Search: “deployment”

arXiv:2608.26209v1 Announce Type: cross Abstract: Data-driven software systems are increasingly deployed in high-stakes socio-economic domains, from criminal justice to financial lending. However, the

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Safety

Five Primitives for Governing Autonomous AI Agents at Runtime

DGX agent

arXiv:2608.26696v1 Announce Type: new Abstract: Enterprise deployments of autonomous AI agents inherit a control model built for human users and long-lived services, and the fit fails in three specifi

safetyarxiv-cs-ai

28 Aug 2026

Tutorials

How Decathlon runs demand forecasting at scale with Chronos-2

Decathlon, one of the world's largest sporting goods retailers, forecasts weekly demand for tens of thousands of products across multiple continents. Learn how they deployed Chronos-2 on AWS to improv

tutorialsaws-ml-blog

INTENT-AS-A-TOOL Makes it Easy to Track Agentic Misalignment

arXiv:2608.27348v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as autonomous agents, safety failures increasingly involve consequential actions. We study agentic misalign

safetyarxiv-cs-cl

KISS-GS: 3D Gaussian Splatting Compression Kept Simple

arXiv:2608.26948v1 Announce Type: new Abstract: Scene reconstruction with 3D Gaussian Splatting (3DGS) has become common, however deployment remains painful as the uncompressed file sizes can be massi

applicationsarxiv-cs-cv

Leakage-Free Evaluation and Distribution-Robust Spatio-Temporal Graph Learning for Inductive Kriging

arXiv:2509.23631v2 Announce Type: replace Abstract: Inductive kriging estimates values at unobserved locations from sparse sensor data, enabling continuous field reconstruction when dense deployment i

researcharxiv-cs-lg

LoRA as Oracle

arXiv:2601.11207v2 Announce Type: replace-cross Abstract: Practitioners increasingly deploy neural networks they did not train, and must audit them after the fact for hidden backdoors, without the tra

Making Clinical Language Models Auditable: Concept-Guided Fine-Tuning for Robust Prediction

arXiv:2608.27397v1 Announce Type: cross Abstract: Clinical language models can achieve strong in-hospital accuracy yet fail under deployment shifts because they exploit note-specific artifacts (e.g.,

Agents

Marine Autonomous Vehicle Fleet Scheduling to Maximise Scientific Impact

arXiv:2608.27271v1 Announce Type: cross Abstract: The marine science community increasingly relies on Marine Autonomous Vehicles (MAVs) to collect the critical environmental data required to understan

agentsarxiv-cs-ro

Memory Anchors for Continual Robot Learning

model-releasesarxiv-cs-ro

arXiv:2608.26545v1 Announce Type: new Abstract: Robot policies deployed in the wild should have the capability to continually learn new tasks without forgetting existing behaviors. A common approach t

Prediction of Prediction (PoP): Inter-Layer Activation Fusion for Single-Pass Hallucination Detection in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.27165v1 Announce Type: new Abstract: Autoregressive large language models (LLMs) routinely generate factually incorrect outputs with high decoding confidence, limiting their deployment in h

Privacy Without Regret: Differentially Private Inference-Time Alignment

model-releasesarxiv-cs-lg

arXiv:2608.26324v1 Announce Type: new Abstract: Best-of-N (BoN) sampling is the simplest and most widely deployed inference-time alignment strategy, but it suffers from two distinct problems: reward h

RedEvoAgent: Automatic Red-Teaming Agent with Experience-Driven Skill Evolution

arXiv:2608.27439v1 Announce Type: cross Abstract: LLM-based agents are increasingly deployed in product-level execution harnesses, where jailbreaks can trigger harmful tool use and persistent state ch

safetyarxiv-cs-ai

Safety Does Not Compose: Non-Decaying Loop State for Autonomous LLM Agents

arXiv:2608.27141v1 Announce Type: cross Abstract: Large language model agents are increasingly deployed as autonomous loops. Starting from one human goal, such a system repeatedly discovers work, plan

safetyarxiv-cs-ai

SAREF-based Ontology for Distributed AI Workflows across the Edge-Fog-Cloud Continuum

arXiv:2608.26160v1 Announce Type: new Abstract: Nowadays semantic models provide limited support for representing distributed AI workflows and their execution across heterogeneous edge, fog, and cloud

A Visual Dependence-Aware Framework for Multimodal Unsupervised Continual Post-Training

arXiv:2608.26095v1 Announce Type: new Abstract: In this paper, we explore a novel task of Multimodal Unsupervised Continual Post-Training (MU-CPT), enabling deployed MLLMs to continually evolve from s

safetyarxiv-cs-cv

Addressing the Reasoning Gap: Mechanistic Circuit-Based Knowledge Editing in Large Language Models

arXiv:2604.05876v2 Announce Type: replace Abstract: Deploying Large Language Models (LLMs) in real-world dynamic environments raises the challenge of updating their pre-trained knowledge. While existi

applicationsarxiv-cs-cl

Can You Trust Frozen Hematology Foundation Models under Acquisition Shift?

