Search: “deployment”

Lot Machine: Multimodal Lot Extraction from Auction Catalogs

model-releasesarxiv-cs-ai

arXiv:2608.30510v1 Announce Type: cross Abstract: For provenance research and art market studies, auction catalogs are an essential resource to trace specific objects over time and space. While histor

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Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance

DGX agent

arXiv:2608.30317v1 Announce Type: cross Abstract: Online dynamic origin-destination (OD) matrix estimation (DODE) calibrates time-dependent OD demand to reproduce observed link-flow trajectories. In o

safetyarxiv-cs-ai

1 Sept 2026

Reference-Grafting Matches Fine-Tuning at Eliciting Sandbagged Capabilities

arXiv:2608.29458v1 Announce Type: cross Abstract: Sandbagging, in which a model deliberately underperforms on an evaluation despite retaining the underlying capability, threatens the safety evaluation

Repair or Resample? Rethinking Failure Debugging in LLM Multi-Agent Systems

arXiv:2608.25920v2 Announce Type: replace Abstract: As large language model (LLM)-based multi-agent systems (MASs) are increasingly applied to long-horizon complex tasks, their reliability has emerged

Responsible Integration of AI in Cancer Genomics: Barriers, Risks, and Pathways to Trustworthy Clinical Translation

arXiv:2608.30912v1 Announce Type: new Abstract: Artificial intelligence (AI) and natural language processing (NLP) are increasingly used to extract, integrate, and interpret biomedical knowledge relev

Rethinking Language's Role in Efficient VLA for Autonomous Vehicles: Toward Smarter, Trustworthy Driving

arXiv:2608.30144v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are reshaping autonomous driving (AD) by unifying perception, reasoning, and control through language, enabling sema

agentsarxiv-cs-ro

Revolutionizing Turn-by-Turn Navigation with Cloud-Edge Deep Learning

arXiv:2608.29073v1 Announce Type: new Abstract: Turn-by-turn (TBT) navigation systems are integral to modern driving experiences, providing real-time audio instructions to guide drivers safely to dest

Scalable Clinical Data Infrastructure and Comparative ML Evaluation for Hospitalisation Risk Prediction in Elderly Patients with Multiple Long-Term Conditions using CPRD

model-releasesarxiv-cs-ai

arXiv:2608.29419v1 Announce Type: cross Abstract: Deep learning architectures are increasingly proposed for patient trajectory modeling in electronic health records (EHRs), yet their advantage over si

SimCRAFT: Distilling Remote Sensing Agents via Synthetic Trajectories and Contextual Retrieval-Augmented Fine-Tuning

arXiv:2608.30277v1 Announce Type: new Abstract: The unprecedented surge in Earth observation data volume and diversity has exposed a critical bottleneck for traditional manual workflows, catalyzing th

SleepWalking: Privileged Representation Shaping for End-to-End Blind Locomotion in Legged Robots

arXiv:2608.30883v1 Announce Type: new Abstract: Partially observable locomotion requires a policy to act when task-relevant properties of the robot--environment state are not fully specified by instan

safetyarxiv-cs-ro

STEP: A Modular Silent Trial Engine for Operational Evaluation of Digital Pathology AI in Routine Workflow

arXiv:2608.28708v1 Announce Type: cross Abstract: Prospective silent trials provide an important bridge between retrospective validation of artificial intelligence (AI) models and their use in clinica

local-aiarxiv-cs-cv

SUB-PLAY: Adversarial Policies against Partially Observed Multi-Agent Reinforcement Learning Systems

arXiv:2402.03741v4 Announce Type: replace-cross Abstract: Recent advancements in multi-agent reinforcement learning (MARL) have opened up vast application prospects, such as swarm control of drones, c

VERA: Authority-Preserving Edge Revocation for Federated AI-Agent Workflows

arXiv:2608.30091v1 Announce Type: new Abstract: Modern agent frameworks compose planners, tool agents, remote services, and shared specialists into runtime delegation graphs, but their revocation APIs

When Does Bigger Help? A Controlled Study of LLM Scale for Ontology Learning

model-releasesarxiv-cs-ai

arXiv:2608.31118v1 Announce Type: new Abstract: The effect of Large Language Model (LLM) scale on ontology learning (OL) performance remains insufficiently characterized. We present a controlled evalu

Wide Learning: Learning to Reach Evidence

arXiv:2608.29608v1 Announce Type: cross Abstract: Machine learning is usually evaluated after an evidence interface has been fixed. A dataset, sensor suite, query language, action set, or experimental

researcharxiv-cs-ai

Zeva: In-Context Causal Learning for Generalizable Embodied Manipulation

arXiv:2608.30880v1 Announce Type: new Abstract: Generalizable embodied manipulation remains difficult to achieve through pretraining alone, due to unseen physical conditions in the real world. We argu

safetyarxiv-cs-ro

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

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

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

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

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

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

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

25 Aug 2026

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