-Efficient Agentic Graph Domain Adaptation via Reliability-Aware Prototype Learning

arXiv:2609.14045v1 Announce Type: new Abstract: Agentic learning systems are often required to adapt after deployment by observing new data and reusing prior knowledge under limited supervision or fee

agentsarxiv-cs-lg

Decentralized Multi-Robot Task Allocation Under Degraded Communication: A Benchmark of Performance, Reliability, and Computation

model-releasesarxiv-cs-ro

arXiv:2609.13711v1 Announce Type: new Abstract: Selecting a decentralized Multi-Robot Task Allocation (MRTA) method for embedded deployment on autonomous platforms requires considering more than route

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

safetyarxiv-cs-ai

Local Ai

DynSTEER: Dynamic Stage-wise Trajectory Evaluation and Execution-time Review for Agents

arXiv:2609.14637v1 Announce Type: new Abstract: Large language model agents are increasingly deployed for long-horizon task execution. However, current evaluation paradigms face three major limitation

local-aiarxiv-cs-ai

FLoKD: Adaptive Knowledge Distillation for Federated Low-Rank LLM over Wireless Networks

arXiv:2609.13580v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across a wide range of natural language processing tasks. However, conventional fine-

ForeSight: Enhancing Risk Monitoring via Early Safety Signal Distillation

arXiv:2609.13737v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed, the generation of harmful content has become a critical safety concern. Existing safeguards o

safetyarxiv-cs-cl

Fusing Spectral Signatures and Activation Clustering for Backdoor Detection in Healthcare Imaging Models: Method, Implementation, and Evaluation

model-releasesarxiv-cs-lg

arXiv:2609.14290v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in healthcare imaging pipelines for diagnostic support, and training-time attacks against them are a

Tutorials

Generalized Correctness Models: Learning Calibrated and Model-Agnostic Correctness Predictors from Historical Patterns

arXiv:2509.24988v2 Announce Type: replace-cross Abstract: Generating accurate and calibrated confidence estimates is critical for deploying LLMs in high-stakes or user-facing applications, and remains

tutorialsarxiv-cs-ai

Hardware-Aware Learned Representation Compression for Distributed In-Sensor Vision

arXiv:2609.13947v1 Announce Type: cross Abstract: In-sensor computing reduces the cost of transmitting high-resolution image data by performing early-stage processing near the sensor. However, the log