Knowledge catalogue
arXiv:2606.29116v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combin
Automated lint: 49 errors, 14 warnings, 3 info
Automated lint: 48 errors, 13 warnings, 3 info
arXiv:2606.08729v1 Announce Type: cross Abstract: Simulation plays a key role in automated robotics research supported by large language models (LLMs). However, existing simulators often require custo
arXiv:2508.00724v2 Announce Type: replace-cross Abstract: The increasing demand for flexible automation has accelerated the adoption of heterogeneous automated guided vehicles (AGVs). This work invest
Automated lint: 47 errors, 12 warnings, 3 info
An open-source browser with built-in AI agents that emphasizes privacy and automation, enabling task automation through natural language without coding. The browser supports multiple AI providers incl
arXiv:2308.04823v5 Announce Type: replace Abstract: This paper unveils CG-Eval, the first-ever comprehensive and automated evaluation framework designed for assessing the generative capabilities of la
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arXiv:2602.24138v2 Announce Type: replace Abstract: Automated recognition of surgical phases and steps is a fundamental capability for intraoperative decision support, workflow automation, and skill a
arXiv:2605.14790v1 Announce Type: cross Abstract: Research idea generation is the innovation-driving step of automated scientific research. Recently, large language models (LLMs) have shown potential
arXiv:2605.05682v2 Announce Type: replace-cross Abstract: Recent developments in AI safety research have called for red-teaming methods that effectively surface potential risks posed by generative AI
Automated lint: 45 errors, 11 warnings, 3 info
The momentum is undeniable: the world’s fastest-growing AI startups are building with Google Cloud. Instead of stitching together fragmented point solutions, founders are building their businesses her
Automated lint: 44 errors, 10 warnings, 3 info
This is crazy. ml-intern just passed the @huggingface internship test in 15 minutes. The task: replicate a research baseline from a DeepMind paper on test-time compute scaling. Here's what the agent d
In the early days of generative AI, building safe and reliable business tools took massive engineering effort and a high tolerance for trial and error. We helped solve that with Vertex AI, our trusted
Automated lint: 43 errors, 9 warnings, 3 info
arXiv:2604.14034v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence, particularly Large Language Models (LLMs), have stimulated growing interest in automating or as
arXiv:2604.09578v1 Announce Type: new Abstract: The recent advancement in artificial intelligence (AI) technologies facilitates a paradigm shift toward automation. Autonomous systems are fully or part
Automated lint: 34 errors, 0 warnings, 3 info
In the enterprise landscape, data is often highly fragmented across multiple source systems. Data curation is the process of organizing, cleaning, and enriching raw data to transform it into high-qual
arXiv:2604.08523v1 Announce Type: new Abstract: AI agents may be able to automate your inbox, but can they automate other routine aspects of your life? Everyday online tasks offer a realistic yet unso
Compliance workflow automation startup Haast Pty Ltd. said today it has raised $12 million in an early-stage round of funding to help organizations accelerate the rollout of artificial intelligence-ge
arXiv:2610.17130v2 Announce Type: new Abstract: Automated alpha factor discovery is critical for modern quantitative research. While large language models (LLMs) have increasingly been integrated into
arXiv:2610.19735v1 Announce Type: new Abstract: Scenario-based validation is essential for automated road vehicles but cannot cover the full variability of openworld traffic. We present MakSafe, a for
arXiv:2610.17951v1 Announce Type: new Abstract: Head circumference (HC) measured from 2D ultrasound is a routine marker of fetal growth, and automating it needs segmentations whose boundaries hold up
arXiv:2610.15286v1 Announce Type: new Abstract: The accuracy of detecting protein crystals for fluorescence microscopy images is very critical for high throughput and automated systems. Although the t
TRL v1.15 is out, and it’s an absolute banger of a release for memory-efficient post-training. The main change: SFT, DPO, KTO, GRPO, RLOO and Distillation now use a fused LM head by default. Instead o
arXiv:2610.11674v1 Announce Type: new Abstract: Automated video surveillance analysis has become a critical component of intelligence infrastructures and Law Enforcement agencies. Traditional systems
arXiv:2607.10826v2 Announce Type: replace-cross Abstract: Automated evaluation is essential for scaling generative 3D systems, where exhaustive human review is costly and slow. Yet the reliability of
arXiv:2610.08026v1 Announce Type: new Abstract: In recent years, several methods for detecting when large language models (LLMs) hallucinate have been developed. These methods are often benchmarked wi
