Search: “deployment”

Autonomous Repair for Multi-Agent Systems via Monte-Carlo Tree Search

arXiv:2607.29055v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly deployed to solve complex tasks. In case of incorrect or unsatisfactory outputs, users have to manually loc

Human

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Model Releases

Benchmarks Are Not Validation: A System-Level View of Financial LLM Applications

DGX agent

arXiv:2607.28840v1 Announce Type: new Abstract: Large language models are increasingly deployed in financial applications that combine retrieval, proprietary data, tool use, orchestration logic, monit

model-releasesarxiv-cs-cl

3 Aug 2026

Local Ai

CENDRe: Concept Extraction with Natural Domain Representations

arXiv:2607.29621v1 Announce Type: cross Abstract: Convolutional neural networks (CNNs) are widely used for time-series classification, but their deployment in critical domains requires understanding t

local-aiarxiv-cs-ai

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation

model-releasesarxiv-cs-ro

arXiv:2602.11885v2 Announce Type: replace Abstract: Diffusion-based policies generalize poorly in semantic manipulation, a key obstacle to real-world deployment, because text-only instructions cannot

Data Turnstile: A Scalable Open Framework for Function-Calling Data Generation

model-releasesarxiv-cs-cl

arXiv:2607.29250v1 Announce Type: new Abstract: Small language models (SLMs) are attractive for agentic deployment due to low latency, reduced cost, and on-device privacy, yet they struggle with tool-

Faster but Different: Diagnosing and Controlling Content Drift in Accelerated Multimodal Diffusion Language Models

arXiv:2607.29079v1 Announce Type: new Abstract: Training-free acceleration makes diffusion-based multimodal large language models (dMLLMs) more deployable, but it may silently change generated content

safetyarxiv-cs-cl

Lightweight Neural Networks for Affordance Segmentation: Enhancement of the Decoder Module

arXiv:2607.29473v1 Announce Type: new Abstract: The deployment of deep neural networks for visual affordance segmentation on wearable robots poses may prove critical, due to some conflicting aspects o

applicationsarxiv-cs-cv

MROPE: A Multi-Robot Safe Cooperative Strategy via combined Predictive Safety Filters and Ellipse-based Constraint Compression

arXiv:2607.29203v1 Announce Type: new Abstract: Deploying drone swarms to track a dynamic target in cluttered environments presents severe computational and safety challenges. We propose MROPE, a hier

safetyarxiv-cs-ro

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability

arXiv:2607.28942v1 Announce Type: new Abstract: Recently Large Language Models (LLMs) have been increasingly deployed as autonomous agents in applications such as self-reflection, retrieval-augmented

agentsarxiv-cs-ai

NousResearch keeps doing things on hermes

model-releasesr-localllama

Has anyone followed nousresearch work on Hermes? I mean we are Q3 2026. We have some crazy models trickling down from HGX territory to multi gpu workstation. And we have nousresearch deploying the 0.2

Reproducing Human Individual Motor Signatures: A Data-Driven Approach for Repetitive Motion

arXiv:2503.15225v3 Announce Type: replace-cross Abstract: The deployment of autonomous virtual avatars (in extended reality) and robots in human group activities---such as rehabilitation therapy, spor

agentsarxiv-cs-ai

The K-Space Signature: Frequency-Domain Representation Learning for Medical Deepfake Detection

arXiv:2607.29541v1 Announce Type: new Abstract: In medical imaging, generative models are increasingly deployed to synthesize realistic data and augment limited datasets. Unfortunately, while benefici

Tokenizer Transplantation: Mitigating Autoregressive Collapse in Edge-Efficient Bengali ASR

arXiv:2607.09598v2 Announce Type: replace Abstract: Lightweight speech recognition models are critical for edge deployment, yet highly optimized architectures like Moonshine often fail on morphologica

researcharxiv-cs-cl

Towards White-Box Deep Wireless Sensing

arXiv:2507.21799v2 Announce Type: replace-cross Abstract: The empirical success of deep learning has spurred its application to the radio-frequency (RF) domain, leading to significant advances in Deep

applicationsarxiv-cs-ai

Local Ai

Versatile On-device Adaptation at the Edge by Unifying Few-shot, Zero-shot, Continual, and In-context Learning

arXiv:2607.29353v1 Announce Type: cross Abstract: With the ever-increasing pervasiveness of smart edge devices, the demand is growing for applications that can be tailored to users (e.g., custom keywo

local-aiarxiv-cs-ai

Vision-based Goal-Reaching Control for Mobile Robots Using a Hierarchical Learning Framework

arXiv:2601.00610v2 Announce Type: replace Abstract: Reinforcement learning (RL) has strong potential in robotics, but exploration-based training complicates safe deployment on large-scale robots. For

safetyarxiv-cs-ro

What Makes a Sale? Simulating End-to-End Seller--Buyer Retail Dynamics with LLM Agents

arXiv:2604.04468v2 Announce Type: replace Abstract: Evaluating retail strategies before deployment is difficult, as outcomes are determined across multiple stages, from seller-side persuasion through

applicationsarxiv-cs-ai

WitCert: Sound Runtime Risk Observability and Gating for KV-Cache Quantization

arXiv:2607.28699v1 Announce Type: cross Abstract: KV-cache quantization is validated today by offline benchmark averages; a deployed system cannot tell whether compression is damaging the request it i

Hardware

I pushed Kimi K3 onto one CPU with 8 GB of RAM

I deployed K3 on 32 H100s at work a couple of weeks ago and then got annoyed that there was no way to poke at it on my own machine. So I wrote an inference engine for it in C99. Nothing clever going o

hardwarer-localllama

2 Aug 2026

Belief Coevolution in a Social Network of Generalist and Specialist Large Language Models

arXiv:2607.27512v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in multi-agent environments. However, the processes by which beliefs form and propagate among int

agentsarxiv-cs-cl

Benchmarking the Residual: What Long-Horizon Evaluations Add Beyond Matched Short-Task Performance

arXiv:2607.27283v1 Announce Type: new Abstract: Long-horizon benchmarks often show that agents fail more as tasks become longer. This observation is useful for deployment, but it does not by itself ex

agentsarxiv-cs-lg

Building a User Foundation Model for the Open Web

arXiv:2607.28019v1 Announce Type: new Abstract: User foundation models have demonstrated strong results in e-commerce and social recommendation, but most industrial deployments assume environments whe

applicationsarxiv-cs-lg

Can Agents Deceive? Evaluating Reasoning and Deception in ParliamentBench using a Social Deduction Game

model-releasesarxiv-cs-cl

arXiv:2607.28146v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as agents in high-stakes settings, such as medical and legal systems, understanding their deceptive capabil

ClawTrack: Towards Trace-Level Evaluation and Improvement of Real-World Autonomous Agents

model-releasesarxiv-cs-lg

arXiv:2607.28037v1 Announce Type: new Abstract: As LLM-based agents are deployed in complex, multi-step workflows, a critical evaluation gap has emerged: most existing benchmarks judge only final outc

Collusion with Competitive Marginals: Price-Level Audits Are Blind by Construction

arXiv:2607.26385v1 Announce Type: cross Abstract: Empirical work on algorithmic collusion asks one question of the data: are prices supracompetitive? We show this can be answered 'no' by a conspiracy

Even More Deception: Objective Misalignment in Mixed-Motive LLM Multi-Agent Systems

arXiv:2607.26120v1 Announce Type: new Abstract: Large Language Models (LLMs)-powered multi-agent systems are increasingly deployed in mixed-motive environments, where agents operate under asymmetric i

agentsarxiv-cs-ai

Failure Detection for Surgical Robot Imitation Policies via Flow-Matching World Modeling

arXiv:2607.27511v1 Announce Type: new Abstract: Imitation learning has shown increasing promise for autonomous robotic surgery, yet safe deployment remains challenging due to the safety-critical natur

safetyarxiv-cs-ro

GradMAP: Faster Layer Pruning with Gradient Metric and Projection Compensation

arXiv:2602.14649v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit strong reasoning abilities, but their high computational costs limit their practical deployment. Recent studies

researcharxiv-cs-cl

LLMs struggle to simulate human belief updates in controlled environments

model-releasesarxiv-cs-cl

arXiv:2607.28347v1 Announce Type: new Abstract: LLMs are increasingly deployed as proxies for human study participants in social science experiments, yet the fidelity of this practice has rarely been

Memory Efficient Tabular Foundation Models

arXiv:2607.27546v1 Announce Type: new Abstract: Tabular Foundation Models, such as TabPFN, have received a large amount of recent attention due to their performance on in-context tabular machine learn

MixFrag: Fragility-Guided Mixed-Precision Post-Training Quantization for Vision Transformers

arXiv:2607.28589v1 Announce Type: new Abstract: Post-training quantization (PTQ) has emerged as an effective solution for deploying Vision Transformers (ViTs) on resource-constrained devices. However,

QuantWAMs: Calibrating at the Right Granularity for World Action Models

arXiv:2607.28405v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly predict future observations and actions, but their iterative denoising and closed-loop execution make efficient dep

