Search: “deployment”

arXiv:2605.13182v1 Announce Type: new Abstract: Diffusion-based models have shown strong performance in video super-resolution (VSR) and video frame interpolation (VFI). However, their role in the cou

tutorialsarxiv-cs-cv

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Digital Twins as Synthetic Controls in Single-Arm Trials

DGX agent

arXiv:2605.12832v1 Announce Type: cross Abstract: Single-arm trials are an important study design for evaluating drug efficacy and safety without enrolling patients into a control arm. Although they d

safetyarxiv-cs-lg

14 May 2026

DistractMIA: Black-Box Membership Inference on Vision-Language Models via Semantic Distraction

arXiv:2605.12574v1 Announce Type: cross Abstract: Vision-language models (VLMs) are trained on large-scale image-text corpora that may contain private, copyrighted, or otherwise sensitive data, motiva

Efficient Generative Prediction for EHR Foundation Models: The SCOPE and REACH Estimators

arXiv:2602.03730v2 Announce Type: replace-cross Abstract: Generative foundation models trained on tokenized electronic health record (EHR) timelines show promise for clinical outcome prediction via Mo

applicationsarxiv-cs-lg

EGSS: Entropy-guided Stepwise Scaling for Reliable Software Engineering

arXiv:2602.05242v1 Announce Type: cross Abstract: Agentic Test-Time Scaling (TTS) has delivered state-of-the-art (SOTA) performance on complex software engineering tasks such as code generation and bu

agentsarxiv-cs-lg

Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation

model-releasesarxiv-cs-cv

arXiv:2511.17031v2 Announce Type: replace-cross Abstract: The rapidly growing computational demands of diffusion models for image generation have raised significant concerns about energy consumption a

Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following

model-releasesarxiv-cs-ro

arXiv:2509.10796v4 Announce Type: replace Abstract: Robot person following (RPF) -- mobile robots that follow and assist a specific person -- has emerging applications in personal assistance, security

Freshworks unveils Freddy AI Agent Studio and MCP Gateway for Freshservice

Freshworks Inc. today unveiled an expanded set of agentic capabilities in its Freshservice information technology service management platform led by a new no-code Freddy AI Agent Studio that lets ente

agentssiliconangle

Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics

arXiv:2605.12728v1 Announce Type: cross Abstract: The power distribution engineering workforce faces a projected shortage of up to 1.5 million engineers by 2030, creating urgent demand for more access

Guide, Think, Act: Interactive Embodied Reasoning in Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2605.13632v1 Announce Type: cross Abstract: In this paper, we propose GTA-VLA(Guide, Think, Act), an interactive Vision-Language-Action (VLA) framework that enables spatially steerable embodied

HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation

arXiv:2605.13581v1 Announce Type: new Abstract: Hyperspectral image (HSI) restoration is crucial for reliable analysis, as real HSIs suffer from degradations like noise, blur, and resolution loss. How

Humanwashing -- It Should Leave You Feeling Dirty

arXiv:2605.13723v1 Announce Type: cross Abstract: The phrase 'human in the loop' is increasingly used to imply a sense of safety in relation to AI decision systems. It shouldn't. There are contexts wh

Inference-Time Machine Unlearning via Gated Activation Redirection

arXiv:2605.12765v1 Announce Type: new Abstract: Large Language Models memorize vast amounts of training data, raising concerns regarding privacy, copyright infringement, and safety. Machine unlearning

KVServe: Service-Aware KV Cache Compression for Communication-Efficient Disaggregated LLM Serving

arXiv:2605.13734v1 Announce Type: cross Abstract: LLMs are widely adopted in production, pushing inference systems to their limits. Disaggregated LLM serving (e.g., PD separation and KV state disaggre

applicationsarxiv-cs-ai

Language Model Networks: Supervision-Efficient Learning through Dense Communication

arXiv:2505.12741v2 Announce Type: replace Abstract: Language models are increasingly used not only as standalone predictors but also as components in larger inference systems, from test-time reasoning

applicationsarxiv-cs-ai

Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety

arXiv:2605.12729v1 Announce Type: cross Abstract: Large language models are increasingly being used to support network operations (NetOps) and artificial intelligence for IT operations (AIOps), includ

