Knowledge catalogue
Written by: Chad Reams, Tufail Ahmed, Keith Knapp, Ashley Frazer, Tyler McLellan Introduction From January through May 2026, Mandiant identified a financially motivated data theft extortion campaign e
arXiv:2606.04647v1 Announce Type: new Abstract: Active learning (AL) for node classification typically focuses on selecting the most informative nodes for annotation within one or a few large graphs (
arXiv:2407.03956v3 Announce Type: replace-cross Abstract: Prior research has enhanced the ability of Large Language Models (LLMs) to solve logic puzzles using techniques such as chain-of-thought promp
We have a Fleet agent called @docs_plz in our Slack that's made a very noticeable impact on our velocity of docs changes. In the chart below, you can clearly see that after it was added, the amount of
arXiv:2506.02018v2 Announce Type: replace Abstract: Paraphrasing re-expresses meaning to enhance applications like text simplification, machine translation, and question-answering. Specific paraphrase
arXiv:2606.03412v1 Announce Type: new Abstract: During the recent years, the use of linguistic data for language processing increased progressively. Such data are now commonly called language resource
arXiv:2606.00027v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed across healthcare, yet existing benchmarks fail to capture model behavior under adversarial or
arXiv:2603.19005v2 Announce Type: replace-cross Abstract: Data science plays a critical role in transforming complex data into actionable insights across numerous domains. Recent developments in large
arXiv:2606.00154v1 Announce Type: cross Abstract: Recent advancements in multimodal large language models (MLLMs) have achieved remarkable progress in multimodal reasoning and code generation, catalyz
arXiv:2603.24511v2 Announce Type: replace-cross Abstract: We show that AI agents are capable of discovering novel algorithms for adversarial attacks against LLMs, advancing the state of the art on whi
arXiv:2606.00472v1 Announce Type: cross Abstract: Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feat
Google Cloud Storage (GCS) is a foundational component of the modern agentic tech stack and the preferred home for unstructured data at scale. As enterprises deploy agents in production, the critical
arXiv:2506.11083v3 Announce Type: replace Abstract: We introduce RedDebate, a novel multi-agent debate framework that provides the foundation for Large Language Models (LLMs) to identify and mitigate
arXiv:2603.25640v2 Announce Type: replace-cross Abstract: Accurate parsing of citations is necessary for machine-readable scholarly infrastructure. But, despite sustained interest in this problem, exi
arXiv:2606.01820v1 Announce Type: new Abstract: Fine-grained morphosyntactic error annotation is important in clinical and developmental language research, yet it is labour-intensive, expert-dependent
arXiv:2605.31468v1 Announce Type: new Abstract: Scientific research has traditionally been human-intensive, requiring researchers to coordinate literature, ideas, experiments, manuscripts, and review
arXiv:2601.21372v2 Announce Type: replace Abstract: We present NEMO, a system that translates Natural-language descriptions of decision problems into formal Executable Mathematical Optimization implem
arXiv:2506.12060v2 Announce Type: replace-cross Abstract: Cybersecurity organizations are adapting to GenAI integration through modified frameworks and hybrid operational processes, with success influ
arXiv:2602.22971v2 Announce Type: replace Abstract: As LLMs achieved breakthroughs in general reasoning, their proficiency in specialized scientific domains reveals pronounced gaps in existing benchma
arXiv:2605.28994v1 Announce Type: new Abstract: AI tools to support real world decision making must be able to build simulation models that inform their recommendations and render them interpretable.
arXiv:2605.29786v1 Announce Type: new Abstract: Reproducibility is fundamental to the scientific method, yet remains a critical challenge in machine learning. Contributing factors include underspecifi
arXiv:2605.29378v1 Announce Type: new Abstract: Natural language interfaces can simplify interaction with multi-robot systems, especially when non-expert users need to issue high-level commands. Acous
arXiv:2605.29795v1 Announce Type: new Abstract: Real-world tasks often lack large labeled datasets, motivating extensive work on learning in low-data regimes. However, existing approaches such as few-
arXiv:2605.29220v1 Announce Type: new Abstract: Tracking the dynamics of non-canonical biological systems in microscopy videos remains a persistent challenge. Both classical and learning-based tracker
Google’s mission is to organize the world’s information and make it universally accessible. In high-growth, technically ambitious markets like the Middle East, North Africa, and Türkiye (MENA-T), we f
arXiv:2605.27725v1 Announce Type: cross Abstract: High-fidelity computational fluid dynamics (CFD) is widely used for thermal-fluid design, but repeated CFD solves remain expensive for design optimiza
arXiv:2605.27402v1 Announce Type: cross Abstract: Open-ended grading is central to equitable and personalized education, yet manual grading remains time-consuming and costly, underscoring the need for
arXiv:2510.20665v3 Announce Type: replace Abstract: Evaluating the quality of reasoning traces from large language models remains understudied, labor-intensive, and unreliable: current practice relies
arXiv:2605.27131v1 Announce Type: cross Abstract: Enterprise data platforms face an enduring tension between domain self-service and holistic governance. The data mesh paradigm proposed decentralized
arXiv:2605.26898v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate functional source code from natural-language prompts, but often fail to consistently follow higher-level arc
arXiv:2605.23920v1 Announce Type: cross Abstract: Real-effort tasks, in which participants perform cognitively costly activities whose outcomes depend on actual performance, are widely used in experim
arXiv:2605.26100v1 Announce Type: cross Abstract: Code review is a critical practice in software engineering, yet the growing scale and frequency of code patches in modern projects, together with the
arXiv:2410.01648v2 Announce Type: replace Abstract: The increasing availability of sensitive textual data has created an urgent need for robust de-identification methods that enable compliant data sha
arXiv:2605.25781v1 Announce Type: new Abstract: Evaluating structured-information extraction from historical documents at scale requires high-precision ground-truth annotations, yet traditional manual
arXiv:2605.22093v2 Announce Type: replace Abstract: Knowledge graphs have become the primary vehicle for data integration and are critical to the success of modern AI, but the diversity of KG modellin
arXiv:2605.25955v1 Announce Type: cross Abstract: Large language models (LLMs) face a dual challenge in creative capability evaluation: existing benchmarks (e.g., Story Cloze Test, HellaSwag) measure
arXiv:2605.05795v2 Announce Type: replace Abstract: Decomposing complex tasks into a sequence of simpler subtasks can improve learning efficiency for an autonomous agent. Reinforcement learning (RL) c
arXiv:2601.06201v2 Announce Type: replace-cross Abstract: Enterprises are confronted with an unprecedented escalation in cybersecurity vulnerabilities, with thousands of new CVEs disclosed each month.