Shared Semantic Codebook Distillation for Unpaired Cross-Modal Medical Classification

arXiv:2607.27357v1 Announce Type: new Abstract: Cross-modal knowledge distillation can transfer diagnostic knowledge from a strong but costly teacher modality to a cheaper and more deployable student

Tutorials

SUNSET - A Sensor-fUsioN based semantic SegmEnTation exemplar for ROS-based self-adaptation

arXiv:2601.13732v2 Announce Type: replace Abstract: The fact that robots are getting deployed more often in dynamic environments, together with the increasing complexity of their software systems, rai

tutorialsarxiv-cs-ro

Theia: Large-Scale Multimodal Captioning and Automated Validation of the Incidents1M Dataset for Data-Free Distillation

arXiv:2607.28269v1 Announce Type: new Abstract: The deployment of Vision-Language Models (VLMs) in critical domains like disaster management requires high-quality multimodal datasets, especially for t

Towards Practical Algorithm Selection for Unsupervised Domain Adaptation in Medical Imaging

arXiv:2607.28125v1 Announce Type: new Abstract: Numerous unsupervised domain adaptation (UDA) algori-thms exist, but for clinical practice, selecting the best-suited one along with proper hyperparamet

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles

arXiv:2607.28483v1 Announce Type: new Abstract: Real-time anomaly segmentation is essential for the safety of autonomous systems. Although recent approaches offer high accuracy, their computational co

Uncertainty quantification for trustworthy deep learning: Methods and measures

arXiv:2607.28248v1 Announce Type: cross Abstract: The deployment of deep neural networks in safety-critical domains demands reliable estimates of predictive confidence, yet conventional architectures

safetyarxiv-cs-lg

Unifying Adversarially Robust Model Experts in Vision-Language Models

arXiv:2607.27897v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP, are vulnerable to adversarial attacks, posing a serious problem for real-life applications and deployment.

What Does It Take to Detect an AI Agent? Minimal Feature Sets for Behavioral Detection under Browser Automation

arXiv:2607.26935v1 Announce Type: new Abstract: Bot detectors deployed at scale treat traffic as binary: human or bot. This assumption breaks when AI agents browse the web through browser automation,

What’s new in AI infrastructure and orchestration this month

model-releasesgoogle-cloud-ai

At Google, AI is a soup-to-nuts endeavor. Obviously, we make leading AI models like Gemini and Nano Banana. We incorporate AI into the tools you use every day (think Gmail, BigQuery, AlloyDB, Google C

Witness Evidence Portfolios: Single-Prefill Risk Detection for Closed Multimodal Answers

arXiv:2607.27667v1 Announce Type: new Abstract: Reliable deployment of multimodal large language models (MLLMs) requires deciding whether a confident visual answer should be trusted, reviewed, or rout

Adaptive Gradient-Based Methods for a Broader Class of Optimization Problems under Performative Prediction

arXiv:2607.26562v1 Announce Type: cross Abstract: We study optimization under performative prediction, where deploying a model affects the future data distribution. For this setting, several gradient-

Local Ai

Adaptively Robust LLM Monitoring via Activation Watermarking

arXiv:2603.23171v3 Announce Type: replace-cross Abstract: Providers monitor deployed large language models (LLMs) to detect misuse that they cannot prevent. LLM monitoring is deterministic and often o

local-aiarxiv-cs-lg

AIGen: Automating AI Bill of Materials Generation Through Hybrid MLOps Integration

arXiv:2607.26652v1 Announce Type: new Abstract: The responsible development and deployment of artificial intelligence (AI) systems requires rigorous documentation of their constituent artifacts, e.g.,

Deep Expert Injection for Anchoring Retinal VLMs with Domain-Specific Knowledge

arXiv:2603.07131v4 Announce Type: replace Abstract: Large Vision Language Models (LVLMs) show immense potential for automated ophthalmic diagnosis. However, their clinical deployment is severely hinde

DP-MGTD: Privacy-Preserving Machine-Generated Text Detection via Adaptive Differentially Private Entity Sanitization

arXiv:2601.04641v2 Announce Type: replace-cross Abstract: The deployment of Machine-Generated Text (MGT) detection systems necessitates processing sensitive user data, creating a fundamental conflict

researcharxiv-cs-cl

Explainable and Resource-Efficient Spatial Reasoning in Multimodal LLMs for Decision-Critical Applications

arXiv:2607.27145v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) are increasingly deployed in decision-critical pipelines such as robotics, embodied AI, and safety monitorin