Search: “deployment”

ADEPT: A Unified Framework for Deep Learning Test Adequacy

arXiv:2608.12144v1 Announce Type: cross Abstract: Over the past decade, many test adequacy metrics have been proposed for deep learning that characterize test dataset adequacy from different perspecti

Agent Safety Should Be a Runtime Contract

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DGX agent

arXiv:2608.11274v1 Announce Type: cross Abstract: The dominant paradigm treats AI safety as a property to be instilled during model training via RLHF, DPO, or Constitutional AI. We argue this is struc

model-releasesarxiv-cs-ai

13 Aug 2026

AgenticTwin: An Agentic LLM Framework Integrated with Digital Twin for Anomaly Detection

arXiv:2608.11679v1 Announce Type: new Abstract: Digital twins are increasingly used to monitor and simulate the behavior of cyber-physical systems. Even with skilled operators, interpreting anomalies

AgonAlpha: Autonomous Alpha Discovery via Prompt Economy and Scalable Agentic Search

arXiv:2608.11250v1 Announce Type: new Abstract: Language models can propose many plausible trading factors, but an autonomous research system must also allocate its evaluation budget, verify its own e

Air Quality Station Simulation via LSTM and Attention-Based Modelling

arXiv:2608.11839v1 Announce Type: new Abstract: Poor air quality in urban areas is driven by a complex chain of processes and presents a significant public health concern. To better understand and con

Autonomous Telerehabilitation via Skeletal Motion Prediction and Joint-Level Performance Assessment

arXiv:2608.12145v1 Announce Type: new Abstract: Autonomous rehabilitation systems must not only recognize human motion but also provide structured feedback to support users without continuous therapis

agentsarxiv-cs-cv

AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention

model-releasesarxiv-cs-cl

arXiv:2608.11758v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) exhibit strong generalization and reasoning abilities due to large-scale multimodal pre-training. However, fine

Benchmarking Trustworthiness of SLMs: Pre-trained vs. Compressed

arXiv:2608.11981v1 Announce Type: new Abstract: Small Language Models (SLMs) have emerged as a more efficient alternative to traditional Large Language Models (LLMs), offering promising potential in r

safetyarxiv-cs-cl

BoltNet: An Ultra-Lightweight Convolutional Network for On-Device Plant Species Identification

arXiv:2608.11844v1 Announce Type: new Abstract: Automated plant species identification from citizen-science imagery is an established, demanding fine-grained recognition problem: large taxonomic label

local-aiarxiv-cs-cv

COLORA: Efficient Fine-Tuning for Convolutional Models with a Study Case on Optical Coherence Tomography Image Classification

arXiv:2505.18315v3 Announce Type: replace-cross Abstract: We introduce extbf{CoLoRA} (Convolutional Low-Rank Adaptation), a parameter-efficient fine-tuning method for convolutional neural networks (CN

Cross-Corpus Evaluation of Generalizable Vulnerability Detection in IoT Firmware

arXiv:2608.11492v1 Announce Type: cross Abstract: IoT firmware vulnerability detection remains challenging due to heterogeneous firmware ecosystems, resource-constrained platforms, and limitations in

Curvature-Aware Zeroth-Order Optimization for Memory-Efficient Test-Time Adaptation

arXiv:2608.12279v1 Announce Type: new Abstract: Test-time adaptation (TTA) aims to enhance the cross-domain performance of pre-trained models by adapting to unlabeled test data. While most existing TT

local-aiarxiv-cs-cv

Hardware

Cutting AI Datacenter Energy with Reinforcement Learning: Measured Power Control of LLM Training from One GPU to the Fleet

arXiv:2608.11226v1 Announce Type: new Abstract: Reinforcement-learning post-training dominates modern language-model development, yet its power behavior on GPU hardware has not been characterized, and

hardwarearxiv-cs-ai

Defending against Model Extraction for GNNs with Model Reprogramming

arXiv:2608.11495v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) serve as the backbone for high-stakes applications in Machine-Learning-as-a-Service (MLaaS). Still, their black-box deploym

safetyarxiv-cs-lg

Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction

arXiv:2608.11772v1 Announce Type: new Abstract: Self-correction is particularly useful when a failure constrains the next repair. Coding agents benefit from this property because compilers, tests, and

safetyarxiv-cs-cl

Distribird: Literature-Informed Prior Distribution Design for Bayesian Model Calibration

arXiv:2608.11210v1 Announce Type: new Abstract: Bayesian calibration of process-based models requires a prior distribution for each model parameter. Despite decades of methodological work, researchers

