Search: “deployment”

Uncertainty Quantification in Detection Transformers: Object-Level Calibration and Image-Level Reliability

arXiv:2412.01782v4 Announce Type: replace-cross Abstract: DETR and its variants have emerged as promising architectures for object detection, offering an end-to-end prediction pipeline. In practice, h

local-aiarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling

DGX agent

arXiv:2604.19734v1 Announce Type: cross Abstract: Scaling humanoid foundation models is bottlenecked by the scarcity of robotic data. While massive egocentric human data offers a scalable alternative,

model-releasesarxiv-cs-ai

22 Apr 2026

VCE: A zero-cost hallucination mitigation method of LVLMs via visual contrastive editing

arXiv:2604.19412v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) frequently suffer from Object Hallucination (OH), wherein they generate descriptions containing objects that are

VDPP: Video Depth Post-Processing for Speed and Scalability

arXiv:2604.06665v2 Announce Type: replace Abstract: Video depth estimation is essential for providing 3D scene structure in applications ranging from autonomous driving to mixed reality. Current end-t

VISTA: Verification In Sequential Turn-based Assessment

arXiv:2510.27052v5 Announce Type: replace Abstract: Hallucination--defined here as generating statements unsupported or contradicted by available evidence or conversational context--remains a major ob

researcharxiv-cs-cl

Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs

arXiv:2508.00161v3 Announce Type: replace-cross Abstract: The releases of powerful open-weight large language models (LLMs) are often not accompanied by access to their full training data. Existing in

What’s new with the Cross-Cloud Network at Next ‘26

model-releasesgoogle-cloud-ai

While generative AI sparked a revolution, the true paradigm shift is the rapid evolution from standalone AI models to multi-agent autonomous systems. In this new era, the network transcends basic conn

A Real-Time Bike-Pedestrian Safety System with Wide-Angle Perception and Evaluation Testbed for Urban Intersections

arXiv:2604.17046v1 Announce Type: new Abstract: Collisions between cyclists and pedestrians at urban intersections remain a persistent source of injuries, yet few systems attempt real-time warnings to

safetyarxiv-cs-cv

Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration

arXiv:2508.18025v4 Announce Type: replace-cross Abstract: Autonomous planetary exploration demands real-time, high-fidelity environmental perception. Standard deep learning models require massive comp

agentsarxiv-cs-cv

AeroRAG: Structured Multimodal Retrieval-Augmented LLM for Fine-Grained Aerial Visual Reasoning

arXiv:2604.17889v1 Announce Type: new Abstract: Despite recent progress in multimodal large language models (MLLMs), reliable visual question answering in aerial scenes remains challenging. In such sc

Industry

Announcing our 2026 Google Cloud Partners of the Year

Google Cloud is honored to present the 2026 Partner of the Year winners! These awards recognize partners who have displayed a commitment to excellence by leveraging Google Cloud technology to deliver

industrygoogle-cloud-ai

Anthropic gets $5B investment from Amazon, will use it to buy Amazon chips

model-releasesars-technica

Amazon announced a 5 billion investment in Anthropic, with up to 20 billion more tied to commercial milestones. Anthropic committed to spending over $100 billion on AWS technologies over the next deca

Anyone here using ai agent orchestration software to control multiple hermes agents? I'm retired and have some extra hardware

This Reddit post from r/ollama asks the community about AI agent orchestration software for managing multiple Hermes agents, posted by a retired individual with available hardware resources. The post

agentsr-ollama

Asset Harvester: Extracting 3D Assets from Autonomous Driving Logs for Simulation

arXiv:2604.18468v1 Announce Type: new Abstract: Closed-loop simulation is a core component of autonomous vehicle (AV) development, enabling scalable testing, training, and safety validation before rea

safetyarxiv-cs-cv

Attention-ResUNet for Automated Fetal Head Segmentation

arXiv:2604.18148v1 Announce Type: new Abstract: Automated fetal head segmentation in ultrasound images is critical for accurate biometric measurements in prenatal care. While existing deep learning ap

Autonomous Unmanned Aircraft Systems for Enhanced Search and Rescue of Drowning Swimmers: Image-Based Localization and Mission Simulation

arXiv:2604.18088v1 Announce Type: new Abstract: Drowning is an omnipresent risk associated with any activity on or in the water, and rescuing a drowning person is particularly challenging because of t

agentsarxiv-cs-cv

Balanced Co-Clustering of Users and Items for Embedding Table Compression in Recommender Systems

arXiv:2604.18351v1 Announce Type: cross Abstract: Recommender systems have advanced markedly over the past decade by transforming each user/item into a dense embedding vector with deep learning models

Benchmarking programs?