model-releasesarxiv-cs-cv

arXiv:2608.25148v1 Announce Type: new Abstract: Frozen hematology foundation-model (FM) embeddings reach near-saturated in-domain white-blood-cell (WBC) accuracy, but clinical deployment demands relia

CrossMambaTuning: Synergistic Spatial and Cross-Layer Adaptation for Machine Vision Compression

model-releasesarxiv-cs-cv

arXiv:2608.25568v1 Announce Type: new Abstract: To reduce deployment cost and retraining overhead, adapting pretrained learned image compression (LIC) models to downstream machine vision tasks has att

Energy Yield and Lifetime Climate Classification via Machine Learning for Optimizing Photovoltaic Module Design and Materials

arXiv:2608.25448v1 Announce Type: cross Abstract: To resiliently and sustainably meet our future energy demand, photovoltaic (PV) modules must be deployed across a broad and diverse range of geographi

researcharxiv-cs-lg

Fairness-Aware Test-Time Prompt Tuning

arXiv:2608.25707v1 Announce Type: new Abstract: Vision-language models have displayed remarkable capabilities in multi-modal understanding and are increasingly used in critical applications where econ

safetyarxiv-cs-lg

Rollout-Decoded Reconstruction for Long-Horizon Prediction in Latent World Models

arXiv:2608.25017v1 Announce Type: new Abstract: A latent world model trains its decoder on latents anchored to observations, then deploys it on the model's own free-running rollout, hundreds of steps

researcharxiv-cs-lg

Sequential Object Placement Optimization with Convex Decomposition

arXiv:2608.25162v1 Announce Type: new Abstract: Robotic object packing has been a core challenge for robotic deployment in logistics, industry, etc., due to the curse of dimensionality in combinatoria

applicationsarxiv-cs-ro

Agents

Simulating Cognitive Smart Freight Corridors with Agent-Based Models and Reinforcement Learning

arXiv:2608.25193v1 Announce Type: cross Abstract: Smart freight corridors offer a practical pathway for connected and automated vehicle (CAV) deployment in freight transportation, but physical experim

agentsarxiv-cs-lg

Tutorials

Transforms for LLM Quantization: The Great Inversion and Format Co-Design

arXiv:2608.25188v1 Announce Type: new Abstract: Most competitive 4-bit LLM research pipelines now open the same way: apply a linear, function-preserving transform (rotation, scaling, permutation, non-

tutorialsarxiv-cs-lg

Trojan Attacks on Neural Network Controllers for Robotic Systems

arXiv:2602.05121v3 Announce Type: replace-cross Abstract: Neural network controllers are increasingly deployed in robotic systems for tasks such as trajectory tracking and pose stabilization. However,

applicationsarxiv-cs-ro

Trust the Mass: Forced Weights in KV-Cache Eviction

model-releasesarxiv-cs-cl

arXiv:2608.25230v1 Announce Type: cross Abstract: Every deployed sparse-attention or KV-cache-eviction rule keeps a subset of the keys, discards the rest, and renormalizes the attention weights over t

— Upgrades coming to @FlowbyGoogle — Extend scenes in the @GeminiApp (globally rolling out for all Google AI Plus, Pro and Ultra subscribers…

model-releasesgoogle-ai--x

— Upgrades coming to @FlowbyGoogle — Extend scenes in the @GeminiApp (globally rolling out for all Google AI Plus, Pro and Ultra subscribers) — Build directly in @GoogleAIStudio — Deploy on the Gemini

VDAR-Router: Adaptive LLMs Routing via Verbalized Query Difficulty Analysis Retrieval

arXiv:2607.18098v2 Announce Type: replace Abstract: Large language models are increasingly used in practical systems, making efficient model selection important for reducing deployment cost. LLM routi

researcharxiv-cs-cl

Virgil: Navigating Explainability for Transformer-based Language Models

arXiv:2608.25555v1 Announce Type: new Abstract: Explainability for transformer-based language models is becoming crucial as these systems are deployed in high-stakes applications. As a result, the eco

researcharxiv-cs-cl

Adaptive Influence Graphs for Failure Attribution in Multi-Agent Systems

arXiv:2608.24361v1 Announce Type: new Abstract: Multi-agent LLM systems are increasingly deployed in real-world applications, where failures can be costly and difficult to localize. Despite growing ef

Adaptive Multi-Mode Out-of-Distribution Detection for Trajectory Prediction in Autonomous Vehicles

arXiv:2509.13577v3 Announce Type: replace Abstract: Trustworthy trajectory prediction grounds autonomous vehicle (AV) safety, yet deployed models inevitably face out-of-distribution (OOD) scenes. Prio

safetyarxiv-cs-cv

Tools

Amazing deep dive on K3!!