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling

arXiv:2608.12271v1 Announce Type: new Abstract: Global weather reanalyses and forecasts resolve the evolving atmospheric state on coarse grids, but site-specific applications require predictions at ar

researcharxiv-cs-lg

Easper: An Accessible ASR Pipeline for Language Documentation

arXiv:2608.11629v1 Announce Type: new Abstract: Audio transcription is a critical bottleneck in language documentation. While multilingual Automatic Speech Recognition (ASR) models like Whisper offer

researcharxiv-cs-cl

Explainability in Practice: A Survey of Explainable NLP Across Various Domains

arXiv:2502.00837v3 Announce Type: replace-cross Abstract: Natural Language Processing (NLP) is now embedded in critical sectors including healthcare, finance, and customer relationship management, whe

FEWT: Frequency-Enhanced Wavelet-based Transformer for Multimodal Wheeled Bimanual Manipulation

arXiv:2509.11109v4 Announce Type: replace Abstract: Embodied intelligence bridges the physical world and information spaces, with robots demonstrating immense potential through imitation learning algo

applicationsarxiv-cs-ro

Foresight Without Seeing: Latent Futures for World Action Models

arXiv:2608.11605v1 Announce Type: new Abstract: World Action Models (WAMs) couple future visual prediction with robot action generation, enabling policies to model how the physical world evolves durin

GUIDE: Governed Unified Intelligence for Document-to-Artifact Generation in Enterprise Settings

arXiv:2608.12133v1 Announce Type: new Abstract: Enterprise guideline documents are heterogeneous and multimodal, combining narrative text, complex tables, and embedded images. Existing LLM and VLM sys

HAMP-LIC: Hessian-Aware Mixed-Precision Post-Training Quantization for Learned Image Compression

arXiv:2608.12239v1 Announce Type: cross Abstract: Use this plain-text version for the arXiv abstract field: Learned image compression (LIC) models achieve strong rate-distortion performance but are hi

researcharxiv-cs-ai

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents

arXiv:2608.11727v1 Announce Type: new Abstract: When a coding agent obeys a rule, it may simply have been going to do that anyway. Existing instruction-following benchmarks cannot tell the difference:

HUGIN: Enhancing Vision-Language Planning for Autonomous Logistics Sorting

arXiv:2608.11692v1 Announce Type: new Abstract: Autonomous logistics sorting systems (ALSS) are an important industrial application of embodied AI, which requires joint planning over spatially disjoin

Latent variable models for simultaneous EOV identification and removal in population-based SHM

arXiv:2608.11995v1 Announce Type: cross Abstract: The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM).

Learning Loco-Manipulation From SMPC Demonstrations With Sparse Offline-to-Online RL

arXiv:2608.12063v1 Announce Type: cross Abstract: Integrating locomotion and manipulation is essential for robot autonomy, but scaling standard Reinforcement Learning (RL) to complex tasks is severely

LLM-Powered Automatic Translation and Urgency in Crisis Scenarios

arXiv:2602.13452v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly proposed for crisis preparedness and response, particularly for multilingual communication. Howe

researcharxiv-cs-ai

LLMs in Process Diagram Engineering: From Optimal PFDs to Validated P&IDs

arXiv:2608.11220v1 Announce Type: new Abstract: Nowadays, the creation of a process flow diagram (PFD) and its subsequent transformation into a piping and instrumentation diagram (P&ID) is predominant

Machine Learning-Based Cyber Defense for Cloud Infrastructure: An Adaptive Deep Q-Network Architecture for Intelligent Intrusion Detection and Automated Threat Mitigation

arXiv:2608.12190v1 Announce Type: cross Abstract: With the increasing complexity of cyber assaults in cloud environments, adaptable security solutions are needed that can support real-time detection a

Multi-Agent Embodied Autonomous Driving: From V2X Information Exchange to Shared World Models

arXiv:2606.13840v2 Announce Type: replace-cross Abstract: Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and

safetyarxiv-cs-cv

One Frozen Simulator Is Not Enough: Simulator Collapse in Multi-Agent RL

arXiv:2608.12253v1 Announce Type: cross Abstract: Multi-agent reinforcement learning for human-AI interaction typically relies on a single large language model to simulate user behavior. We show that

Our UK reps didn’t remember to smile 😂 We recently opened a @llama_index office in London 🇬🇧. It is three people strong (Frank, Max, Joe)…

