Search: “deployment”

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!!

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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

26 Aug 2026

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

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

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

Hardware

Rethinking Pre-Training and Augmentation for Zero-Shot Cross-City Object Detection

arXiv:2608.24154v1 Announce Type: cross Abstract: Real-world deployment of traffic surveillance systems is bottlenecked by geographic domain shift, in which models trained in one city underperform whe

hardwarearxiv-cs-ai

VIP: Variation-based Iterative-learning Planning for Robotic Navigation

arXiv:2608.24618v1 Announce Type: new Abstract: Over the past decade, autonomous robotic systems have been increasingly deployed in applications such as surveying, search and rescue, and last-mile del

agentsarxiv-cs-ro

Vision Language Model Fusion for Explainable Face Recognition

arXiv:2608.24430v1 Announce Type: new Abstract: Responsible deployment of face verification systems requires more than accurate decisions: systems should also provide interpretable and auditable evide

researcharxiv-cs-cv

Aligned Alone, Misaligned Together: Forecasting Adversarial Capture in LLM Agent Populations

arXiv:2608.22444v1 Announce Type: new Abstract: The unit of AI safety evaluation is still the individual model, yet language-model agents are increasingly deployed in interacting populations that read

safetyarxiv-cs-cl

AUDITA: certified auditing and causal attribution of adverse outcomes in autonomous multi-agent systems

arXiv:2608.22160v1 Announce Type: new Abstract: Physical automation is scaling toward fleets of embodied machines commanded by an AI brain. Early deployments already run factories and warehouses at pr

Local Ai

Backdoor Sentinel: Detecting and Detoxifying Backdoors in Diffusion Models via Temporal Noise Consistency

arXiv:2602.01765v2 Announce Type: replace-cross Abstract: Diffusion models have been widely deployed in AIGC services, but their reliance on opaque training data exposes them to backdoor attacks. In p

local-aiarxiv-cs-ai

Beyond the Harness: End-to-End Optimization of Context Artifacts for Enterprise Text-to-SQL

arXiv:2608.22830v1 Announce Type: new Abstract: Deploying LLMs for enterprise Text-to-SQL is bottlenecked less by the model than by what context reaches it: business logic spans thousands of tables, a

Buried in Textual Debt: Context Pruning with Visual Evidence Preservation for MLLM Agents

arXiv:2608.22963v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed as multi-step agents, where explicit reasoning supports task decomposition and tool c

Applications

Conformal Risk Minimization for Semi-Supervised Domain Adaptation via Optimal Transport

arXiv:2608.23153v1 Announce Type: new Abstract: In high-stakes healthcare applications, machine learning models are frequently trained on data from one patient population and deployed on another, crea

applicationsarxiv-cs-lg

Environmental Injection Attacks against GUI Agents in Realistic Dynamic Environments

arXiv:2509.11250v3 Announce Type: replace-cross Abstract: Graphical User Interface (GUI) agents are increasingly deployed to interact with online web services, yet their exposure to open-world content

agentsarxiv-cs-cv

ExplainGuard: A Zero Trust Framework for Post-Hoc Explanation Integrity Guarantees in Blackbox XAI Models

arXiv:2608.21803v1 Announce Type: cross Abstract: As machine learning (ML) models are increasingly deployed in high-stakes environments, explainable AI (XAI) methods like SHAP and LIME have become ess

Local Ai

GeoQ: Geometry-Aware Conditional Quantile Error Estimation for Scientific Surrogate Models

arXiv:2608.21652v1 Announce Type: new Abstract: Neural-network surrogate models are increasingly used to accelerate scientific simulations, but their deployment in extrapolative and autoregressive set

local-aiarxiv-cs-lg

How Agents Represent Humans: Human-Directed Stereotypes in an Open Agent Social Network

arXiv:2608.22192v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in persistent social environments, where generated claims can be posted, replied to, remembered, and reused.

safetyarxiv-cs-cl

InjecMEM: Memory Injection Attack on LLM Agent Memory Systems

arXiv:2608.23471v1 Announce Type: cross Abstract: Memory is becoming a default subsystem in deployed LLM agents to provide persistent personalization and continuity. This naturally prompts a question:

agentsarxiv-cs-ai

Learning from the Test: Self-Referential Differential Testing for Deep RL Agents

arXiv:2608.22284v1 Announce Type: cross Abstract: Deep Reinforcement Learning (DRL) has achieved significant success in complex decision-making problems. As DRL systems are increasingly deployed in re