arXiv:2610.03896v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for automated algorithm design. However the computational cost of evaluating the generated algorithms
arXiv:2610.06366v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed for automated software vulnerability analysis. Binary classification alone is insufficient; pra
arXiv:2610.02361v1 Announce Type: cross Abstract: Large language model (LLM)-driven evolutionary search is a powerful paradigm for automated program and algorithm discovery, yet existing systems are l
arXiv:2609.40284v1 Announce Type: cross Abstract: Computer use agents (CUAs), which use graphical user interfaces (GUIs) to complete tasks on a computer, have recently surpassed human performance on m
arXiv:2609.35806v1 Announce Type: cross Abstract: Automated skill extraction underpins workforce planning, yet most systems represent skills as flat labels with no notion of the responsibility level a
arXiv:2609.27336v1 Announce Type: new Abstract: Automated red teaming often replays a fixed set of prompts, which measures known risks but cannot learn from failures found during testing. We present C
AIOps (Artificial Intelligence for IT Operations) merges AI and machine learning with comprehensive observability to automate event correlation, root‑cause analysis, anomaly detection, incident respon
Who need words any more Words are just human kludge AI don’t need no words We release Needle 3: A Sliceable 8-29MB automation foundation model that can match DeepSeek V4 Flash. One set of weights, eve
arXiv:2603.11667v3 Announce Type: replace Abstract: This paper examines how value is constructed and negotiated in today's increasingly automated language and translation industry. Drawing on intervie
arXiv:2609.14839v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into automated code optimization introduces a critical reliability risk we term the Efficiency Halluci
arXiv:2609.14770v1 Announce Type: cross Abstract: Generalisations are common in scientific communication, even though they are semantically ambiguous. An automated method is needed to identify and cat
arXiv:2609.14533v1 Announce Type: cross Abstract: Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2]. It underpins a wide rang
arXiv:2609.12491v1 Announce Type: new Abstract: Skeleton-based action recognition can support automated tracking of physiotherapy exercises, particularly in remote rehabilitation settings where contin
arXiv:2609.10594v1 Announce Type: cross Abstract: Expert evaluation of jailbreak responses is costly and difficult to scale, so the community increasingly relies on automated evaluators to determine w
arXiv:2609.08256v1 Announce Type: cross Abstract: Automated red-team attacks and blue-team defenses for large language models (LLMs) are advancing quickly. However, attackers and defenders are built a
arXiv:2601.13591v3 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-
arXiv:2609.10123v1 Announce Type: cross Abstract: Large language models (LLMs) have become ubiquitous in software development, with LLM-based automated program repair tools increasingly used during co
arXiv:2609.04439v1 Announce Type: new Abstract: Automated aortic segmentation in 4D flow MRI is essential for reproducible hemodynamic assessment but is limited by scarce dense annotations and high co
This research details an agentic framework that automatically generates custom GPU kernels and rigorously validates them. By integrating automated synthesis and thorough performance testing, the syste
arXiv:2609.03463v1 Announce Type: new Abstract: Automated pig monitoring is essential for assessing their health, behaviour, and welfare. To date, most pig monitoring solutions operate on the group-le
arXiv:2412.14626v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing
arXiv:2609.00682v1 Announce Type: new Abstract: Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-c
Introduction Beginning in 2024 Mandiant investigated a string of compromises affecting Brazilian financial services, retail, and eCommerce organizations. Google Threat Intelligence Group (GTIG) tracks
arXiv:2608.27923v1 Announce Type: new Abstract: Printed circuit boards (PCBs) are fundamental to modern electronic systems, yet AI-driven PCB design automation remains constrained by the lack of large
arXiv:2608.25570v1 Announce Type: new Abstract: Hardware kernel optimization requires repeated compilation, correctness testing, profiling, and revision. LLM agents can automate parts of this process,
arXiv:2608.25660v1 Announce Type: new Abstract: Automated novelty judgment can accelerate scientific discovery by enabling efficient evaluation, refinement, and comparison of research ideas. While lar
arXiv:2608.24793v1 Announce Type: new Abstract: Automated malaria diagnosis from stained blood-smear microscopy is dominated by deep convolutional neural networks that are accurate but computationally
arXiv:2608.23061v1 Announce Type: new Abstract: Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucinat