Search: “automated”

arXiv:2605.31093v1 Announce Type: new Abstract: Breast cancer is a major global health concern, and mammography screening plays a central role in early detection. The large volume of screening examina

arXiv:2605.30802v1 Announce Type: cross Abstract: Prediction markets aggregate collective intelligence to forecast uncertain events, but their utility depends on reliable outcome resolution. Existing

arXiv:2602.01173v3 Announce Type: replace Abstract: Understanding the multi-dimensional attributes and intensity nuances of image-evoked emotions is pivotal for advancing machine empathy and empowerin

arXiv:2605.31487v1 Announce Type: new Abstract: Deploying computer vision models in Warehouse Facilities traditionally requires extensive resources for camera mounting, image collection, annotation, t

arXiv:2605.30521v1 Announce Type: new Abstract: Large language models must frequently process untrusted inputs, such as judging an answer from another model or running tasks like spam and harm classif

arXiv:2503.14190v3 Announce Type: replace Abstract: A common goal in analyzing time series data is to understand how events cause observed variations. We study whether Large Language Models (LLMs) can

arXiv:2412.18134v4 Announce Type: replace Abstract: Randomized self-reductions (RSRs) express f(x) using f evaluated at random correlated points, enabling self-correcting programs, instance-hiding pro

arXiv:2605.30829v1 Announce Type: new Abstract: Lower extremity computed tomography (CT) contains clinically relevant information for body composition analysis, sarcopenia assessment, and musculoskele

arXiv:2509.16187v3 Announce Type: replace-cross Abstract: Code translation transforms source code from one programming language (PL) to another. Validating the functional equivalence of translation an

arXiv:2605.30794v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated significant achievements in general visual question answering (VQA) tasks. However, they re

MiniMax M3 launched on June 1, 2026 as the first open-weights model to combine frontier coding, a 1-million-token context window, and native multimodality. The model achieves top-tier performance on c

arXiv:2605.30889v1 Announce Type: cross Abstract: Constructing production-quality machine-learned interatomic potentials (MLIPs) requires balancing accuracy, dynamical stability, and computational thr

The Hermes Skills Hub is a feature that allows users to discover, manage, and integrate skills within the Hermes agent framework, enabling extended functionality and customization of agent capabilitie

NVIDIA DSX OS is an open source, modular software platform designed for operating and scaling multi-tenant AI factories. It provides foundational technologies for building and operating AI factories,

Personal agents are exploding in popularity, with open source projects like OpenClaw and Hermes seeing rapid adoption by AI developer communities on GitHub. Built to adapt to individual preferences an

arXiv:2601.11702v3 Announce Type: replace-cross Abstract: AI compliance is becoming increasingly critical as AI systems grow more powerful and pervasive. Yet the rapid expansion of AI policies creates

arXiv:2605.31463v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become the dominant architecture for frontier language models. To meet this demand, production frameworks have built opti

arXiv:2603.21558v2 Announce Type: replace Abstract: Self-improvement training, where models learn from self-generated solutions, promises sustained capability gains but suffers from a pervasive failur

arXiv:2511.03100v2 Announce Type: replace-cross Abstract: The agent-environment co-design paradigm jointly optimises agent policies and environment configurations in search of improved system performa

arXiv:2605.31113v1 Announce Type: new Abstract: Automatically detecting machine-generated text (MGT) is critical to maintaining the knowledge integrity of user-generated content (UGC) platforms such a

arXiv:2605.31040v1 Announce Type: new Abstract: Developing effective representations for register transfer level (RTL) designs is crucial for accelerating the hardware design workflow. Existing approa

arXiv:2509.21561v2 Announce Type: replace Abstract: Ensuring the safety of surgical instruments requires reliable detection of visual defects. However, manual inspection is prone to error, and existin

arXiv:2605.31281v1 Announce Type: new Abstract: As wind turbine fleets age, data-driven reliability engineering is essential to optimise their operation and maintenance for service life extension and