M^3ISR: A Multi-Modal Multi-View Benchmark for 3D/4D Gaussian Splatting and Feedforward Compression

model-releasesarxiv-cs-cv

arXiv:2608.22465v1 Announce Type: new Abstract: High-fidelity free-viewpoint video (FVV) and interactive rendering increasingly rely on explicit Gaussian representations, yet practical deployment rema

Measuring Activation Control in Large Language Models

arXiv:2608.21664v1 Announce Type: new Abstract: Safe deployment of increasingly capable models will likely come to rely on latent-space monitoring as a complement to behavioral evaluations, especially

Models in the Same Family are NOT Trust-Equivalent

model-releasesarxiv-cs-cl

arXiv:2508.13533v2 Announce Type: replace Abstract: Within a model family, a smaller variant is often deployed as a drop-in replacement for a larger one when their performance is similar. However, per

Multimodal-Language-Model-Driven Interaction and Companionship for Service Robots in Elderly-Care Facilities

arXiv:2608.21387v1 Announce Type: new Abstract: Service robots are increasingly deployed in elderly-care facilities to alleviate caregiver workload and enhance the quality of daily care. However, most

safetyarxiv-cs-ro

NeuroPrefetcher: Storage-Aware Sparse LLM Inference via Delta Prefetching

model-releasesarxiv-cs-lg

arXiv:2608.22643v1 Announce Type: cross Abstract: Deploying large language models on edge devices is increasingly limited by a widening gap between model size and available memory. Existing approaches

No One Model Catches Every Harm: Benchmarking Content Moderation Across Safety Scenarios

arXiv:2608.21775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications, yet they remain vulnerable to generating harmful content. From advers

safetyarxiv-cs-cl

Now introducing Gemini Enterprise for Financial Services

model-releasesgoogle-cloud-ai

Protecting capital in today's markets requires immense speed and precision. A financial analyst preparing a deal memo works across licensed market data, internal models, and confidential client files.

Now introducing Gemini Enterprise for Legal

model-releasesgoogle-cloud-ai

Few professions are as exacting as the practice of law. A team reviewing a contract or building a case works inside strictly privileged information, firm-specific playbooks, and a body of law that cha

Privileged Critic Training Enables Sensor-Free Thruster Fault Adaptation in End-to-End RL

arXiv:2608.22976v1 Announce Type: new Abstract: Fault-tolerant navigation for thruster-actuated robots requires online adaptation to failures that are neither binary nor fully observable: thrusters ma

safetyarxiv-cs-ro

Pruned Traffic Trees: Native Semantic Compression with a Protocol-Structured Model Family for Encrypted Traffic Classification

arXiv:2608.21874v1 Announce Type: cross Abstract: Deep learning has achieved strong performance in encrypted traffic classification (ETC), yet its computational cost limits deployment on resource-cons

PsychJail: Exploring Psychological Jailbreaks via Multi-Turn Persuasion of LLM Policies

arXiv:2608.23028v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in education, healthcare, policy advising, and other interactive settings, where users engage the

RACO: Reliability-Aware Coarse-Goal Optimization for Inspection-Oriented UAV Vision-Language Navigation

arXiv:2608.22678v1 Announce Type: cross Abstract: UAV vision-language navigation (UAV-VLN) is commonly evaluated as goal reaching, but inspection-oriented deployment requires the agent to stop within

agentsarxiv-cs-ai

Reinforcement Learning on Benign Facts Amplifies Leakage of Memorized Private Data

arXiv:2608.21727v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is deployed to make models better at reasoning tasks, but its side effect on what models will di

SA-RSQ: A Versatile Sparse Representation Framework for Multi-modal Recommender Systems

arXiv:2608.22979v1 Announce Type: new Abstract: Deploying high-dimensional multimodal features in industrial recommender systems incurs substantial storage and latency overhead. Hard quantization is c

Scalable quantum simulation of continuous-time generative models via tensor networks

arXiv:2608.21700v1 Announce Type: cross Abstract: Continuous-time flow and diffusion models are widely used across many application domains, from large-scale deployment in computer vision and protein

Spine-Branch Coordination for Multi-agent Computer Use

arXiv:2608.22077v1 Announce Type: new Abstract: Computer use agents (CUAs) are increasingly deployed as multi-agent systems that decompose a task into multiple subtasks executed across parallel virtua

agentsarxiv-cs-cl