Search: “deployment”

arXiv:2411.09241v5 Announce Type: replace Abstract: We present the design, development, and experimental validation of BlueME, a compact magnetoelectric (ME) antenna array system for underwater robot-

agentsarxiv-cs-ro

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Can LLMs Reason Structurally? Benchmarking via the Lens of Data Structures

DGX agent

arXiv:2505.24069v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are deployed on increasingly complex tasks that require multi-step decision-making. Understanding their algorithm

model-releasesarxiv-cs-ai

2 Jun 2026

Agents

Constitutional Black-Box Monitoring for Scheming in LLM Agents

arXiv:2603.00829v2 Announce Type: replace-cross Abstract: Safe deployment of Large Language Model (LLM) agents in autonomous settings requires reliable oversight mechanisms. A central challenge is det

agentsarxiv-cs-ai

Local Ai

CRePE: Convolution-aware Relative Importance in Post-training Pruning with Efficient Search

arXiv:2606.01544v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in practice incurs substantial memory and computational costs. Post-training pruning (PTP) is an effective approa

local-aiarxiv-cs-lg

Local Ai

DiscourseFlip: An Oblique Discourse-Level Opinion Manipulation Attack against Black-box Retrieval-Augmented Generation

arXiv:2606.01212v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are widely deployed and increasingly influential, but their reliance on external corpora exposes new secu

local-aiarxiv-cs-ai

Distillation of Large Language Models via Concrete Score Matching

arXiv:2509.25837v3 Announce Type: replace-cross Abstract: Large language models (LLMs) deliver remarkable performance but are costly to deploy, motivating knowledge distillation (KD) for efficient inf

Do Text Edits Generalize to Visual Generation? Benchmarking Cross-Modal Knowledge Editing in UMMs

model-releasesarxiv-cs-cl

arXiv:2606.00477v1 Announce Type: new Abstract: Unified multimodal models (UMMs) have emerged as a promising paradigm for general-purpose multimodal intelligence. As they are deployed in real-world ap

Drifting Preference Optimization for One-Step Generative Models

arXiv:2606.02521v1 Announce Type: cross Abstract: One-step text-to-image generators are attractive for deployment because they generate an image with a single forward pass, but preference finetuning t

safetyarxiv-cs-cv

DRL-Based Pose Control for Double-Ackermann Robots Under Actuation Uncertainties

arXiv:2606.00313v1 Announce Type: cross Abstract: Robust deployment of deep reinforcement learning (DRL) policies on real robots remains challenging due to discrepancies between simulation and real-wo

Dynamic Coordination Strategy Selection for Enterprise Multi-Agent Systems

arXiv:2606.00804v1 Announce Type: cross Abstract: Enterprise multi-agent systems increasingly expose multiple coordination patterns, but deployments often lack evidence for when to use consensus, deba

Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence

arXiv:2606.01470v1 Announce Type: cross Abstract: Whether physics foundation models can be usefully deployed on laboratory experiments remains an open question for scientific machine learning (ML). We

researcharxiv-cs-ai

Event-Based Vision in Space: Applications, Trends, and Future Directions

arXiv:2606.01280v1 Announce Type: new Abstract: Earth Observation (EO) is undergoing a significant transformation driven by the deployment of novel sensing technologies. Traditional frame-based optica

researcharxiv-cs-cv

Fast-SAM3D: 3Dfy Anything in Images but Faster

model-releasesarxiv-cs-cv

arXiv:2602.05293v2 Announce Type: replace Abstract: SAM3D enables scalable, open-world 3D reconstruction from complex scenes, yet its deployment is hindered by prohibitive inference latency. In this w

From Empathy to Personalized Empathy: Adapting Empathetic Strategies to Individual Users

arXiv:2606.00728v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in long-term interactions with users, empathy has become an increasingly important capability.

researcharxiv-cs-cl

From Segments to Scenes: Temporal Understanding in Autonomous Driving via Vision-Language Model

arXiv:2512.05277v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as the perception and reasoning backbone of autonomous agents acting in the wild, with

GovAI-Pipe: A Layered AI Governance Pipeline for Citizen-Facing AI in Turkey's e-Government Gateway

arXiv:2606.01417v1 Announce Type: new Abstract: Turkey's e-Government Gateway (e-Devlet) serves over 68 million registered users with more than 9,200 government services, and is increasingly integrati