Our UK reps didn’t remember to smile 😂 We recently opened a @llama_index office in London 🇬🇧. It is three people strong (Frank, Max, Joe), with two more people starting soon. It also has a beautiful v

applicationsjerry-liu--x

out of curiosity, i tasked fable to figure this thing out and it looks like the 'saas killer' is done. ▲ it maxed out Fable 5 + used most of…

out of curiosity, i tasked fable to figure this thing out and it looks like the 'saas killer' is done. ▲ it maxed out Fable 5 + used most of Codex limits ▲ most of the work was done within 45h session

model-releasesswyx--x

Poly-Dialectal Neural Machine Translation System for Bangla Regional Dialects

arXiv:2608.12018v1 Announce Type: new Abstract: Regional dialectal variation poses a fundamental challenge to natural language processing (NLP) in Bangla, where over 240 million speakers communicate a

applicationsarxiv-cs-cl

Quantization-Aware Neuromorphic Architecture for Skin Lesion Classification on Resource-Constrained Devices

arXiv:2507.15958v5 Announce Type: replace-cross Abstract: On-device skin lesion analysis is constrained by the compute and energy cost of conventional CNN inference and by the need for lightweight cal

local-aiarxiv-cs-ai

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

arXiv:2608.12004v1 Announce Type: cross Abstract: In modern AI frameworks, GPU kernels are key to overall system performance. Combining usability, portability, and near-handwritten CUDA performance, T

RoadWeaver: Large-Scale Lane-Level HD Map Generation from Scratch for Autonomous Driving Simulation

arXiv:2608.11580v1 Announce Type: cross Abstract: Autonomous driving simulation requires diverse and scalable lane-level HD maps to support long-horizon evaluation across complex road networks. Existi

Robust Ambiguity Detection (RAD) From Model- and Feature-Space Consistency

arXiv:2608.11541v1 Announce Type: new Abstract: Machine learning models should be robust, in the sense of remaining predictively consistent under permissible variations. A model's predictions should i

applicationsarxiv-cs-lg

SCAR-GS: Spatial Context Attention for Residuals in Progressive Gaussian Splatting

arXiv:2601.04348v2 Announce Type: replace Abstract: Recent advances in 3D Gaussian Splatting have allowed for real-time, high-fidelity novel view synthesis. Nonetheless, these models have significant

researcharxiv-cs-cv

SoftWater: Class-Aware Rate Allocation for Softmax Quantization

arXiv:2608.12026v1 Announce Type: new Abstract: Post-training quantization pipelines routinely leave the softmax output layer in high precision. Yet in small LLMs with modern vocabularies, the head ho

Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages

arXiv:2608.12278v1 Announce Type: cross Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced commu

applicationsarxiv-cs-ai

There is much less signal in agent leaderboards than the rankings imply. A four-facet Generalizability Theory decomposition across TheAgentC…

There is much less signal in agent leaderboards than the rankings imply. A four-facet Generalizability Theory decomposition across TheAgentCompany, tau-squared-bench, and AppWorld finds the agent main

agentsdair-ai--x

TradingMoE: Routing the Right Experts in Evolving Markets

arXiv:2608.11785v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for financial analysis and trading, but direct trading remains challenging because the predicti

researcharxiv-cs-lg

Uncertainty-Aware Compositional Localization and Placement Assessment of Catheters and Tubes in Chest X-Rays

arXiv:2608.11288v1 Announce Type: cross Abstract: Assessing catheter and tube placement on chest X-rays is safety-critical yet tedious and error-prone. Current deep learning methods either classify pl

local-aiarxiv-cs-cv

Using BigQuery Graphs with measures for trusted agentic workloads

When enterprises transition from using simple chat assistants to autonomous, agentic workloads, they quickly run into a hard truth: Agents are prone to inaccurate insights when working with directly r

agentsgoogle-cloud-ai

Variable Selection in the Context of AI Fairness

arXiv:2608.11251v1 Announce Type: cross Abstract: Fairness in AI systems has become more important with recent regulatory demands, such as the EU AI Act. Traditional approaches often do not take into

We examine how these orgs are putting AI to work, and how agentic workflows are expanding across industries and functions: https://openai.co…

The article explores how businesses are embedding AI into daily operations, emphasizing the rise of *agentic* (self‑directed) workflows that span multiple industries and job functions. It highlights t

agentsopenai--x