Search: “deployment”

arXiv:2404.07124v2 Announce Type: replace-cross Abstract: This paper presents a pipeline designed to bring ultrasound (US) plane pose estimation closer to clinical use, demonstrating the feasibility o

hardwarearxiv-cs-ai

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Methane Detection On Board Satellites from Unorthorectified Imagery

DGX agent

arXiv:2609.04906v1 Announce Type: cross Abstract: As a potent greenhouse gas, methane is a major driver of climate change. Its effective mitigation relies on timely detection. Conventional detection m

researcharxiv-cs-ai

7 Sept 2026

Multi-scale Image Representation Compression

model-releasesarxiv-cs-cv

arXiv:2609.04274v1 Announce Type: cross Abstract: Overfitted codecs have demonstrated promising performance for image and video compression. In particular, for image compression, the Cool-chic family

Open-Set 3D Scene Graphs for Field Robotics: An Outdoor Case Study

arXiv:2609.04607v1 Announce Type: new Abstract: Three-dimensional scene graphs (3DSGs) have emerged as a promising approach for building geometrically grounded, semantically informed, hierarchical gen

applicationsarxiv-cs-ro

Pack It My Way: Triadic Human-Robot Collaboration for Personalized Autonomous Packing

arXiv:2609.04620v1 Announce Type: new Abstract: Personalized autonomous packing requires robots to account for resident preferences that cannot be inferred from scene geometry alone. Expert teleoperat

agentsarxiv-cs-ro

Persistent Robot World Models: Stabilizing Multi-Step Rollouts via Reinforcement Learning

arXiv:2603.25685v2 Announce Type: replace-cross Abstract: Action-conditioned robot world models generate future video frames of the manipulated scene given a robot action sequence, offering a promisin

researcharxiv-cs-cv

Local Ai

Privacy Failure in Split-LLM Training, The Returned Gradient Nullifies the Decoys

arXiv:2609.04382v1 Announce Type: cross Abstract: We present a systems-security case study of a two-node split-LLM training system whose privacy evaluation passed while leaving an observable channel u

local-aiarxiv-cs-lg

Proton Irradiation Characterization of an Open-Source ML Accelerator on a Zynq UltraScale+ MPSoC

arXiv:2609.05249v1 Announce Type: cross Abstract: As spaceborne computing systems increasingly rely on neural network (NN) accelerators, the opacity of commercial, black-box architectures severely res

researcharxiv-cs-lg

Qlippy: A Retrieval-Augmented GenAI Assistant for Reproducible Quantum Workflows and Experiment Tracking

arXiv:2609.05039v1 Announce Type: cross Abstract: Quantum software development is iterative and error-prone. Noisy hardware and repeated re-execution make experiment tracking, provenance, and reproduc

researcharxiv-cs-ai

Tools

Quoting Jakub Pachocki

The strongest argument I see for continuing to train much smarter models quickly is the need to build defensive systems against the dangers posed by other AI. [...] We will need powerful, aligned AI f

toolssimon-willison

Really strong benchmark paper on coding agents. Claude Opus 5 running under Claude Code passes 23.9% of the evaluations. An expert human ref…

Really strong benchmark paper on coding agents. Claude Opus 5 running under Claude Code passes 23.9% of the evaluations. An expert human reference scores 82.2%. Here is what the task actually is. The

model-releasesdair-ai--x

Reasoning Without Inference Cost: Latent Semantic Scaffolding for Robot VLA Policies

arXiv:2609.04893v1 Announce Type: new Abstract: Vision-language-action (VLA) models are trained by imitation and capture what action to take but not why; adding causal reasoning improves manipulation,

safetyarxiv-cs-ro

RegionFed: Federated Learning for Personalized Query Understanding in Heterogeneous Retail Environments

arXiv:2609.05403v1 Announce Type: cross Abstract: Retail search systems serve diverse geographic regions with distinct query patterns, vocabularies, and product preferences, creating significant data

Repeat-After-Me: Black-Box Adaptive Visual Prompt Injection

arXiv:2609.04533v1 Announce Type: cross Abstract: Prompt injection is widely recognized as a major security threat to AI agents that interact with untrusted external data, such as websites, documents,

SoK: AI-Augmented Binary Reversing

arXiv:2606.17398v2 Announce Type: replace-cross Abstract: Binary reversing is fundamental to software understanding, vulnerability discovery, malware investigation, and firmware auditing. However, it

agentsarxiv-cs-ai

Super interesting paper on proactive agents from Google DeepMind. (bookmark it) Proactive assistance usually means autocomplete. Researchers…

Super interesting paper on proactive agents from Google DeepMind. (bookmark it) Proactive assistance usually means autocomplete. Researchers asks what it looks like when an agent offers higher-level c

agentsdair-ai--x

Test-Time Adaptation via Cache Personalization for Facial Expression Recognition in Videos

model-releasesarxiv-cs-cv

arXiv:2603.21309v4 Announce Type: replace Abstract: Facial expression recognition (FER) in videos requires model personalization to capture considerable variation across subjects. Vision-language mode

Hardware

Tuning Collective Patterns to Alleviate Congestion in Shared AI Clusters

arXiv:2609.04417v1 Announce Type: cross Abstract: Distributed AI training involves recurring rounds of data exchange between multiple pairs of GPU nodes. Slowdown in even one flow due to congestion ca

hardwarearxiv-cs-lg

Local Ai

Uncensored Open-weight Models: Redistribution as the Persistence Layer

arXiv:2609.05241v1 Announce Type: new Abstract: A rapidly expanding ecosystem of actors is removing built-in safety guardrails from open-weight AI models. We profile this ecosystem by identifying key

local-aiarxiv-cs-ai

Wireless Foundation Models: State-of-the-Art and Open Challenges

arXiv:2609.04707v1 Announce Type: cross Abstract: Wireless foundation models (WFMs) have emerged as a promising approach for learning reusable representations from large-scale wireless data and adapti

applicationsarxiv-cs-ai

Been posting individual pieces of RunAnywhere for months. Here's the whole thing in one place. RunAnywhere SDKs is a complete inference suit…

model-releasesyohei-nakajima--x

Been posting individual pieces of RunAnywhere for months. Here's the whole thing in one place. RunAnywhere SDKs is a complete inference suite for any dev who wants to run AI on the user's device. ->8

I read some strange criticisms of this post. So here is my take. I’m not fully endorsing the piece by Newport, but there’s quite some factua…

I read some strange criticisms of this post. So here is my take. I’m not fully endorsing the piece by Newport, but there’s quite some factually true information in it. Responsible and careful people (

safetygary-marcus--x

[Model] Support for Spark2_5ForCausalLM implementation by KnightYao · Pull Request #27868 · ggml-org/llama.cpp

model-releasesr-localllama

https://huggingface.co/XHToken/Spark-X2.5-4B-GGUF https://huggingface.co/XHToken/Spark-X2.5-1.7B-GGUF from XHToken: We are introducing Spark-X2.5-4B and Spark-X2.5-1.7B, two compact, general-purpose l

Validate your local LLM advertised KV cache against real pressure; see exactly how old contexts get evicted from cache

model-releasesr-localllama

Hello, I'm a bit obsessed with cache management on local LLMs. For the last few days I've been working on cache management on vLLM with my 2x DGX Spark and DeepSeek v4 Flash 0731. I felt something was

Astra vs. Fable 5.1 on real ML tasks -- tradeoffs, strengths, shortcomings [P]

model-releasesr-machinelearning

I ran a side-by-side ML text-processing and model-training workflow using Fable 5.1 vs. Astra (both on xhigh), and the results could not have been more different. Warning, long post. TL;DR -- Astra co

5 Sept 2026

How we think about the “wiki incident,” where our agents wrote to several internet sites: it’s past time for us to define standards for when…

How we think about the “wiki incident,” where our agents wrote to several internet sites: it’s past time for us to define standards for when and how we share misalignment incidents, not just misalignm

model-releasesopenai--x

5 Sept 2026

A comparative study on the accuracy & repeatability of mobile robotic platforms for the delivery of precision NDE measurement

arXiv:2609.03794v1 Announce Type: new Abstract: Mobile robotic platforms offer a flexible alternative to fixed manipulators for non-destructive evaluation (NDE) of large aerospace structures, but thei

safetyarxiv-cs-ro

A Computationally Feasible Framework for Causal Probabilistic Explanation

arXiv:2609.04177v1 Announce Type: new Abstract: Explaining why a specific outcome occurred, and which inputs deserve the blame or credit, is central to philosophical, scientific, and policy analysis.

safetyarxiv-cs-ai

A Multi-Vine Soft Robot Enabling Accessible Working Channel and Steering

arXiv:2609.03758v1 Announce Type: new Abstract: Soft eversion robots, also known as vine robots, have attracted growing interest for navigation and inspection tasks, including minimally invasive medic

researcharxiv-cs-ro

A Reverse Sign Language Dictionary: Open-Vocabulary Sign Recognition from Continuous Signing via Video Captioning and Description Retrieval

arXiv:2609.03788v1 Announce Type: cross Abstract: Isolated Sign Language Recognition (ISLR) is conventionally cast as closed-set classification over gloss labels, which cannot generalize to signs unse

researcharxiv-cs-cl

Adaptive Resolving Methods for Markov Decision Processes with Function Approximations

arXiv:2505.12037v2 Announce Type: replace Abstract: Learning the optimal policy for Markov decision process problems (MDPs) from samples is a fundamental problem in online and data-driven decision-mak

safetyarxiv-cs-lg

An Adversarial Zero-Shot Learning Approach for Anomaly Detection in Multivariate IoT Traffic Data

arXiv:2609.03505v1 Announce Type: new Abstract: Anomaly detection in Internet of Things (IoT) networks presents unique challenges due to the diversity of devices, lack of labeled data, and domain vari

applicationsarxiv-cs-lg

CASCADE: A Component Ablation and Corpus Audit of a Layered Local Defense for MCP-Based Systems

arXiv:2604.17125v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) widens the prompt injection attack surface of large language model applications to tool descriptions, paramet

Compile by Training: Turning Natural-Language Specifications into Local Neural Functions

arXiv:2609.04199v1 Announce Type: cross Abstract: Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduce

applicationsarxiv-cs-ai

Designing lifecycle policies for AgentCore memory

Long-running AI agents accumulate outdated memories that degrade quality and create compliance risk. Learn how to design memory lifecycle policies for Amazon Bedrock AgentCore: scoring, consolidating,

agentsaws-ml-blog

Distilled Rapid Embedding Transfer (DRET): Parameter-Efficient Biomedical Domain Adaptation via Priority-Based Embedding Transfer

model-releasesarxiv-cs-cl

arXiv:2609.02898v1 Announce Type: new Abstract: Large domain-specific language models such as BioBERT and ClinicalBERT achieve strong performance on biomedical NLP tasks, but their computational deman

DropClick: Semi-Automated One-Click Segmentation for Agricultural Robotic Data

arXiv:2609.03680v1 Announce Type: new Abstract: Labelling vision datasets, especially for segmentation tasks, is a laborious and costly process that stymies novel developments in agricultural robotics

researcharxiv-cs-cv

Local Ai

DSAQuant: Denoising-Stage-Aligned Quantization-Aware Training for Video Generation

arXiv:2609.04031v1 Announce Type: new Abstract: Video diffusion models (VDMs) have achieved impressive progress in text-to-video generation, but their high memory and computational costs hinder practi

local-aiarxiv-cs-cv

DuplexSpeechBench-IFEval: Evaluating Implicit Instruction Following in Full-Duplex Voice Agents

arXiv:2609.03423v1 Announce Type: new Abstract: Full-duplex voice agents must continuously decide when to listen, backchannel, interrupt, handle speech overlaps, take the floor, and yield. Existing be

safetyarxiv-cs-ai

Federated Causal Discovery via Regression-Directed Cumulants

arXiv:2609.03705v1 Announce Type: new Abstract: In this paper we study linear non-Gaussian acyclic models (LiNGAM) when used in federated environments. These causal models allow one to go beyond Marko

researcharxiv-cs-lg

FedPS: Federated Preprocessing for structured data via aggregated Statistics

arXiv:2602.10870v2 Announce Type: replace-cross Abstract: Federated Learning (FL) enables multiple parties to collaboratively train machine learning models without sharing raw data. However, before tr

researcharxiv-cs-ai

Learnable composition for neural operators

arXiv:2609.03069v1 Announce Type: new Abstract: Neural operators are fast, differentiable surrogates for physical simulation, but their accuracy often degrades when domain geometry, size, or operating

researcharxiv-cs-lg

Learning What Not to Forget: Long-Horizon Agent Memory from a Few Kilobytes of Learning

arXiv:2606.20954v2 Announce Type: replace-cross Abstract: Long-running language-model systems accumulate interaction history that outgrows the context window, so they must continually evict. When an e

Long-Horizon Consistent and Interaction-Aware World Models for Multi-Style End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2609.03225v1 Announce Type: new Abstract: End-to-end autonomous driving has increasingly adopted world model-based reinforcement learning frameworks to improve learning efficiency through extit{

LRConv-NeRV: Low Rank Convolution for Efficient Neural Video Compression

arXiv:2603.18261v2 Announce Type: replace-cross Abstract: Neural Representations for Videos (NeRV) encode entire video sequences within neural network parameters, offering an alternative paradigm to c

MasterControl Seventeen Every Time

arXiv:2609.03209v1 Announce Type: new Abstract: We study a governed approach to enterprise analytics: a language model interprets the question, while deterministic policy selects and runs a pre-approv

safetyarxiv-cs-ai

MINERVA: How Small Can a Manipulation Policy Be and Still Solve LIBERO?

model-releasesarxiv-cs-ro

arXiv:2609.03715v1 Announce Type: new Abstract: Vision-language-action (VLA) models with billions of parameters now dominate the LIBERO manipulation benchmark, but the model capacity actually required

Hardware

Nvidia becomes a leading global strategic tech backer, with the value of its equity investments up 10x in the past year to $99B, as it bolsters the AI sector (Kai Nicol-Schwarz/CNBC)

Kai Nicol-Schwarz / CNBC: Nvidia becomes a leading global strategic tech backer, with the value of its equity investments up 10x in the past year to $99B, as it bolsters the AI sector — Nvidia has bec

hardwaretechmeme