Search: “deployment”

FedEHR-Agents: Federated Agentic Optimization for Automated EHR Modeling

model-releasesarxiv-cs-lg

arXiv:2608.27856v1 Announce Type: new Abstract: Recent advances in large language models are enabling autonomous clinical agents to perform increasingly complex electronic health record (EHR) modeling

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Applications

From private cloud to private AI cloud, software decides who wins

DGX agent

Enterprise experimentation with cloud AI has run into a wall of data-control, sovereignty and token-cost questions, pushing intelligence back toward infrastructure enterprises own. The result is a reb

applicationssiliconangle

31 Aug 2026

Applications

Pruning Laws for Large Language Models

arXiv:2504.04342v2 Announce Type: replace Abstract: Scaling up model parameters and training data consistently improves the performance of large language models (LLMs), but at the cost of rapidly grow

applicationsarxiv-cs-cl

RiskBlend: A Multi-Signal Framework for Test Input Prioritization in Machine Learning Regression Testing

arXiv:2608.27704v1 Announce Type: new Abstract: When machine learning classifiers are retrained, inputs correctly classified by the previous model version may be misclassified by the updated version,

local-aiarxiv-cs-lg

When the City Teaches the Car: Label-Free 3D Perception from Infrastructure

arXiv:2603.16742v2 Announce Type: replace Abstract: Building robust 3D perception for self-driving still relies heavily on large-scale data collection and manual annotation, yet this paradigm becomes

local-aiarxiv-cs-cv

Hardware

Most Neoclouds Suck At Security

Most neoclouds exhibit weak security controls, exposing users to risks such as container escapes, kernel bypasses, compromised network policies, insecure credential handling, and multi‑tenant Grafana

hardwaresemianalysis

30 Aug 2026

A Layer Importance Metric for Quantization Accounting for the Speed-Quality Trade-off in Autoregressive Models

model-releasesarxiv-cs-lg

arXiv:2608.26926v1 Announce Type: new Abstract: Small language models (sLLMs) are nowadays hosted on devices with limited memory and computational budget. In an autoregressive setup, inference is memo

Activation Outliers Matter: Robust Recovery for Quantized Multimodal LLMs

arXiv:2608.26581v1 Announce Type: new Abstract: Low-bit quantization offers a promising avenue for reducing the computational and memory demands of Multimodal Large Language Models (MLLMs). Recent har

Embodied Scene Rearrangement Planning

model-releasesarxiv-cs-ro

arXiv:2608.27371v1 Announce Type: new Abstract: This paper introduces Embodied Scene Rearrangement Planning (ESRP), a novel task requiring embodied agents to rearrange furniture in 3D scenes to match

Is Your Neighborhood Safe? Place-based Stigma in Large Language Models' Urban Safety Judgments

arXiv:2608.26188v1 Announce Type: new Abstract: Large language models are increasingly used to inform safety decisions in cities, such as where it is safe to walk, rent, or travel. We ask whether such

Large Models for Battery Prognostics and Health Management: A Review and Future Roadmap

arXiv:2608.26111v1 Announce Type: new Abstract: Battery Prognostics and Health Management (BPHM) is critical for ensuring the safe, reliable, and cost-effective operation of batteries across electric

local-aiarxiv-cs-ai

Qwen3.8-Flash on RTX3090 + 64GB RAM (but you only need 12GB VRAM)

model-releasesr-localllama

I've got Qwen3.8-Flash-next running on RTX 3090, Ryzen 9 3950X, a PCIe 3.0 motherboard, and 64GB DDR RAM from 2020. IQ4_XS weights, full kvarn5 context, vision on GPU, experts in host RAM, n-grams on

Robust Neural Stimulation Response Modeling Through Meta-Learning and Pretraining

arXiv:2608.26649v1 Announce Type: new Abstract: Objective: Model-based closed-loop neural stimulation holds promise for therapeutic applications ranging from Parkinson's disease to sensory restoration

Simple Actors and Deep Critics for Scalable Reinforcement Learning

arXiv:2608.26659v1 Announce Type: new Abstract: Recent progress in offline reinforcement learning (RL) has been driven by expressive generative actors such as diffusion and flow-matching policies, whi

TemporalFlow-VLA: Learning Physically Grounded Execution History for Long-Horizon Robot Manipulation

arXiv:2608.26821v1 Announce Type: new Abstract: Vision-language-action (VLA) models leverage pretrained vision-language representations for robot control, yet simply adding historical frames does not

researcharxiv-cs-ro

The Cold-Start Safety Gap in LLM Agents

model-releasesarxiv-cs-cl

arXiv:2606.07867v2 Announce Type: replace Abstract: Are tool-calling LLM agents equally safe throughout a conversation? We discover they are not: agents are most vulnerable at the very start of a sess

