Search: “deployment”

Capable but Careless: Do Computer-Use Agents Follow Contextual Integrity?

arXiv:2606.23189v2 Announce Type: replace-cross Abstract: Computer-use agents (CUAs) now act on a user's behalf across personal applications such as email, calendars, and to-do lists. This cross-appli

safetyarxiv-cs-cl

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Correlation-Guided Fast Machine Unlearning via Hessian Analysis

DGX agent

arXiv:2609.12620v1 Announce Type: new Abstract: The increasing adoption of machine learning in network and distributed security systems has created an urgent need for mechanisms that can selectively a

model-releasesarxiv-cs-lg

14 Sept 2026

Decomposing Discrimination: Causal Mediation Analysis for AI-Driven Credit Decisions

arXiv:2603.27510v2 Announce Type: replace Abstract: Statistical fairness metrics in AI-driven credit decisions conflate two causally distinct mechanisms: discrimination operating directly from a prote

safetyarxiv-cs-lg

Distributed Stochastic Optimal Control for Pattern-Oriented Swarms

arXiv:2609.12959v1 Announce Type: new Abstract: While offering significant promise for diverse applications, pattern-oriented swarms encounter multifaceted challenges in geometric control, self-organi

DWMP: Leveraging Dual World Models for Humanoid Obstacle Traversal

arXiv:2609.12347v1 Announce Type: new Abstract: Humanoid robots must traverse cluttered obstacle fields using onboard proprioceptive and visual observations, yet existing methods usually process multi

Fixed State, Long Reach: What a Constant-Size Cache Buys Block Diffusion at Scale

arXiv:2609.11998v1 Announce Type: new Abstract: Diffusion language models decode tokens in parallel, but their bidirectional denoiser rules out the naive key--value (KV) cache behind fast autoregressi

safetyarxiv-cs-lg

FoldNet++: a Large-Scale Synthetic Dataset for Robotic T-Shirt Folding and Unfolding

arXiv:2609.12433v1 Announce Type: new Abstract: Due to the highly deformable nature of garments, training a generalizable policy for robotic T-shirt folding and unfolding remains a significant challen

GeoSense-AI: Fast Location Inference from Crisis Microblogs

arXiv:2512.18225v2 Announce Type: replace Abstract: This paper presents an applied AI pipeline for real-time geolocation from noisy microblog streams, unifying statistical hashtag segmentation, part-o

applicationsarxiv-cs-cl

GSO-Net: Visual State Machines for Hazardous Freight Transfer Compliance at Petrochemical Logistics Nodes

model-releasesarxiv-cs-cv

arXiv:2609.12408v1 Announce Type: new Abstract: Hazardous-freight operations at petrochemical logistics nodes are safety-critical for intelligent transportation systems, yet existing vision benchmarks

GUIDE: Generative Utility Inference and Decision Engine

arXiv:2609.12137v1 Announce Type: new Abstract: Measuring the preferences of human users remains a fundamental challenge of AI alignment. Existing elicitation approaches struggle to efficiently discov

safetyarxiv-cs-lg

High-Fidelity Multi-Body Simulator for Autonomous Racing

arXiv:2609.12795v1 Announce Type: new Abstract: We present a custom high-fidelity vehicle dynamics simulation environment for testing and validation of Autonomous Racing software. The digital twin of

agentsarxiv-cs-ro

Input Resolution Matters: Real-Time Object Detection Latency

model-releasesarxiv-cs-cv

arXiv:2609.12920v1 Announce Type: new Abstract: We model total latency as the convolution of preprocessing, inference, and postprocessing distributions under a simplifying independence approximation,

MARE: Multimodal Alignment and Reinforcement for Explainable Deepfake Detection via Vision-Language Models

arXiv:2601.20433v4 Announce Type: replace Abstract: Deepfake detection is a widely researched topic that is crucial for combating the spread of malicious content, with existing methods mainly modeling

safetyarxiv-cs-cv

Microsoft says ‘people matter more than AI’ following safety concerns

Microsoft is publishing a 37-page 'humanist AI code of conduct' today, amid growing safety concerns over AI model progress. Anthropic CEO Dario Amodei called for a coordinated slow down of AI developm

safetythe-verge-ai

OphBiWSSD: Scaling Temporal Action Localization in Ophthalmic Surgeries with Bidirectional Weight-tied State Space Duality

model-releasesarxiv-cs-cv

arXiv:2609.12409v1 Announce Type: new Abstract: High-frequency surgical maneuvers in ophthalmology necessitate high-fidelity temporal modeling, yet characterizing long-range procedural dependencies re