arXiv:2605.22993v1 Announce Type: cross Abstract: Characteristic linguistic behaviors associated with Social Language Disorder (SLD) in autism spectrum disorder, including echoic repetition, pronoun d
arXiv:2605.22195v1 Announce Type: new Abstract: Graph of Thoughts (GoT), a generalized form of recent prompting paradigms for large language models (LLMs), has been shown to be useful for elaborate pr
arXiv:2508.08636v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized artificial intelligence by enabling complex reasoning capabilities. While recent advancements in re
arXiv:2605.20973v1 Announce Type: new Abstract: The effectiveness of rock support in underground mines depends on the interaction between installed rock bolts and the structural fabric of the surround
arXiv:2605.21397v1 Announce Type: cross Abstract: Navigation mesh (Navmesh) inconsistencies affect the player experience by directly impacting the navigation systems used by non-playable characters (N
arXiv:2605.19518v1 Announce Type: new Abstract: Generating Knowledge Graphs (KGs) remains one of the most time-consuming and labor-intensive tasks for knowledge engineers, as they need to identify sem
arXiv:2509.14839v2 Announce Type: replace Abstract: City administrations increasingly rely on comprehensive databases and urban digital twins of city assets, such as traffic signs and trees, as well a
arXiv:2605.19755v1 Announce Type: cross Abstract: Artificial Intelligence (AI) systems are increasingly dependent on complex, multi-layered software supply chains that introduce challenges for reprodu
arXiv:2511.06316v3 Announce Type: replace Abstract: In low- and middle-income countries, public safety and urban planning initiatives frequently face a critical shortage of accurate, location-specific
arXiv:2605.18703v1 Announce Type: new Abstract: Equipping LLMs with tool-use capabilities via Agentic Reinforcement Learning (Agentic RL) is bottlenecked by two challenges: the lack of scalable, robus
arXiv:2605.18261v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has demonstrated promising potential to enhance the reasoning capabilities of large language model
arXiv:2605.18239v1 Announce Type: cross Abstract: Large Language Models (LLMs) remain vulnerable to jailbreak attempts that circumvent safety guardrails. We investigate whether multi-turn conversation
arXiv:2605.18004v1 Announce Type: new Abstract: Randomized linear algebra (RLA) algorithms are a modern class of numerical linear algebra techniques that play an essential role in scientific computing
arXiv:2602.22941v2 Announce Type: replace Abstract: Pacing strategies, defined by velocity and stroke rate profiles, are essential for peak performance in canoe sprint. While GPS is the gold standard
arXiv:2605.15537v1 Announce Type: new Abstract: This paper introduces RTL-BenchMT, an agentic framework for dynamically maintaining RTL generation benchmarks. Large Language Models (LLMs) assisted aut
Databricks has integrated OpenAI's GPT-5.5 model into enterprise agent workflows, enabling organizations to build and deploy AI agents with advanced language capabilities. This partnership leverages D
I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they inc
arXiv:2605.14527v1 Announce Type: new Abstract: Developing machine learning interatomic potentials (MLIPs) for complex materials systems remains challenging because it requires expertise in atomistic
arXiv:2601.19924v2 Announce Type: replace-cross Abstract: We investigate the capabilities and scalability of Large Language Models (LLMs) in optimization modeling, a domain requiring structured reason
arXiv:2605.12662v1 Announce Type: new Abstract: High-dimensional point cloud data arise across many scientific domains, especially single-cell biology. The shapes or topologies of these datasets deter
arXiv:2504.14707v3 Announce Type: replace Abstract: We introduce FLAME (FLemish Accounts of Momentary Experiences), a new corpus of nearly 25,000 daily personal narratives in Belgian-Dutch (Flemish),
In the healthcare and life sciences industries, speed saves lives, but meeting regulatory requirements and other administrative burdens often pumps the brakes for manufacturers of software as a medica