Toward Equitable Low-Carbon Mobility: Fairness-Aware Demand Prediction for Expanding Bike-Sharing Systems

arXiv:2608.26451v1 Announce Type: new Abstract: Bike-sharing systems are an important component of low-carbon urban mobility, but continued expansion creates challenges in both cold-start prediction a

safetyarxiv-cs-lg

Vision-centric generative AI models: A software-hardware perspective

model-releasesarxiv-cs-cv

arXiv:2608.27199v1 Announce Type: new Abstract: Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning. The explosion of multimodal mode

A Lightweight Multimodal Vision-Language Framework for Early-Stage Anatomical Green Fruit Classification in Commercial Orchards

arXiv:2608.24935v1 Announce Type: new Abstract: Accurate identification of early-stage apple fruitlet anatomical structures, including the calyx, fruitlet body, and peduncle, is essential for robotic

local-aiarxiv-cs-cv

AI/ML Life Cycle Management for Interoperable AI Native RAN

arXiv:2507.18538v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) and machine learning (ML) are rapidly becoming integral to the 5G Radio Access Network (RAN), enabling beam manag

Capacity Overflow: A Blind Spot for Backdoor Attacks in Vision MoE

arXiv:2608.25371v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent paradigm for scaling Vision Transformers efficiently. To ensure computational scalability and prevent ex

researcharxiv-cs-cv

PANDA - Prototype-Anchored Alignment for Partially Unpaired Multimodal Learning, with Applications to Alzheimers MRI and TCGA Pathology

arXiv:2608.25970v1 Announce Type: new Abstract: Multimodal medical prediction often faces incomplete pairing: auxiliary modalities with complementary signal are available for only a subset of subjects

safetyarxiv-cs-cv

Same-Player Verification for Account Consistency in Counter-Strike 2

arXiv:2608.24893v1 Announce Type: cross Abstract: In competitive first-person shooter (FPS) games such as Counter-Strike 2 (CS2), account-integrity review often asks whether an account's recent behavi

Sources: Town, which develops enterprise personal AI assistants, is in talks to raise at a $1B valuation in a round led by Index Ventures (Newcomer)

Newcomer: Sources: Town, which develops enterprise personal AI assistants, is in talks to raise at a 1B valuation in a round led by Index Ventures — Town, the buzzy enterprise personal agent, is raisi

agentstechmeme

StreamPI: Streaming Multimodal Temporal Modeling for Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2608.26067v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated effectiveness in robot manipulation, yet state-of-the-art models such as pi0.5 operate under a sin

Trace Integrity for LLM Data Agents: A Vision for Auditable Structured Reasoning in Real-World Systems

model-releasesarxiv-cs-cl

arXiv:2608.26036v1 Announce Type: cross Abstract: Answer accuracy is an insufficient reliability signal for LLM data agents. In structured-data tasks, a benchmark-correct answer can be produced by an

Vertical Advantage: Transforming Industries with Lakebase and Agentic AI

**Vertical Advantage: Transforming Industries with Lakebase and Agentic AI** The article details how Lakebase’s unified data‑lake platform, coupled with Agentic AI’s autonomous decision‑making agents,

agentsdatabricks

Why ML-based cough models do not generalize: a systematic cross-dataset evaluation for tuberculosis screening

arXiv:2608.25846v1 Announce Type: cross Abstract: Cough acoustics are promising for non-invasive tuberculosis (TB) screening, yet whether machine learning (ML) models capture disease-related acoustics

Automata from Agent Traces: Failure and Next-Step Prediction

arXiv:2608.23670v1 Announce Type: new Abstract: LLM-based agents execute multi-step tasks, but their behavioral structure remains opaque: long unstructured traces resist the safety auditing and runtim

DreamLedger: Execution-Settled Credit Files for World-Model Imagination in Robot Decision Loops

arXiv:2608.23863v1 Announce Type: new Abstract: Robots are beginning to act on world-model predictions, yet reliability is still expressed through instantaneous, model-internal signals. DreamLedger in

researcharxiv-cs-ro

From Seeing to Acting: Smart Glasses as First-Person Intelligence Platforms

arXiv:2608.24877v1 Announce Type: new Abstract: Smart glasses are evolving from capture and display accessories into first-person intelligence platforms that connect human perception, persistent conte

researcharxiv-cs-cv

LLM-Guided Contextual Action Evaluation for Operational Decisions in Industrial Processes

arXiv:2608.24156v1 Announce Type: cross Abstract: Industrial actor--critic methods usually represent continuous actions as anonymous numerical coordinates. They must therefore learn from limited inter