HLL: Can Agents Cross Humanity's Last Line of Verification?

arXiv:2606.02449v1 Announce Type: new Abstract: Multimodal agents are increasingly expected to operate interfaces on behalf of users, raising a central deployment question: can they truly substitute f

InFerActive: Interactive Tree-Based Exploration of LLM Sampling for Safety Evaluation

arXiv:2512.10234v2 Announce Type: replace-cross Abstract: Even LLMs that appear safe during evaluation can still produce harmful responses in deployment. Because stochastic sampling yields different r

Interpretability in Deep Time Series Models Demands Semantic Alignment

arXiv:2602.02239v2 Announce Type: replace Abstract: Deep time series models continue to improve predictive performance, yet their deployment remains limited by their black-box nature. In response, exi

KG-FairDiff: Knowledge Graph-Guided Prompt Refinement for Demographically Fair Text-to-Image Generation

arXiv:2606.01282v1 Announce Type: new Abstract: Text-to-Image (TTI) systems are now everyday infrastructure for journalism, education, advertising, and public communication, and the demographic and cu

safetyarxiv-cs-cv

LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models

arXiv:2606.00573v1 Announce Type: new Abstract: Vision-language models (VLMs) deliver strong multimodal reasoning capabilities, but their large computational cost and high parameter counts make deploy

LastAct: Trajectory-Guided Latest-Activity Localization for Real-Time Smart-Home Activity Recognition

arXiv:2606.00260v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from ambient sensors enables smart-home applications such as health monitoring and assisted living. In realistic deploy

researcharxiv-cs-cv

Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs

arXiv:2606.00726v1 Announce Type: new Abstract: Strong reasoning depends not only on model knowledge but also on how effectively cognitive behaviors are deployed during generation. Existing methods of

researcharxiv-cs-ai

Limits of Resolution Equivariance in Fourier Neural Operators

arXiv:2606.00677v1 Announce Type: new Abstract: Fourier Neural Operators are often assumed to generalize across spatial resolutions, enabling training on a coarse grid and deployment on a finer grid.

researcharxiv-cs-lg

Linguistics-Aware Non-Distortionary LLM Watermarking

arXiv:2606.00613v1 Announce Type: cross Abstract: Watermarking should identify language-model output without degrading quality or limiting verification to the model provider. Multilingual deployment m

researcharxiv-cs-ai

MidSteer: Optimal Affine Framework for Steering Generative Models

arXiv:2605.05220v2 Announce Type: replace-cross Abstract: Steering intermediate representations has emerged as a powerful strategy for controlling generative models, particularly in post-deployment al

Multi-Agent Computer Use

model-releasesarxiv-cs-cl

arXiv:2606.01533v1 Announce Type: cross Abstract: Computer use agents (CUAs) today are primarily deployed as single serial agents. This setup is suboptimal for complex long-horizon tasks that benefit

Optimal Regularization for Performative Learning

arXiv:2510.12249v2 Announce Type: replace Abstract: In performative learning, the data distribution reacts to the deployed model - for example, because strategic users adapt their features to game it

PaCX-MAE: Physiology-Augmented Chest X-Ray Masked Autoencoder

arXiv:2606.01537v1 Announce Type: new Abstract: Clinical diagnosis often requires combining imaging with physiological measurements, yet deployed models typically operate on unimodal data. We present

researcharxiv-cs-cv

Parameter-Free and Group Conditional Online Conformal Prediction

arXiv:2606.00419v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) is critical for the deployment of machine learning predictors in real-world scenarios where the data distribution may

Physically-Constrained Mamba-SDE for Remaining Useful Life Prediction under Irregular Observations

arXiv:2606.01894v1 Announce Type: new Abstract: Accurate Remaining Useful Life prediction is critical for industrial predictive maintenance. However, real-world deployment is challenging due to the ir

Position Paper: Post-Solve Robustness in Decision Engines: Feasible Regions and Smoothness Under Perturbations

arXiv:2606.00002v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) decision engines routinely output nominally optimal plans for high-stakes industrial systems. Yet deployment rar

ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression

arXiv:2606.00494v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) and Low-Rank Adaptation (LoRA) constitute the standard pipeline for efficient Large Language Model (LLM) deployment. Ho

Applications

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning

arXiv:2606.02576v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, but real-world deployment requires them to continually a

applicationsarxiv-cs-cv

Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment

arXiv:2606.00369v1 Announce Type: cross Abstract: Safe global deployment of AI models requires alignment with human values that vary across cultures. Yet rater pools in safety evaluation datasets rema

Applications

Quantized Reasoning Models Think They Need to Think Longer, but They Do Not

arXiv:2606.00206v1 Announce Type: new Abstract: Post-training quantization (PTQ) is widely used to deploy large language models efficiently, but its effect on reasoning models is not well understood.

applicationsarxiv-cs-lg

RoboStressBench: Benchmarking VLM Robustness to Physical Visual Stress in Embodied Scenes

model-releasesarxiv-cs-cv

arXiv:2606.00828v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong visual understanding and are increasingly deployed in embodied AI systems, where reliable perception und

ROGUE: Misaligned Agent Behavior Arising from Ordinary Computer Use

arXiv:2606.00341v1 Announce Type: cross Abstract: As AI agents are increasingly deployed in real personal and corporate settings (email accounts, development workflows, company databases, etc.), safet

Safety Game: Inference-Time Alignment of Black-Box LLMs via Constrained Optimization

arXiv:2510.09330v3 Announce Type: replace Abstract: Ensuring that large language models (LLMs) comply with safety requirements is a central challenge in AI deployment. Existing alignment approaches pr

Applications

Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning

arXiv:2307.05213v3 Announce Type: replace-cross Abstract: Many real-world optimization problems contain parameters that are unknown before deployment time, either due to stochasticity or to lack of in

applicationsarxiv-cs-ai

SEArch: Optimistic Policy Selection Between Scene Noise and Drift for UAV Radar Search

arXiv:2606.01325v1 Announce Type: cross Abstract: Unmanned Aerial Vehicles (UAVs) equipped with radar sensors are deployed for target search missions in diverse environments, where targets exhibit cha

SilentDrift: Exploiting Action Chunking for Stealthy Backdoor Attacks on Vision-Language-Action Models

arXiv:2601.14323v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are increasingly deployed in safety-critical robotic applications, yet their security vulnerabilities rema

SPADE-Bench: Evaluating Spontaneous Strategic Deception in Agents via Plan-Action Divergence

arXiv:2606.02380v1 Announce Type: cross Abstract: As LLM-based agents expand their operational scope, reliability becomes a prerequisite for real-world deployment. However, in practical applications,

SPADER: Step-wise Peer Advantage with Diversity-Aware Exploration Rewards for Multi-Answer Question Answering

arXiv:2606.00593v1 Announce Type: cross Abstract: Large language models are increasingly deployed as tool-augmented agents to acquire information beyond parametric knowledge. While recent work has imp

Hardware

STaR-KV: Spatio-Temporal Adaptive Re-weighting for KV Cache Compression in GUI Vision-Language Models

arXiv:2606.01790v1 Announce Type: cross Abstract: Vision-language-model-based graphical user interface (GUI) agents have shown broad automation capabilities, yet deployment is bottlenecked by a key-va

hardwarearxiv-cs-ai

Agents

STEM: Semantic Target Search and Exploration using MAVs in Cluttered Environments

arXiv:2606.00762v1 Announce Type: new Abstract: Autonomous target search is crucial for deploying Micro Aerial Vehicles (MAVs) in emergency response and rescue missions. Existing approaches either foc

agentsarxiv-cs-ro

Tutorials

Towards a Physics Foundation Model

arXiv:2509.13805v4 Announce Type: replace-cross Abstract: Foundation models have revolutionized natural language processing through a ``train once, deploy anywhere'' paradigm, where a single pre-train

tutorialsarxiv-cs-ai

Towards Understanding Modality Interaction in Multimodal Language Models via Partial Information Decomposition

arXiv:2606.00959v1 Announce Type: new Abstract: Understanding modality interaction in multimodal large language models (MLLMs) is central to reliable deployment. We introduce Partial Information Decom