The Reddit post 'Benchmarking programs?' in r/ollama likely discusses tools and methods for measuring the performance of local language models running on Ollama. Available benchmarking tools for Ollam

local-air-ollama

Benchmarking System Dynamics AI Assistants: Cloud Versus Local LLMs on CLD Extraction and Discussion

arXiv:2604.18566v1 Announce Type: cross Abstract: We present a systematic evaluation of large language model families -- spanning both proprietary cloud APIs and locally-hosted open-source models -- o

Tutorials

Beyond Attack Success Rate: A Multi-Metric Evaluation of Adversarial Transferability in Medical Imaging Models

arXiv:2604.16532v1 Announce Type: new Abstract: While deep learning systems are becoming increasingly prevalent in medical image analysis, their vulnerabilities to adversarial perturbations raise seri

tutorialsarxiv-cs-cv

Bridging the Ex-Vivo to In-Vivo Gap: Synthetic Priors for Monocular Depth Estimation in Specular Surgical Environments

arXiv:2512.23786v2 Announce Type: replace Abstract: Accurate Monocular Depth Estimation (MDE) is critical for autonomous robotic surgery. However, existing self-supervised methods often exhibit a seve

agentsarxiv-cs-cv

CAPO: Counterfactual Credit Assignment in Sequential Cooperative Teams

arXiv:2604.17693v1 Announce Type: new Abstract: In cooperative teams where agents act in a fixed order and share a single team reward, it is hard to know how much each agent contributed, and harder st

safetyarxiv-cs-lg

Channel Attention-Guided Cross-Modal Knowledge Distillation for Referring Image Segmentation

arXiv:2604.16806v1 Announce Type: new Abstract: Referring image segmentation (RIS) requires accurate segmentation of target regions in images according to language descriptions, which is a cross-modal

CLASP: Training-Free LLM-Assisted Source Code Watermarking via Semantic-Preserving Transformations

arXiv:2510.11251v2 Announce Type: replace-cross Abstract: The proliferation of open-source code and large language models (LLMs) for code generation has amplified the risks of unauthorized reuse and i

local-aiarxiv-cs-lg

CoLLM: A Unified Framework for Co-execution of LLMs Federated Fine-tuning and Inference

arXiv:2604.16400v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly adopted in edge intelligence to power domain-specific applications and personalized services, the qua

Composed Vision-Language Retrieval for Skin Cancer Case Search via Joint Alignment of Global and Local Representations

arXiv:2603.09108v2 Announce Type: replace Abstract: Medical image retrieval aims to identify clinically relevant lesion cases to support diagnostic decision making, education, and quality control. In

safetyarxiv-cs-cv

Contact-Rich Robotic Assembly in Construction via Diffusion Policy Learning

arXiv:2511.17774v3 Announce Type: replace Abstract: Fabrication uncertainty arising from tolerance accumulation, material imperfection, and positioning errors remains a critical barrier to automated r

safetyarxiv-cs-ro

CWT-Enhanced Vibration Sensing With Spatial Fault Localization Using YOLO

arXiv:2509.03070v4 Announce Type: replace-cross Abstract: This letter presents a CWT-enhanced vibration sensing framework for bearing fault monitoring through spatial localization on time-frequency sp

Applications

Deep Hierarchical Knowledge Loss for Fault Intensity Diagnosis

arXiv:2604.16459v1 Announce Type: cross Abstract: Fault intensity diagnosis (FID) plays a pivotal role in intelligent manufacturing while neglecting dependencies among target classes hinders its pract

applicationsarxiv-cs-cv

Depth Registers Unlock W4A4 on SwiGLU: A Reader/Generator Decomposition

arXiv:2604.18128v1 Announce Type: new Abstract: We study post-training W4A4 quantization in a controlled 300M-parameter SwiGLU decoder-only language model trained on 5B tokens of FineWeb-Edu, and ask

Diagnosing LLM-based Rerankers in Cold-Start Recommender Systems: Coverage, Exposure and Practical Mitigations

arXiv:2604.16318v1 Announce Type: cross Abstract: Large language models (LLMs) and cross-encoder rerankers have gained attention for improving recommender systems, particularly in cold-start scenarios

safetyarxiv-cs-cl

DifFoundMAD: Foundation Models meet Differential Morphing Attack Detection

arXiv:2604.17961v1 Announce Type: new Abstract: In this work, we introduce DifFoundMAD, a parameter-efficient D-MAD framework that exploits the generalisation capabilities of vision foundation models

