Search: “automated”

arXiv:2605.27249v1 Announce Type: new Abstract: An effective method of teaching across disciplines is to provide examples of high-quality work. However, an example may be significantly different from

arXiv:2605.26190v1 Announce Type: cross Abstract: This paper presents the HRVConformer, a novel deep learning architecture for the classification of hypoxic-ischemic encephalopathy (HIE) using the ins

I really appreciate the lessons and technical ideas @samaysham & team were able to share about their tax agent system, which learns from production traces to self-improve via detailed tracing tightly

Anthropic are strongly rumored to be about to have their first profitable quarter. Stories are circulating of companies surprised at how expensive their LLM bills are becoming from usage by their staf

arXiv:2509.18384v2 Announce Type: replace Abstract: Large language models (LLMs) can translate natural language instructions into executable action plans for robotics, autonomous driving, and other do

arXiv:2605.26781v1 Announce Type: new Abstract: Advanced Large Multimodal Models (LMMs) have demonstrated impressive performance in K-12 reasoning tasks, exhibiting great promise as intelligent tutors

arXiv:2605.26438v1 Announce Type: cross Abstract: Large language models can recognize when they are being evaluated (evaluation awareness) and behave differently because of that, which undermines the

arXiv:2605.26840v1 Announce Type: new Abstract: Reinforcement learning with evaluation metrics as rewards is widely used to enhance specific capabilities of language models. However, for tasks such as

arXiv:2510.18668v2 Announce Type: replace-cross Abstract: The vast majority of cardiovascular diseases may be preventable if early signs and risk factors are detected. Cardiovascular monitoring with b

arXiv:2604.04940v2 Announce Type: replace Abstract: Designing effective heuristics for NP-hard combinatorial optimization problems remains challenging and often requires substantial domain expertise.

arXiv:2605.26862v1 Announce Type: new Abstract: Accurate road segmentation from aerial imagery is fundamental to many geospatial applications. However, existing datasets often suffer from limited scen

This article discusses implementing role-based access control (RBAC) systems that work for both human users and AI agents, likely addressing how to manage permissions and authentication in environment

arXiv:2510.09606v2 Announce Type: replace Abstract: With the current surge in spatial reasoning explorations, researchers have made significant progress in understanding indoor scenes, but still strug

arXiv:2605.26682v1 Announce Type: cross Abstract: This dataset provides high-resolution, annotated video sequences of shredded E40-grade steel and copper scrap on a conveyor belt. Captured in a contro

arXiv:2605.26429v1 Announce Type: cross Abstract: This paper addresses structured out-of-distribution (OOD) testing in high-stakes machine learning applications. Traditional conformal methods rely on

arXiv:2605.26151v1 Announce Type: cross Abstract: Contactless diagnosis of musculoskeletal disorders can potentially improve population health as well as robot behaviours in collaborative settings. Ho

arXiv:2510.17790v3 Announce Type: replace-cross Abstract: Computer-use agents face a fundamental limitation. They rely exclusively on primitive GUI actions (click, type, scroll), creating brittle exec

arXiv:2603.23994v2 Announce Type: replace-cross Abstract: Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using executio

arXiv:2605.26118v1 Announce Type: cross Abstract: Porting deep learning algorithms to new hardware accelerators requires developers to repeatedly apply the same low-level optimizations -- quantization

arXiv:2601.16578v2 Announce Type: replace Abstract: We present a reproducible benchmark for evaluating sim-to-real transfer of Multi-Agent Reinforcement Learning (MARL) policies for Connected and Auto

arXiv:2605.25440v1 Announce Type: cross Abstract: Verbal feedback delivered by attending surgeons in the operating room plays a critical formative role in resident trainee skill acquisition. Yet, asse