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs

arXiv:2605.12714v1 Announce Type: new Abstract: Hidden states change substantially across the layers of modern language models, but most layer-wise analyses focus on one aspect of that change. We prop

local-aiarxiv-cs-lg

LMU-Based Sequential Learning and Posterior Ensemble Fusion for Cross-Domain Infant Cry Classification

arXiv:2603.02245v3 Announce Type: replace-cross Abstract: Decoding infant cry causes remains challenging for healthcare monitoring due to short nonstationary signals, limited annotations, and strong d

local-aiarxiv-cs-lg

Local Inverse Geometry Can Be Amortized

arXiv:2605.13068v1 Announce Type: new Abstract: Nonlinear inverse problems often trade inexpensive but fragile first-order updates against curvature-aware methods such as Gauss-Newton and Levenberg-Ma

local-aiarxiv-cs-lg

Multi-Dimensional Behavioral Evaluation of Agentic Stock Prediction Systems Using Large Language Model Judges with Closed-Loop Reinforcement Learning Feedback

arXiv:2605.05739v2 Announce Type: replace-cross Abstract: Forecast evaluation in finance has relied on aggregate accuracy metrics and predictive-accuracy tests built on point-forecast errors. These in

agentsarxiv-cs-ai

Multistep Belief Space Dynamics Learning For Risk-Aware Control

arXiv:2605.12628v1 Announce Type: new Abstract: As autonomous vehicles move from a simplified research setting to practical use, there exists a large gap between the dynamic behavior of a human drivin

agentsarxiv-cs-ro

Tutorials

New course: Transformers in Practice. You'll get a practical view of how transformer-based LLMs work, so you can reason about their behavior…

New course: Transformers in Practice. You'll get a practical view of how transformer-based LLMs work, so you can reason about their behavior, diagnose problems like slow inference, and make smarter de

tutorialsandrew-ng--x

No Attack Required: Semantic Fuzzing for Specification Violations in Agent Skills

arXiv:2605.13044v1 Announce Type: cross Abstract: LLM-powered agents can silently delete documents, leak credentials, or transfer funds on a routine user request, not because the agent was attacked, b

Research

Object Manipulation of the Variable Topology Truss system

arXiv:2605.13086v1 Announce Type: new Abstract: This paper presents an object manipulation strategy for the Variable Topology Truss (VTT) system, a truss robot that comprises actuated truss members co

researcharxiv-cs-ro

On the Sample Complexity of Differentially Private Policy Optimization

arXiv:2510.21060v3 Announce Type: replace-cross Abstract: Policy optimization (PO) is a cornerstone of modern reinforcement learning (RL), with diverse applications spanning robotics, healthcare, and

OpenAaaS: An Open Agent-as-a-Service Framework for Distributed Materials-Informatics Research

arXiv:2605.13618v1 Announce Type: cross Abstract: The Materials Genome Initiative catalyzed the proliferation of centralized platforms--SaaS, PaaS, and IaaS--that aggregate computational and experimen

agentsarxiv-cs-ai

PRA-PoE: Robust Alzheimer's Diagnosis with Arbitrary Missing Modalities

arXiv:2605.13081v1 Announce Type: new Abstract: Missing modalities are prevalent in real-world Alzheimer's disease (AD) assessment and pose a significant challenge to multimodal learning, particularly

R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow

arXiv:2605.13838v1 Announce Type: new Abstract: Video-guided 3D animation holds immense potential for content creation, offering intuitive and precise control over dynamic assets. However, practical d

RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records

arXiv:2507.15867v2 Announce Type: replace-cross Abstract: Rare diseases affect 1 in 10 Americans yet remain systematically underdocumented in clinical records. ICD-based systems cannot capture their b

agentsarxiv-cs-ai

Reframing preprocessing selection as model-internal calibration in near-infrared spectroscopy: A large-scale benchmark of operator-adaptive PLS and Ridge models

arXiv:2605.13587v1 Announce Type: cross Abstract: Near-infrared spectroscopy (NIRS) is rapid and non-destructive, but reliable calibration still depends heavily on spectral preprocessing. In routine p

Revisiting DAgger in the Era of LLM-Agents

arXiv:2605.12913v1 Announce Type: new Abstract: Long-horizon LM agents learn from multi-turn interaction, where a single early mistake can alter the subsequent state distribution and derail the whole

safetyarxiv-cs-lg

Scale-Gest: Scalable Model-Space Synthesis and Runtime Selection for On-Device Gesture Detection

arXiv:2605.12506v1 Announce Type: cross Abstract: Realizing on-device ML-based gesture detection under tight real-time performance, energy and memory constraints is challenging, especially when consid

local-aiarxiv-cs-ai

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs

arXiv:2510.18245v3 Announce Type: replace-cross Abstract: Scaling the number of parameters and the size of training data has proven to be an effective strategy for improving large language model (LLM)