Mahadev Konar co‑hosted a 2‑hour live broadcast titled “Amazing deep dive on K3!!” with Together Compute. The session explored scaling the Kimi K3 language model for inference, detailing deployment st

toolstogether-ai--x

Are Android GUI Agents Robust Against Runtime Anomalies? AnTrap: Evaluating Agents in Dynamic Adversarial Environments

arXiv:2608.24099v1 Announce Type: new Abstract: GUI agents often encounter dynamic anomalies when deployed on Android devices, from unexpected pop-ups to action misuse, yet existing benchmarks lack sy

Bridging Teacher Expectations and Robot Learning via Coupling Dynamics

arXiv:2608.23994v1 Announce Type: new Abstract: Human-robot teaching focuses on enabling nontechnical experts to customize robots according to their needs after deployment. With recent advances in mac

researcharxiv-cs-ro

Can Large Language Models Still Explain Themselves? Investigating the Impact of Quantization on Self-Explanations

arXiv:2601.00282v2 Announce Type: replace-cross Abstract: Quantization is widely used to accelerate inference and streamline the deployment of large language models (LLMs), yet its effects on self-exp

Compression Trinity: Exploring Sparsity, Quantization, and Low-Rank Approximations for LLM Compression

arXiv:2608.24070v1 Announce Type: new Abstract: Prohibitive computational and environmental costs impede the scalable deployment of Large Language Models (LLMs). Traditional compression techniques (sp

Lightweight GenAI for Network Traffic Generation: Fidelity, Augmentation, and Classification

arXiv:2603.25507v2 Announce Type: replace-cross Abstract: Network Traffic Classification (NTC) increasingly relies on data-driven models, yet its practical deployment is often constrained by limited l

Tutorials

Macro-Operator Generation and Predicate Selection for TAMP Operator Learning

arXiv:2608.23629v1 Announce Type: cross Abstract: Creating symbolic operators by hand is one of the main bottlenecks in deploying Task and Motion Planning systems (TAMP). Recent works show that these

tutorialsarxiv-cs-ai

More GPUs or a Smaller Cache? Tensor Parallelism versus KV Compression for Memory-Bound LLM Serving

arXiv:2608.23962v1 Announce Type: new Abstract: When an LLM serving deployment runs out of KVcache room, there are two well-established ways out. Tensor parallelism shards the weights and the KV cache

NeuronTune: Fine-Grained Neuron Modulation for Balanced Safety-Utility Alignment in LLMs

arXiv:2508.09473v2 Announce Type: replace-cross Abstract: Ensuring robust safety alignment while preserving utility is critical for the reliable deployment of Large Language Models (LLMs). However, cu

safetyarxiv-cs-ai

Local Ai

Not All Tokens Are Equal: Region-Aware Consistency Repair of Backdoors in MLLMs

arXiv:2608.24354v1 Announce Type: cross Abstract: MLLMs are increasingly deployed in user-facing applications, yet they inherit backdoor risks from the pipelines used to construct them: triggers may r

local-aiarxiv-cs-ai

Hardware

Output-Level Regularization Eliminates the Seed Lottery in Single-GPU VLA Fine-Tuning

arXiv:2606.13856v2 Announce Type: replace Abstract: Fine-tuning a vision-language-action model (VLA-JEPA) on a single GPU should be simple: load a pretrained checkpoint, run training, deploy. There is

hardwarearxiv-cs-ro

Agents

PinSieve: Production Selective VLM Serving and a Governed Memory Flywheel for Enterprise Content-Quality Triage

arXiv:2608.24040v1 Announce Type: new Abstract: Enterprise AI agents in production often need to be bounded, stateful, observable, and governable rather than fully autonomous. We present PinSieve, a p

agentsarxiv-cs-lg

Preference Data Selection for Mitigating the Alignment Tax in Large Language Models

arXiv:2608.24192v1 Announce Type: new Abstract: Aligning large language models to human preferences is crucial for real-world deployment but frequently incurs an alignment tax, leading to the catastro

PROOF-Gen: From Optimized Data to Better Distillation

researchapple-ml-research

Supervised fine-tuning on teacher-generated trajectories is the standard first stage for distilling tool-calling capabilities into deployable models. Post-training pipelines that drive shipped tool-ca

Provenance Guided Incremental Learning Under Evolving Concept Definitions

arXiv:2608.23893v1 Announce Type: new Abstract: Learning systems deployed over long periods must adapt not only to statistical changes in incoming data, but also to revisions of the definitions that g

Reading Is Not Using: Retrieval, Judgment, and the Design of AI Financial Research Workflows

arXiv:2608.24842v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as AI analysts to process financial disclosures and support AI-assisted investment decisions. Y