PEARL: Structural Privacy-Utility Control in Human-Centric CPS via Personalized Early-Exit Deep Reinforcement Learning

arXiv:2403.05864v3 Announce Type: replace Abstract: In human-centric Cyber-Physical Systems (CPS), personalized Deep Reinforcement Learning (DRL) agents must share fine-grained control actions with cl

Protect Your Score: Contact Tracing With Differential Privacy Guarantees

arXiv:2312.11581v3 Announce Type: replace-cross Abstract: The pandemic in 2020 and 2021 had enormous economic and societal consequences, and studies show that contact tracing algorithms can be key in

agentsarxiv-cs-lg

Size Doesn't Matter: Material-State Reinforcement Learning for Excavator Transferable Soil Manipulation

arXiv:2609.12677v1 Announce Type: new Abstract: Earthmoving tasks such as excavation, backfilling, or embankment construction require deliberate repositioning of deformable soil. For these tasks, huma

The world deserves confidence that American companies developing increasingly capable AI will act responsibly, especially as the trajectory …

The world deserves confidence that American companies developing increasingly capable AI will act responsibly, especially as the trajectory of progress has steepened. Every frontier lab must deliver o

safetysam-altman--x

Towards Sustainable Hydrogen Systems: Supply Chain Optimization with Model Predictive Control and Reinforcement Learning

arXiv:2609.11933v1 Announce Type: cross Abstract: Hydrogen supply chains are expected to play a central role in future low-carbon energy systems by enabling renewable energy integration, long-duration

Tutorials

Transfer Learning for Evolving Domains

arXiv:2609.13039v1 Announce Type: new Abstract: Transfer learning explores how to leverage knowledge from various tasks or domains (sources) to enhance predictive performance in related tasks or domai

tutorialsarxiv-cs-lg

VertiFuseX: Generalizable Financial Forecasting via Multi-Stream Temporal Fusion

arXiv:2609.12793v1 Announce Type: new Abstract: Stock price prediction remains challenging due to the non-stationary and noisy nature of financial time series. Existing deep learning models often rely

Very Exciting: Zero-Shot Model Predictive Control of Buildings via Excitation-Based Generalized Transfer Learning Models

arXiv:2609.12853v1 Announce Type: cross Abstract: The widespread adoption of data-driven, energy-efficient model predictive control (MPC) in buildings remains hindered by substantial effort to collect

What does it mean to pace the frontier? Over the last month, @random_walker and I have analyzed the loss-of-control incidents at AI companie…

What does it mean to pace the frontier? Over the last month, @random_walker and I have analyzed the loss-of-control incidents at AI companies to understand what technical and policy interventions can

safetyyann-lecun--x

I built a serverless hosting platform for LoRA adapters with vLLM

model-releasesr-localllama

It’s always bothered me that after fine-tuning a model for a project, there isn’t a particularly easy way to host it without either running it locally and keeping a GPU on 24/7 or paying for an entire

13 Sept 2026

About a year ago, before it was on anyone's radar, we began exploring the idea of a benchmark for open-ended invention. Since then, we've de…

model-releasesfrancois-chollet--x

About a year ago, before it was on anyone's radar, we began exploring the idea of a benchmark for open-ended invention. Since then, we've developed several promising directions that will serve as the

ActMap: Single-Pass Uncertainty Quantification from Generation-Time Activation Maps

arXiv:2609.11498v1 Announce Type: new Abstract: Practical uncertainty quantification (UQ) for large language models must decide, from a single generation, whether a specific answer should be trusted.

researcharxiv-cs-ai

Agentic Share-of-Search: A Multi-Agent AI System for Competitive Decision-Making in LLM-Mediated E-Commerce

arXiv:2609.11190v1 Announce Type: new Abstract: AI shopping assistants increasingly redirect consumer discovery, creating an urgent need for tools that support seller-side competitive decision-making.

AI Exposure and AI Resilience: A Two-Dimensional Assessment Framework for Software and Software-Based Business Model

arXiv:2609.11321v1 Announce Type: new Abstract: Artificial intelligence is changing both software production and the economics of software-based business models. Classical technology due diligence mai

applicationsarxiv-cs-ai

Beyond Verified Answers: Solver-Informed Self-Distillation for Bootstrapping Operations Research Language Models

arXiv:2609.09957v1 Announce Type: cross Abstract: Modern large language models (LLMs) can translate natural-language descriptions into operations research (OR) formulations. Post-training techniques i

safetyarxiv-cs-ai

Can LLMs Follow Medical Expert Logic? A Benchmark for Hierarchical Logical Consistency in Risk-of-Bias Assessment

model-releasesarxiv-cs-ai

arXiv:2609.11185v1 Announce Type: new Abstract: Evidence-based medicine demands strict logical consistency, yet current evaluations of large language models (LLMs) prioritize superficial label matchin