SHM-Agents: A Generalist-Specialist Integrated Agent System for Structural Health Monitoring

arXiv:2605.12916v1 Announce Type: cross Abstract: Artificial intelligence is increasingly used to simplify complex tasks. In engineering applications of structural health monitoring (SHM), existing sp

agentsarxiv-cs-lg

SpectralTrain: A Universal Framework for Hyperspectral Image Classification

arXiv:2511.16084v2 Announce Type: replace-cross Abstract: Hyperspectral image (HSI) classification typically involves large-scale data and computationally intensive training, which limits the practica

Still Camouflage, Moving Illusion: View-Induced Trajectory Manipulation in Autonomous Driving

arXiv:2605.12743v1 Announce Type: cross Abstract: Existing physical adversarial attacks on vision-based autonomous driving induce time-evolving perception errors, including biased object tracking or t

agentsarxiv-cs-cv

TeleGate: Whole-Body Humanoid Teleoperation via Gated Expert Selection with Motion Prior

arXiv:2602.09628v2 Announce Type: replace Abstract: Real-time whole-body teleoperation is a critical method for humanoid robots to perform complex tasks in unstructured environments. However, developi

safetyarxiv-cs-ro

TouchAnything: A Dataset and Framework for Bimanual Tactile Estimation from Egocentric Video

model-releasesarxiv-cs-ro

arXiv:2605.13083v1 Announce Type: new Abstract: Egocentric human video data, which captures rich human-environment interactions and can be collected at scale, has become a key driver of embodied intel

Research

TurboGR: An Accelerated Training System for Large-Scale Generative Recommendation

arXiv:2605.13433v1 Announce Type: cross Abstract: Generative recommendation (GR) has emerged as a promising paradigm that replaces fragmented, scenario-specific architectures with unified Transformer-

researcharxiv-cs-lg

Uncertainty-Aware 3D Position Refinement for Multi-UAV Systems

arXiv:2605.13500v1 Announce Type: new Abstract: Reliable real-time 3D localization is essential for multi-UAV navigation, collision avoidance, and coordinated flight, yet onboard estimates can degrade

agentsarxiv-cs-ro

Tools

Unlocking asynchronicity in continuous batching

This article explains how asynchronous processing can be integrated with continuous batching techniques to improve inference efficiency in machine learning models. Continuous batching allows requests

toolshugging-face

VectorSmuggle: Steganographic Exfiltration in Embedding Stores and a Cryptographic Provenance Defense

arXiv:2605.13764v1 Announce Type: cross Abstract: Modern retrieval-augmented generation (RAG) systems convert sensitive content into high-dimensional embeddings and store them in vector databases that

What’s the best model to use with RAG to create a locally hosted survival and off grid LLm?

This discussion explores which language models work best when combined with RAG (Retrieval-Augmented Generation) for building a locally hosted LLM focused on survival and off-grid living topics. The t

local-air-ollama

When Backdoors Meet Partial Observability: Attacking Real-World Reinforcement Learning

arXiv:2601.14104v2 Announce Type: replace-cross Abstract: Backdoor attacks can cause reinforcement learning (RL) policies to behave normally under clean inputs while executing malicious behaviors when

1/5 We’re seeing 4 common agent optimization methods for hitting the right accuracy-cost or accuracy-latency tradeoff. We tried them all out…

AI21 Labs discusses four common agent optimization methods used to balance accuracy against cost and latency constraints. The post indicates the team evaluated all four approaches, likely covering tec

agentsai21-labs--x

BEExformer: A Fast Inferencing Binarized Transformer with Early Exits

model-releasesarxiv-cs-cl

arXiv:2412.05225v3 Announce Type: replace Abstract: Large Language Models (LLMs) based on transformers achieve cutting-edge results on a variety of applications. However, their enormous size and proce

Beyond Parameter Aggregation: Semantic Consensus for Federated Fine-Tuning of LLMs

arXiv:2605.11857v1 Announce Type: new Abstract: Federated fine-tuning of large language models is commonly formulated as a parameter aggregation problem. However, even parameter-efficient methods requ

Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs

arXiv:2605.11107v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP and SigLIP 2, are widely used for image classification, yet their vision encoders remain vulnerable to syste

applicationsarxiv-cs-cv