Knowledge catalogue
AlloyDB is a fully managed, PostgreSQL-compatible database service built for your most demanding enterprise workloads. It combines the best of open source PostgreSQL with Google’s advanced technology,
Vibe coding isn't just for your PC anymore. Here's LLM Hub generating and previewing code entirely on an iPhone. Everything runs locally. Using the RunAnywhere SDK, Timmy Qian ported LLM Hub, an Andro
We're hosting the August LA Agentic AI Meetup on Tuesday, August 11, 5 to 7pm at Gulp in Playa Vista. May drew 70 people. July brought 80. Let's break 100 in August. Come hang out with builders, engin
arXiv:2607.13038v1 Announce Type: cross Abstract: We present the design and implementation of a safety constrained large language model (LLM) system for public health information access, focusing on m
arXiv:2607.14046v1 Announce Type: new Abstract: This paper presents Earthquaker-AI, a hybrid educational framework building upon a previously implemented educational robotics project by integrating a
arXiv:2607.13370v1 Announce Type: cross Abstract: This paper is an extension of a paper presented at the ICAART 2026 conference, which introduced LEA (Learning Engagement Assistant), an adaptive AI tu
arXiv:2607.12336v1 Announce Type: cross Abstract: Artificial Intelligence (AI) technologies, while serving as a foundational enabler for modern social media and digital health services, exert a bivale
arXiv:2512.01241v4 Announce Type: replace-cross Abstract: Large language models (LLMs) and medical AI tools are routinely used by physicians and patients for medical advice, yet their clinical safety
arXiv:2607.11942v1 Announce Type: cross Abstract: KV-cache compression methods are predominantly evaluated with the query appended to the context before compression -- a query-aware protocol. Yet the
arXiv:2607.12310v1 Announce Type: cross Abstract: While modern question answering (QA) systems excel on clean, schema-aligned corpora, real-world knowledge is rarely so neatly packaged. Answering ques
arXiv:2512.04144v3 Announce Type: replace Abstract: Targeted interventions on language models, such as unlearning or model editing, aim to modify specific information, but their effects often propagat
one of the most memorable cooking pods we've had - both in terms of the content and the food! high protein percentage in both. In this episode, @EngramLab co-founder and CEO @dan_biderman joins @allen
How should your security team manage shadow AI? Workloads deployed by developers without formal registration can often evade traditional security scanners, because organizations are reluctant to slow
arXiv:2607.07740v1 Announce Type: cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workfl
arXiv:2607.08495v1 Announce Type: cross Abstract: Sharp et al. (2025) introduce 'agentic inequality' as a framework for analyzing disparities in access to AI agents across three dimensions: availabili
arXiv:2607.07846v1 Announce Type: new Abstract: VectorizationLLM is a specialized Large Language Model based on Google open-weight LLMs. The model is designed to assist students to learn smart vectori
arXiv:2607.06839v1 Announce Type: cross Abstract: Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain
arXiv:2510.17476v2 Announce Type: replace Abstract: Equitable access to reliable health information is vital when integrating AI into healthcare. Yet, information quality varies across languages, rais
arXiv:2607.05483v1 Announce Type: cross Abstract: Agentic workflows often operate over shared, structured state. Because LLM context windows are limited, each model invocation is typically shown only
arXiv:2607.05479v1 Announce Type: cross Abstract: Generative AI (GenAI) systems store and process client data in three distinct ways: in the model's parameters through training and memorisation, in th
Moving Beyond the Prototype The AI landscape has shifted. While 'vibe coding' with tools like Antigravity and AI Studio lets you build and deploy complex agents in minutes, the real work begins on 'Da
arXiv:2605.06605v2 Announce Type: replace Abstract: Evaluating and predicting the performance of large language models (LLMs) in multi-turn conversational settings is critical yet computationally expe
arXiv:2605.06142v2 Announce Type: replace-cross Abstract: When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than expl
arXiv:2602.23297v2 Announce Type: replace Abstract: Medical diagnosis requires the effective synthesis of visual manifestations and clinical metadata. However, existing methods often treat metadata as
arXiv:2607.05055v1 Announce Type: new Abstract: Healthcare appointment scheduling remains a persistent operational bottleneck, driven by manual coordination, fragmented legacy systems, and high admini
arXiv:2607.03836v1 Announce Type: cross Abstract: Despite remarkable progress in machine translation, Vision Language Models (VLMs) struggle on historical manuscripts, a domain that stresses core Natu
Most agentic retrieval demos assume clean, well-structured documents. Enterprise reality is often different, consisting of messy PDFs where critical information is buried across tables, figures, and c
arXiv:2607.02262v1 Announce Type: new Abstract: Reasoning Language Models (RLMs) have significantly improved performance on complex tasks by extending the reasoning chain. However, these chains are pr
arXiv:2607.02116v1 Announce Type: new Abstract: Autonomous AI agents increasingly depend on external knowledge stores, yet most retrieval pipelines provide relevance without durable guarantees of prov
arXiv:2607.01557v1 Announce Type: cross Abstract: Large Language Models (LLMs) often struggle with persuasion in high-stakes scenarios. People's individual personalities and concerns require tailored
