Search: “deployment”

Personalized Benchmarking: Evaluating LLMs by Individual Preferences

arXiv:2604.18943v1 Announce Type: new Abstract: With the rise in capabilities of large language models (LLMs) and their deployment in real-world tasks, evaluating LLM alignment with human preferences

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Applications

Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption

DGX agent

arXiv:2510.18333v2 Announce Type: replace-cross Abstract: Despite progress in watermarking algorithms for large language models (LLMs), real-world deployment remains limited. We argue that this gap st

applicationsarxiv-cs-cl

22 Apr 2026

ProjLens: Unveiling the Role of Projectors in Multimodal Model Safety

arXiv:2604.19083v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success in cross-modal understanding and generation, yet their deployment is threate

safetyarxiv-cs-ai

Prompt to Pwn: Automated Exploit Generation for Smart Contracts

arXiv:2508.01371v3 Announce Type: replace-cross Abstract: Smart contracts are important for digital finance, yet they are hard to patch once deployed. Prior work has mainly explored LLMs for smart con

applicationsarxiv-cs-ai

Protecting Bystander Privacy via Selective Hearing in Audio LLMs

model-releasesarxiv-cs-ai

arXiv:2512.06380v3 Announce Type: replace-cross Abstract: Audio Large language models (LLMs) are increasingly deployed in the real world, where they inevitably capture speech from unintended nearby by

SimDiff: Depth Pruning via Similarity and Difference

arXiv:2604.19520v1 Announce Type: new Abstract: Depth pruning improves the deployment efficiency of large language models (LLMs) by identifying and removing redundant layers. A widely accepted standar

researcharxiv-cs-ai

Agents

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving

arXiv:2604.19145v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have become central to autonomous driving systems, yet their deployment is severely bottlenecked by the massive computat

agentsarxiv-cs-ai

Startups are building the next big thing with Google Cloud AI

model-releasesgoogle-cloud-ai

The future is taking shape in Las Vegas this week, where the world’s leading startups are showcasing their groundbreaking AI work at Google Cloud Next. Whether they need the top AI models, infrastruct

Local Ai

StrikeWatch: Wrist-worn Gait Recognition with Compact Time-series Models on Low-power FPGAs

arXiv:2510.24738v2 Announce Type: replace-cross Abstract: Running offers substantial health benefits, but improper gait patterns can lead to injuries, particularly without expert feedback. While prior

local-aiarxiv-cs-lg

Industry

The DP World Tour tees off a new era of connectivity by tapping Amazon Leo

The DP World Tour will become the first professional sports organization to use Amazon Leo as its official satellite connectivity partner, deploying low Earth orbit or LEO terminals at tournament venu

industrysiliconangle

Towards Streaming Target Speaker Extraction via Chunk-wise Interleaved Splicing of Autoregressive Language Model

arXiv:2604.19635v1 Announce Type: cross Abstract: While generative models have set new benchmarks for Target Speaker Extraction (TSE), their inherent reliance on global context precludes deployment in

researcharxiv-cs-ai

TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards

arXiv:2512.07761v3 Announce Type: replace Abstract: Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment.

safetyarxiv-cs-ai

Tools

Try Kimi K2.6 now on the AI Native Cloud: http://www.together.ai/models/kimi-k26#

Kimi K2.6 is now available for use on Together AI's cloud platform, which offers AI model deployment and inference services. This announcement indicates the model has been added to Together AI's roste

toolstogether-ai--x

Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items

arXiv:2604.19748v1 Announce Type: new Abstract: Recent advances in image generation and editing have opened new opportunities for virtual try-on. However, existing methods still struggle to meet compl

What’s new with compute: Scaling core and agentic workloads

model-releasesgoogle-cloud-ai

At Google Cloud Next, we’re announcing a range of compute capabilities to enable your core general purpose and AI workloads for the agentic world with higher performance and lower costs. Why it matter

What’s next in Google AI infrastructure: Scaling for the agentic era

model-releasesgoogle-cloud-ai

AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem

Tutorials

Workspace agents

Workspace agents are AI systems designed to automate tasks and workflows within collaborative work environments, likely covering how these agents can handle scheduling, communication, document managem

tutorialsopenai

A Survey of Spatial Memory Representations for Efficient Robot Navigation

arXiv:2604.16482v1 Announce Type: new Abstract: As vision-based robots navigate larger environments, their spatial memory grows without bound, eventually exhausting computational resources, particular