As artificial intelligence agents begin to proliferate across information technology infrastructure, IT leaders are moving away from asking, “How do we monitor every alert?” to “How do we design infra

Agentic artificial intelligence governance depends upon humans to keep agentic AI from going off the rails. However, putting humans in the loop is woefully insufficient. Here are the problems – and pe

arXiv:2510.04704v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promising potential in scientific research, enabling tasks ranging from knowledge retrieval to propert

arXiv:2602.02849v2 Announce Type: replace Abstract: The design of Analog and Mixed-Signal (AMS) integrated circuits remains heavily reliant on expert knowledge, with transistor sizing a major bottlene

arXiv:2512.00283v3 Announce Type: replace-cross Abstract: Foundation models have revolutionized various fields such as natural language processing (NLP) and computer vision (CV). While efforts have be

arXiv:2605.30000v1 Announce Type: new Abstract: Front-end web code has become a core product surface for every frontier LLM release, yet evaluating these interactive applications at development speed

arXiv:2605.28912v1 Announce Type: new Abstract: The rapid growth of AI-driven data centers and large-scale energy storage systems is increasing the reliance of power system operation on real-time meas

arXiv:2508.19202v3 Announce Type: replace Abstract: Scientific problem solving poses unique challenges for LLMs, requiring both deep domain knowledge and the ability to apply such knowledge through co

arXiv:2605.29695v1 Announce Type: new Abstract: Approximately 10% of newborns require assistance to initiate breathing at birth, and around 5% need ventilation support. Fetal heart rate (FHR) monitori

arXiv:2605.28916v1 Announce Type: cross Abstract: We report a comparison of two state-of-the-art agentic AI systems, Claude Code (Anthropic) and Codex (OpenAI), tasked with autonomously executing a si

arXiv:2605.29955v1 Announce Type: new Abstract: We present AutoformBot, a multi-agent system for building an Autoformalized Textbook Library At Scale (Atlas) in Lean 4. AutoformBot orchestrates thousa

Many organizations’ single source of truth is data that resides in BigQuery, Google’s governed, secure and petabyte-scale data platform. However, the 'last mile' of ad-hoc analysis, modeling, and repo

arXiv:2605.28835v1 Announce Type: cross Abstract: Large Language Models (LLMs) extend their capabilities through function-calling (FC), which relies on training data with high quality, diversity, and

arXiv:2605.29218v1 Announce Type: new Abstract: Web agents, which couple language models with browsing and tool-use capabilities, show promise as open web assistants. Yet progress is increasingly limi

arXiv:2605.28910v1 Announce Type: cross Abstract: Large language models (LLMs) have shown promise on summarization tasks, but they often produce hallucinations, which are unsupported or incorrect stat

This post from LangChain's Harrison Chase contrasts traditional manual methods of improving AI agents (tracing execution, identifying patterns, writing evaluations, and implementing fixes) with a more

arXiv:2511.22884v2 Announce Type: replace Abstract: Data analysis has become an indispensable part of scientific research. To discover the latent knowledge and insights hidden within massive datasets,

arXiv:2410.15236v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have transformed artificial intelligence by advancing natural language understanding and generation, enabling app

arXiv:2605.29259v1 Announce Type: cross Abstract: Given the wide range of deployment targets, flexible model selection is essential for optimizing performance within a given compute budget. Recent wor

arXiv:2605.29798v1 Announce Type: new Abstract: Reliable identification of fracture origins in alumina matrix composite hip and knee implants is critical for quality assurance and patient safety, yet

My MLSys keynote on AI writing systems code got more interest than I expected. The recording will take a while, so in the finest tradition of AI labs sharing blog posts, we’re starting the Core Automa

arXiv:2605.29556v1 Announce Type: new Abstract: Building mathematical optimization models is critical in operations research (OR), while it requires substantial human expertise. Recent advancements ha

arXiv:2605.29829v1 Announce Type: new Abstract: Leveraging Large Language Models (LLMs) to automatically formulate and solve optimization problems from natural language has emerged as an efficient par