Disentangled Robot Learning via Separate Forward and Inverse Dynamics Pretraining

arXiv:2604.16391v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have shown great potential in building generalist robots, but still face a dilemma-misalignment of 2D image foreca

DocQAC: Adaptive Trie-Guided Decoding for Effective In-Document Query Auto-Completion

arXiv:2604.18257v1 Announce Type: cross Abstract: Query auto-completion (QAC) has been widely studied in the context of web search, yet remains underexplored for in-document search, which we term DocQ

Does 'Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients?

arXiv:2604.18161v1 Announce Type: new Abstract: In policy gradient reinforcement learning, access to a differentiable model enables 1st-order gradient estimation that accelerates learning compared to

safetyarxiv-cs-lg

DriveAgent-R1: Advancing VLM-based Autonomous Driving with Active Perception and Hybrid Thinking

arXiv:2507.20879v3 Announce Type: replace Abstract: The advent of Vision-Language Models (VLMs) has significantly advanced end-to-end autonomous driving, demonstrating powerful reasoning abilities for

Dynamic Risk Assessment by Bayesian Attack Graphs and Process Mining

arXiv:2604.18080v1 Announce Type: cross Abstract: While attack graphs are useful for identifying major cybersecurity threats affecting a system, they do not provide operational support for determining

researcharxiv-cs-lg

EmbodiedLGR: Integrating Lightweight Graph Representation and Retrieval for Semantic-Spatial Memory in Robotic Agents

model-releasesarxiv-cs-ro

arXiv:2604.18271v1 Announce Type: new Abstract: As the world of agentic artificial intelligence applied to robotics evolves, the need for agents capable of building and retrieving memories and observa

Evaluating Multimodal LLMs for Inpatient Diagnosis: Real-World Performance, Safety, and Cost Across Ten Frontier Models

arXiv:2604.16980v1 Announce Type: new Abstract: Background: Large language models (LLMs) are increasingly proposed for diagnostic support, but few evaluations use real-world multimodal inpatient data,

Expressing Social Emotions: Misalignment Between LLMs and Human Cultural Emotion Norms

arXiv:2604.16757v1 Announce Type: new Abstract: The expression of emotions that serve social purposes, such as asserting independence or fostering interdependence, is central to human interactions and

researcharxiv-cs-cl

Expressive yet Efficient Feature Expansion with Adaptive Cross-Hadamard Products

arXiv:2505.22226v2 Announce Type: replace Abstract: Recent theoretical advances reveal that the Hadamard product induces nonlinear representations and implicit high-dimensional mappings for the field

FrameVGGT: Geometry-Aligned Frame-Level Memory for Bounded Streaming VGGT

arXiv:2603.07690v2 Announce Type: replace Abstract: Streaming Visual Geometry Transformers such as StreamVGGT enable strong online 3D perception, but their KV-cache grows unbounded over long streams,

Fringe Projection Based Vision Pipeline for Autonomous Hard Drive Disassembly

arXiv:2604.17231v1 Announce Type: new Abstract: Unrecovered e-waste represents a significant economic loss. Hard disk drives (HDDs) comprise a valuable e-waste stream necessitating robotic disassembly

local-aiarxiv-cs-cv

From User Recognition to Activity Counting: An Identity-Agnostic Approach to Multi-User WiFi Sensing

arXiv:2604.16572v1 Announce Type: new Abstract: Wi-Fi Channel State Information (CSI) enables device-free human activity recognition, but existing multi-user approaches assume a fixed set of known use

researcharxiv-cs-lg

G-PARC: Graph-Physics Aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics on Unstructured Meshes

arXiv:2604.16533v1 Announce Type: new Abstract: Physics-aware recurrent convolutional networks (PARC) have demonstrated strong performance in predicting nonlinear spatiotemporal dynamics by embedding

researcharxiv-cs-lg

GEAR up to get the most out of AI learning at Google Cloud Next ‘26

Our new GEAR program, powered by Google Skills, equips every professional with the hands-on AI training needed to build and launch enterprise-ready agents at scale. Anyone can join GEAR for access to

agentsgoogle-cloud-ai

Geometric Stability: The Missing Axis of Representations

arXiv:2601.09173v4 Announce Type: replace-cross Abstract: Representational similarity analysis and related methods have become standard tools for comparing the internal geometries of neural networks a

safetyarxiv-cs-cl

Greedy Kalman-Swarm: Improving State Estimation in Robot Swarms in Harsh Environments

arXiv:2604.16868v1 Announce Type: new Abstract: State estimation is a fundamental requirement in robotics, where the accurate determination of a robot's state is essential for stable operation despite

agentsarxiv-cs-ro