Agents

AppZen targets accounts payable bottleneck with new AI agent service center

Autonomous finance platform company AppZen Inc. today launched AP Inbox Service Center, a new accounts payable service that deploys eight prebuilt artificial intelligence agents to automate how financ

agentssiliconangle

Are they lovers or friends? Evaluating LLMs' Social Reasoning in English and Korean Dialogues

arXiv:2510.19028v3 Announce Type: replace Abstract: As LLMs are increasingly deployed in real-world interactions, their social reasoning in interpersonal communication becomes critical. To explore the

applicationsarxiv-cs-cl

Bielik Guard: Efficient Polish Language Safety Classifiers for LLM Content Moderation

model-releasesarxiv-cs-cl

arXiv:2602.07954v4 Announce Type: replace Abstract: As Large Language Models (LLMs) become increasingly deployed in Polish language applications, the need for efficient and accurate content safety cla

BridgeEQA: Virtual Embodied Agents for Real Bridge Inspections

arXiv:2511.12676v2 Announce Type: replace Abstract: Deploying embodied agents that can answer questions about their surroundings in realistic real-world settings remains difficult, partly due to the s

Chasing Ghosts: A Simulation-to-Real Olfactory Navigation Stack with Optional Vision Augmentation

arXiv:2602.19577v2 Announce Type: replace Abstract: Autonomous odor source localization remains a challenging problem for aerial robots due to turbulent airflow, sparse and delayed sensory signals, an

safetyarxiv-cs-ro

Compositional Steering of Large Language Models with Steering Tokens

arXiv:2601.05062v2 Announce Type: replace Abstract: Deploying LLMs in real-world applications requires controllable output that satisfies multiple desiderata at the same time. While existing work exte

applicationsarxiv-cs-cl

CSF: Black-box Fingerprinting via Compositional Semantics for Text-to-Image Models

arXiv:2604.16363v1 Announce Type: cross Abstract: Text-to-image models are commercially valuable assets often distributed under restrictive licenses, but such licenses are enforceable only when violat

researcharxiv-cs-cv

Domain-oriented RAG Assessment (DoRA): Synthetic Benchmarking for RAG-based Question Answering on Defense Documents

model-releasesarxiv-cs-cl

arXiv:2604.17943v1 Announce Type: new Abstract: Open-domain RAG benchmarks over public corpora can overestimate deployment performance due to pretraining overlap and weak attribution requirements. We

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty

arXiv:2506.12622v2 Announce Type: replace Abstract: Deep reinforcement learning (RL) has achieved remarkable success, yet its deployment in real-world scenarios is often limited by vulnerability to en

safetyarxiv-cs-lg

Dual-End Consistency Model

arXiv:2602.10764v2 Announce Type: replace Abstract: The slow iterative sampling nature remains a major bottleneck for the practical deployment of diffusion and flow-based generative models. While cons

researcharxiv-cs-cv

EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications

arXiv:2604.16783v1 Announce Type: new Abstract: Vehicle trajectory prediction is central to highway perception, but deployment on roadside edge devices necessitates bounded, deterministic end-to-end l

researcharxiv-cs-cv

Embedding Arithmetic: A Lightweight, Tuning-Free Framework for Post-hoc Bias Mitigation in Text-to-Image Models

arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli

EmbodiTTA: Resource-Efficient Test-Time Adaptation for Embodied Visual Systems

arXiv:2505.00986v2 Announce Type: replace-cross Abstract: Continual Test-time adaptation (CTTA) continuously adapts the deployed model on every incoming batch of data. While achieving optimal accuracy

applicationsarxiv-cs-cv

Tutorials

End-to-end lineage with DVC and Amazon SageMaker AI MLflow apps

In this post, we show how to combine DVC (Data Version Control), Amazon SageMaker AI, and Amazon SageMaker AI MLflow Apps to build end-to-end ML model lineage. We walk through two deployable patterns

tutorialsaws-ml-blog

End-to-End Optimization of LLM-Driven Multi-Agent Search Systems via Heterogeneous-Group-Based Reinforcement Learning

arXiv:2506.02718v2 Announce Type: replace Abstract: Large language models (LLMs) are versatile, yet their deployment in complex real-world settings is limited by static knowledge cutoffs and the diffi

safetyarxiv-cs-lg

Evolutionary Negative Module Pruning for Better LoRA Merging

arXiv:2604.17753v1 Announce Type: cross Abstract: Merging multiple Low-Rank Adaptation (LoRA) experts into a single backbone is a promising approach for efficient multi-task deployment. While existing

safetyarxiv-cs-cl

From Attribution to Abstention: Training-Free Attention-Based Auditing for Clinical Summarization

arXiv:2601.16397v2 Announce Type: replace Abstract: Deploying multimodal large language models (MLLMs) for clinical summarization demands not only fluent generation but also transparency about where e

researcharxiv-cs-cl

FUSE: Ensembling Verifiers with Zero Labeled Data

arXiv:2604.18547v1 Announce Type: cross Abstract: Verification of model outputs is rapidly emerging as a key primitive for both training and real-world deployment of large language models (LLMs). In p

applicationsarxiv-cs-cl

Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization

arXiv:2604.16496v1 Announce Type: cross Abstract: Continual learning, the ability to acquire new tasks sequentially without forgetting prior knowledge, is essential for deploying neural networks in dy

applicationsarxiv-cs-lg

I agree, and I will add to this. Companies should own their memories, skills and other resources agents need. Use Claude code, codex, copilo…

model-releasesharrison-chase--x

I agree, and I will add to this. Companies should own their memories, skills and other resources agents need. Use Claude code, codex, copilot, etc for intelligence but your execution layer should plug

I built a web analytics system to track traffic and events across all my @Replit projects in one place. Drop-in @posthog stack: → Full analy…

I built a web analytics system to track traffic and events across all my @Replit projects in one place. Drop-in @posthog stack: → Full analytics dashboard → Reverse proxy (beat ad blockers) → AI skill

applicationsreplit--x

Tutorials

I have done no promotion at all for our @LangChain for Beginners course and I just checked and it has 371 stars on GitHub🌟 Working on updat…

tutorialsharrison-chase--x

I have done no promotion at all for our @LangChain for Beginners course and I just checked and it has 371 stars on GitHub🌟 Working on updating some of our docs today and at some point will do a video

Identifying Ethical Biases in Action Recognition Models

arXiv:2604.17971v1 Announce Type: new Abstract: Human Action Recognition (HAR) models are increasingly deployed in high-stakes environments, yet their fairness across different human appearances has n

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Agents

Learning to Trade Like an Expert: Cognitive Fine-Tuning for Stable Financial Reasoning in Language Models

arXiv:2604.16862v1 Announce Type: new Abstract: Recent deployments of large language models (LLMs) as autonomous trading agents raise questions about whether financial decision-making competence gener

agentsarxiv-cs-lg

Learning Unanimously Acceptable Lotteries via Queries

arXiv:2604.17505v1 Announce Type: cross Abstract: Many high-stakes AI deployments proceed only if every stakeholder deems the system acceptable relative to their own minimum standard. With randomizati

researcharxiv-cs-lg

Lil: Less is Less When Applying Post-Training Sparse-Attention Algorithms in Long-Decode Stage

arXiv:2601.03043v3 Announce Type: replace Abstract: Large language models (LLMs) demonstrate strong capabilities across a wide range of complex tasks and are increasingly deployed at scale, placing si

researcharxiv-cs-cl

LoRaQ: Optimized Low Rank Approximation for 4-bit Quantization

arXiv:2604.18117v1 Announce Type: new Abstract: Post-training quantization (PTQ) is essential for deploying large diffusion transformers on resource-constrained hardware, but aggressive 4-bit quantiza

researcharxiv-cs-lg

Measuring Social Bias in Vision-Language Models with Face-Only Counterfactuals from Real Photos

model-releasesarxiv-cs-cl

arXiv:2601.06931v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly deployed in socially consequential settings, raising concerns about social bias driven by demog

Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs

arXiv:2603.02618v3 Announce Type: replace Abstract: Out-of-distribution (OOD) detection seeks to identify samples from unknown classes, a critical capability for deploying machine learning models in o

Local Ai

Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach

arXiv:2503.15845v2 Announce Type: replace Abstract: Network-wide Traffic State Estimation (TSE), which aims to infer a complete image of network traffic states with sparsely deployed sensors, plays a

local-aiarxiv-cs-lg