Rebuild Dossier: Mechanically-Enforced Specs for Agentic App Rebuilds, and What Model-Tier Failures Reveal

arXiv:2608.23616v1 Announce Type: cross Abstract: An AI agent's rebuild is only as good as the process that produced it. Prior work found that once a model is strong enough, a multi-agent rebuild pipe

agentsarxiv-cs-ai

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification

arXiv:2509.03754v2 Announce Type: replace-cross Abstract: Responding to rising global food security needs, precision agriculture and deep learning-based plant disease diagnosis have become crucial. Ye

researcharxiv-cs-ai

The Shadow Price of Intelligence: Quality Degradation in LLM Inference as a Supply Chain Problem

arXiv:2608.23986v1 Announce Type: cross Abstract: Large language model providers are compute constrained, and their universal response to congestion is to degrade service: route queries to smaller mod

Benchmarking and Boosting Multilingual Capabilities of LVLMs via OCR-Centric Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2503.18484v3 Announce Type: replace-cross Abstract: Evaluating the multilingual capabilities of Large Vision-Language Models (LVLMs) remains challenging because most benchmarks rely on non-paral

Calibrate What You SHIP: Post-Selection Risk Control for Verifier-Guided Text-to-Image Generation

model-releasesarxiv-cs-cv

arXiv:2608.21748v1 Announce Type: new Abstract: Verifier-guided text-to-image systems increasingly use test-time search to select, refine, or stop among multiple candidates, yet release thresholds are

Do Time-Series Foundation Models Pay Off for Industrial Monitoring? A Cost-Aware Empirical Study

arXiv:2608.22968v1 Announce Type: new Abstract: Industrial monitoring models must detect operationally relevant deviations while satisfying target-specific data, calibration, and resource constraints.

local-aiarxiv-cs-lg

Gated Decoupled Compositional Bandits: A Unified Theory of Contextual Bandits with Supervised-Calibrated Action Scaling and Pre-Execution Gating

model-releasesarxiv-cs-lg

arXiv:2608.21993v1 Announce Type: new Abstract: We introduce Gated Decoupled Compositional Bandits (GDCB), a family of contextual bandit algorithms with three structural innovations that jointly fall

HIRA: A Human-in-the-Loop Retrieval-Augmented Cascade for Document Classification in Regulated Industries

model-releasesarxiv-cs-ai

arXiv:2608.21792v1 Announce Type: new Abstract: Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-go

Lexical Coupling in GUI Element Grounding: Sentence Embeddings Track Labels across Mobile and Web

model-releasesarxiv-cs-ai

arXiv:2608.21794v1 Announce Type: cross Abstract: GUI grounding evaluations that expose UI elements as text metadata often treat high instruction-element embedding similarity as evidence of semantic g

Molecular LLM Agents: From Architectural Design to Scientific Autonomy

arXiv:2608.23104v1 Announce Type: cross Abstract: Molecular science represents an important frontier for LLM-based agents. Unlike general agents that mainly operate over natural language, code, or web

agentsarxiv-cs-ai

MorFiC: Fixing Value Miscalibration for Zero-Shot Quadruped Transfer

arXiv:2603.14554v2 Announce Type: replace Abstract: Generalizing learned locomotion policies across quadrupedal robots with different morphologies remains a challenge. Policies trained on a single rob

safetyarxiv-cs-ro

On the Capability Separation Between World-Model Policy Learning and Imitated World-Action Models

arXiv:2608.22197v1 Announce Type: new Abstract: World-action models predict a future outcome and then infer an associated action. Although this factorization can improve representation learning and da

safetyarxiv-cs-lg

OpenAI subpoenaed by Alabama AG over Hugging Face hack

Alabama's attorney general issued a subpoena to OpenAI on Monday as part of an investigation into how one of its AI agents escaped a supposedly secure testing environment and autonomously hacked anoth

safetythe-verge-ai

Reward-Free Continual Adaptation for Resilient Space Robots

arXiv:2608.23452v1 Announce Type: cross Abstract: Space robots operate in extreme environments where hardware degradation can critically compromise traditional control strategies. While continual rein

Significant improvements to Row-Bot recently. Looking for feedback.

v4.5.0: Added native desktop control, agent execution budgets, concurrency limits, loop protection, and safer local embedding fallback. v4.6.0: Rebuilt agents around durable parent-led orchestration.

local-air-ollama

Applications

The Laws of Context Allocation: Causal Measurement and Closed-Loop Orchestration in Generative Search

arXiv:2608.23252v1 Announce Type: cross Abstract: As Retrieval-Augmented Generation (RAG) shifts toward diverse portfolio generation, it is stymied by two critical bottlenecks: flawed measurement of e

applicationsarxiv-cs-cl