arXiv:2607.01276v1 Announce Type: cross Abstract: Embedding models are essential components of modern Information Retrieval (IR) systems, yet they are typically hidden behind APIs. Recent works have s
arXiv:2602.03315v2 Announce Type: replace Abstract: Agent memory systems must accommodate continuously growing information while supporting efficient, context-aware retrieval for downstream tasks. Abs
arXiv:2607.02185v1 Announce Type: cross Abstract: Deep learning has achieved remarkable performance in medical image segmentation, yet it suffers from critical limitations: mathematical intractability
arXiv:2607.00147v1 Announce Type: new Abstract: Rare disease differential diagnosis is a critical yet arduous clinical task, requiring physicians to identify precise phenotypes from complex, unstructu
arXiv:2603.26266v3 Announce Type: replace Abstract: Large vision-language models have endowed GUI agents with strong general capabilities for interface understanding and interaction. However, due to i
arXiv:2606.28467v1 Announce Type: cross Abstract: Appliance-level energy monitoring in office buildings produces noisy alerts that non-expert facility managers struggle to use. This paper proposes an
arXiv:2606.17041v4 Announce Type: replace Abstract: Meta-analysis is a demanding form of evidence synthesis that combines literature retrieval, PI/ECO-guided study selection, and statistical aggregati
arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different
arXiv:2606.29746v1 Announce Type: new Abstract: Navigating the deluge of heterogeneous medical data, from academic literature (PubMed) to clinical guidelines (Web) and private knowledge bases, remains
arXiv:2507.05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while a
arXiv:2606.28409v1 Announce Type: cross Abstract: Software-compilable C programs routinely fail to complete the four-stage pipeline of a high-level synthesis (HLS) toolchain -- compilation, C simulati
arXiv:2606.29243v1 Announce Type: new Abstract: We present KrishokChat, the first citation-grounded Bengali agricultural instruction-tuning dataset for crop advisory in low-resource settings. We estab
arXiv:2606.29778v1 Announce Type: cross Abstract: Long-term conversational agents need to remember and query cross-session, multi-typed information with complex correlations. Existing agent memory sys
arXiv:2606.29824v1 Announce Type: cross Abstract: While Large Language Models (LLMs) excel as static solvers, transforming them into autonomous agents remains challenging. This transition requires con
arXiv:2606.30139v1 Announce Type: new Abstract: Relevance is not permission. Attention lets a model read key-value items related to the current query, but it does not guarantee that the value contribu
arXiv:2606.28002v1 Announce Type: cross Abstract: Insurance fraud imposes substantial financial losses and operational inefficiencies, raising premiums and impacting trust among legitimate policyholde
arXiv:2606.28011v1 Announce Type: cross Abstract: We propose an agentic Large Language Model (LLM) framework for active Fault-Tolerant Control (FTC) that transforms fault detection outputs into constr
arXiv:2606.27974v1 Announce Type: cross Abstract: Knowledge-based Visual Question Answering (KB-VQA) requires models to combine image understanding with external knowledge. Most prior methods use a fi
arXiv:2606.21649v2 Announce Type: replace Abstract: Existing embedding models are inherently static: they encode text segments in isolation, ignoring their surrounding context and temporal order. This
arXiv:2606.26857v1 Announce Type: new Abstract: The interpretation phase of life cycle assessment often lacks structured mechanisms for translating quantified improvement opportunities addressing envi
arXiv:2606.26157v1 Announce Type: cross Abstract: The rapid growth of digital pathology has created an urgent need for efficient indexing and retrieval of whole slide images (WSIs). This need is inten
arXiv:2606.26476v1 Announce Type: cross Abstract: Warm-started diffusion samplers accelerate iterative inference, but it is rarely clear which part of the pipeline carries the gain. We study extbf{ret
arXiv:2606.24902v1 Announce Type: cross Abstract: The 'First Proof' benchmark [1] posed ten research-level mathematics questions to the strongest publicly available LLMs and found them consistently wr
Telecommunications is an incredibly complex, highly specialized domain. Modern mobile networks are inherently multi-vendor, featuring diverse and often proprietary data structures. While AI has made m
Protecting sensitive data used with AI is a critical part of our commitment to providing advanced and secure cloud infrastructure. Confidential Computing cryptographically protects data in use in hard
Vector search is a retrieval method that converts unstructured data (text, images, audio) into numerical vector representations and finds similar items by comparing vectors in high-dimensional space,
Why the structure matters: OCR 4 localizes each block with a bounding box, classifies it (title, table, equation, signature…), and scores confidence per region, the foundation for source-grounded cita
You've got a working prototype in Google AI Studio. A React frontend, a Node.js backend, maybe a database. Now you want a live URL to share with your team, your users, or a friend who wants to try it.
arXiv:2606.11910v1 Announce Type: new Abstract: Traffic law liability determination is critical for assigning legal penalties, requiring the simultaneous identification of interdependent statutory pro
arXiv:2603.08501v3 Announce Type: replace Abstract: Large language models (LLMs) can answer religious knowledge queries fluently, yet they often hallucinate and misattribute sources, which is especial