In this post, we demonstrate the capabilities of AgentWatch through practical implementation. You will see how the solution performs infrastructure checks every 15 minutes, summarizing CloudWatch metr

arXiv:2601.03624v3 Announce Type: replace Abstract: The rapid evolution of Large Language Models (LLM) and subsequent Agentic AI technologies requires systematic architectural guidance for building so

arXiv:2510.10185v2 Announce Type: replace-cross Abstract: Large language models are increasingly being assembled into medical multi-agent systems that emulate multidisciplinary consultation through sp

arXiv:2605.24546v1 Announce Type: new Abstract: Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task trad

arXiv:2605.24219v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents that reason, use tools, and act over multiple steps. Yet most hallucination

arXiv:2605.23931v1 Announce Type: new Abstract: The formal verification of operating system kernels requires precise specifications that capture the intended behavior of system calls. Writing these sp

In this post you'll learn how to build a multi-agent campaign review system that demonstrates parallel reasoning, context persistence, and traceable execution paths using an integrated architecture th

This essay by Ethan Mollick explores how individuals can maintain their humanity and agency in an increasingly AI-driven world, likely addressing practical strategies for preserving human skills, crea

arXiv:2605.26086v1 Announce Type: new Abstract: Large language model agents are increasingly envisioned as always-on personal assistants with access to anything relevant in the user's digital world. Y

arXiv:2605.24253v1 Announce Type: cross Abstract: Digital pathology archives increasingly contain multiple whole-slide images (WSIs) per case, capturing spatially distinct tumour regions and reflectin

arXiv:2605.24267v1 Announce Type: new Abstract: Human conversation relies heavily on conversational implicature, in which speakers convey meanings that are suggested rather than explicitly stated. Alt

arXiv:2505.18979v2 Announce Type: replace Abstract: Text-to-image (T2I) models can generate not-safe-for-work (NSFW) content, motivating multi-stage safety pipelines with both text and image filters.

arXiv:2605.24137v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to generate summaries of software bug reports, including sections such as Steps-to-Reproduce (S2R),

arXiv:2605.24172v1 Announce Type: new Abstract: Secure patient-provider messages contain clinically important communication behaviors that are difficult to characterize manually at scale. The Electron

arXiv:2510.22827v3 Announce Type: replace-cross Abstract: Evaluating text-to-image (T2I) systems requires judging not only whether an image matches a prompt, but also whether socially salient attribut

arXiv:2605.25052v1 Announce Type: new Abstract: Chains of thought (CoTs) have become central in interpreting and auditing behaviors of large language models. Yet growing evidence suggests that these t

arXiv:2605.25447v1 Announce Type: new Abstract: Generating structured, editable diagrams remains a significant challenge for contemporary large language models, despite their proficiency in general-pu

arXiv:2605.24636v1 Announce Type: new Abstract: While large language models (LLMs) hold transformative potential for medicine, their reasoning robustness and safety in real-world clinical scenarios re

arXiv:2507.19219v2 Announce Type: replace Abstract: Overestimation in evaluating large language models (LLMs) has become an increasing concern. Due to the contamination of public benchmarks or imbalan

Over the last 25 years of building Google’s global network, we’ve navigated major architectural eras — from the Internet, to streaming, and the cloud. Today, we are squarely in the midst of a fourth:

arXiv:2605.24883v1 Announce Type: new Abstract: The widespread integration of Large Language Models (LLMs) necessitates rigorous and systematic safety evaluation. Existing paradigms either rely on con

arXiv:2605.25641v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) systems in complex B2B (business-to-business) settings may often receive free-form response feedback. Rathe

arXiv:2605.23997v1 Announce Type: cross Abstract: Multimodal large language models via reinforcement learning (RL) have demonstrated remarkable capabilities in complex visual reasoning tasks, yet they

arXiv:2605.24515v1 Announce Type: new Abstract: With climate change and increasing human pressure on natural landscapes, inland water resources are becoming progressively scarcer, more vulnerable, and

arXiv:2512.15922v3 Announce Type: replace Abstract: Despite initial successes and a variety of architectures, retrieval-augmented generation systems still struggle to reliably retrieve and connect the