Four Generations of Quantum Biomedical Sensors

arXiv:2603.29944v3 Announce Type: replace-cross Abstract: Quantum sensing technologies offer transformative potential for ultra-sensitive biomedical sensing, yet their clinical translation remains con

researcharxiv-cs-ai

From Document Silos to Process Intelligence: A Multi-Layer Knowledge Graph for CMC Process Development

arXiv:2609.11493v1 Announce Type: new Abstract: Chemistry, Manufacturing and Controls (CMC) process development generates an enormous body of technical information across a multi-stage, knowledge-inte

Grounding Agent Memory: Environment-Probing Curation for Enterprise Agents

arXiv:2609.11060v1 Announce Type: new Abstract: Persistent memory is entering production-oriented agent platforms to help long-horizon agents accumulate experience across sessions. Yet a post-task cur

If you showed me Claude Code today in 2018, I would have thought it was AGI. We have already absorbed a dramatic amount of change in the pro…

If you showed me Claude Code today in 2018, I would have thought it was AGI. We have already absorbed a dramatic amount of change in the profession of software engineering and society as a whole. But

model-releasesthariq--x

No-Box Vulnerability Analysis: Description-only Detection of Indirect Prompt Injection Vulnerabilities in MCP Servers

arXiv:2609.10854v1 Announce Type: cross Abstract: Conventional vulnerability analysis relies on either system access or dynamic interaction, all of which may be unavailable to third-party analysts aud

Prompt Revision as a Source of Cultural Bias in Text-to-Image Systems

model-releasesarxiv-cs-ai

arXiv:2609.11532v1 Announce Type: new Abstract: Commercial text-to-image systems silently revise user prompts before generating images, a step users typically cannot disable or even see. Yet, existing

The Coxon psyop was a decade and more than a billion dollars in the making. Here's the story. Coefficient Giving (formerly Open Philanthropy…

applicationsyann-lecun--x

The Coxon psyop was a decade and more than a billion dollars in the making. Here's the story. Coefficient Giving (formerly Open Philanthropy) is the grant-providing vehicle of Dustin Moskowitz. CG is

“We can’t slow down because China will beat us.” We can slow down. Chinese AI is waterskiing behind the US. Their AI capabilities come at a …

“We can’t slow down because China will beat us.” We can slow down. Chinese AI is waterskiing behind the US. Their AI capabilities come at a delay since they mainly come from distilling US AIs. If we s

safetydan-hendrycks--x

AI-Powered Flare Combustion Efficiency Estimation

arXiv:2609.11262v1 Announce Type: cross Abstract: Achieving high combustion efficiency in flare stacks is crucial for adhering to regulatory standards and controlling the release of hydrocarbons into

applicationsarxiv-cs-cv

Are frontier models actually becoming less important?

I’m genuinely mind-blown by what’s happening with AI models right now. On one side, you have GPT-6-class frontier models that are just… insane. The level of capability is getting hard to wrap your hea

model-releasesr-ollama

Automated multi-class wound assessment using dedicated instance segmentation models for boundary detection and classification

arXiv:2603.27325v2 Announce Type: replace Abstract: Accurate wound classification (WC) and boundary segmentation are essential for guiding clinical decisions in chronic and acute wound management. How

researcharxiv-cs-cv

Beyond Benchmarks: Using VLMs to Reveal Systematic Classification Failures Under Real World Conditions

arXiv:2609.11126v1 Announce Type: new Abstract: Verification and validation (V&V) of classification models is crucial to enable a wide range of sensor processing applications. Currently, the V&V proce

applicationsarxiv-cs-cv

Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery

arXiv:2609.09647v1 Announce Type: new Abstract: Agentic systems are rapidly moving to production, where they read untrusted inputs, call tools with real permissions, and act autonomously, expanding th

Conformal Calibration Transfer

arXiv:2609.10737v1 Announce Type: new Abstract: Conformal prediction converts point predictions into set-valued predictions with coverage guarantees under exchangeability between calibration and deplo

Local Ai

Cross-Lingual Clinical Annotation Projection as Constrained Text Generation: A Six-Language Study

arXiv:2609.11450v1 Announce Type: new Abstract: Background: To determine whether cross-lingual clinical annotation projection can be formulated as a text-preserving, document-level generative task tha

local-aiarxiv-cs-cl

Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

arXiv:2609.11777v1 Announce Type: cross Abstract: Clinical electroencephalography (EEG) data are valuable for healthcare research and for developing artificial intelligence (AI)-based clinical decisio

applicationsarxiv-cs-lg

EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression

model-releasesarxiv-cs-lg

arXiv:2609.11058v1 Announce Type: new Abstract: Recent advances in multimodal large language mod- els (MLLMs) have opened new opportunities for edge intelligence by enabling reasoning across heterogen