Knowledge catalogue
arXiv:2608.26789v1 Announce Type: new Abstract: Accurate steering sensing and LiDAR-to-vehicle extrinsics are crucial for reliable path tracking in warehouse mobile robots (WMRs); miscalibration often
arXiv:2608.26602v1 Announce Type: cross Abstract: Large software repositories are often beyond model context limits. Training repository knowledge into models is costly and quickly stale, while local
arXiv:2608.26895v1 Announce Type: cross Abstract: Agentic recommender systems ground each decision of a large language model (LLM) in a persistent memory of the user, and in existing agents that memor
100% Agree @GavinSBaker. Now, I'm going to debunk every single piece of mis-information about data centers that I've ever seen online: > DISINFORMATION: Data centers use a lot of water. FACT: Most AI
arXiv:2510.16899v2 Announce Type: replace Abstract: AI memory mechanisms primarily focus on preserving information content, often neglecting the validity conditions under which knowledge remains appli
arXiv:2608.26081v1 Announce Type: cross Abstract: Collective intelligence can emerge when individuals coordinate through a shared environment, allowing local actions to accumulate into durable social
arXiv:2608.24040v1 Announce Type: new Abstract: Enterprise AI agents in production often need to be bounded, stateful, observable, and governable rather than fully autonomous. We present PinSieve, a p
arXiv:2608.23893v1 Announce Type: new Abstract: Learning systems deployed over long periods must adapt not only to statistical changes in incoming data, but also to revisions of the definitions that g
arXiv:2608.21423v1 Announce Type: cross Abstract: Agentic security uses large-language-model (LLM) agents to plan, dispatch, and interpret security tools. As these systems move from demonstrations to
arXiv:2608.23283v1 Announce Type: new Abstract: General-purpose language models can reason and synthesize knowledge, but complex work also requires sustained interaction with files, information source
arXiv:2608.22332v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable problem-solving capabilities when guided by Chain-of-Thought (CoT) prompting, yet the internal mecha
arXiv:2608.21964v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over evolving software repositories, where success depends on repository-specific procedural know
arXiv:2608.20845v1 Announce Type: new Abstract: Nearly every retrieval-augmented question-answering system in production ships with a hidden interpreter: on each query a language model re-derives the
arXiv:2608.20965v1 Announce Type: new Abstract: We define an atomic generation fact f=(u,tau,omega,z;rho), recording the origin, realized transformation, concrete occurrence, generated result and rela
arXiv:2608.20218v1 Announce Type: new Abstract: Electronic Navigational Charts (ENCs) are geospatial vector datasets used in maritime navigation systems that represent hydrographic and navigational in
arXiv:2608.20231v1 Announce Type: cross Abstract: The standard objection to full automation is demand-side: if humans earn nothing, who buys the output? This confuses an accounting role with a biologi
arXiv:2603.15722v3 Announce Type: replace-cross Abstract: The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Syste
arXiv:2608.18675v1 Announce Type: new Abstract: Accurate forecasting of energy consumption is important for the efficient operation of power systems, with direct implications for operational costs, en
arXiv:2608.18133v1 Announce Type: new Abstract: Reliable transformer fault diagnosis is essential for maintaining power system stability. The IEEE Key Gas Method (KGM), a widely utilized approach in D
arXiv:2608.17146v1 Announce Type: new Abstract: Symbolic planning with PDDL offers a principled framework for long-horizon robot manipulation, but constructing accurate PDDL domain and problem descrip
In modern enterprise data engineering, Apache Spark remains a cornerstone framework for processing massive datasets at scale. However, managing infrastructure such as provisioning clusters, tuning YAR
arXiv:2608.15533v1 Announce Type: cross Abstract: Linear attention models eliminate the quadratic prefix computation and context-growing KV cache of softmax attention by replacing pairwise token inter
arXiv:2608.16114v1 Announce Type: new Abstract: As agentic tasks grow in complexity, LLM agents increasingly rely on experiential memory to reuse procedural knowledge across tasks. Effective memory de
arXiv:2505.07372v3 Announce Type: replace-cross Abstract: This paper presents a novel methodology for enhancing Automated Program Repair (APR) through synthetic data generation utilizing Large Languag
arXiv:2608.16710v1 Announce Type: new Abstract: As autonomous vehicles (AVs) approach Level 4 and Level 5 operational capability [SAE International, 2018], their on- board decision systems must handle
arXiv:2608.13566v1 Announce Type: cross Abstract: Post-training papers, model cards, and blog posts often treat scores on a small set of coding benchmarks (e.g., SWE-bench and LiveCodeBench) as eviden
arXiv:2608.14032v1 Announce Type: cross Abstract: Existing multimodal RAG methods often flatten structured documents into isolated text and image units, weakening the source organization and local tex
arXiv:2608.14244v1 Announce Type: new Abstract: In large and heavy structures, vibrations arise during motion, posing significant challenges for precise manipulation. To accomplish the desired motion,
arXiv:2608.12977v1 Announce Type: cross Abstract: The expanding operational capabilities of large language model (LLM) agents introduce sophisticated security threats. Runtime defenses have emerged as
arXiv:2608.12426v1 Announce Type: new Abstract: Large language models are increasingly deployed in settings that require simultaneous adherence to multiple explicit constraints - reasoning structure,
arXiv:2608.13029v1 Announce Type: cross Abstract: The field of bioinformatics struggles with legacy code - old code that is commonly used but may no longer have a maintainer, or may be written in an n
arXiv:2608.11359v1 Announce Type: new Abstract: Electricity price forecasting is crucial for market participants but remains difficult because prices are volatile, market-specific, and closely tied to
arXiv:2606.13840v2 Announce Type: replace-cross Abstract: Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and
arXiv:2608.12129v1 Announce Type: new Abstract: While retrieval-augmented generation (RAG) has proven effective at giving LLMs access to external knowledge, mainstream dense-retrieval implementations
arXiv:2608.11802v1 Announce Type: cross Abstract: Methods to increase the resilience of systems to cyber-attacks become increasingly important. Control-flow monitoring provides a principled basis to e
arXiv:2608.10906v1 Announce Type: cross Abstract: An agent skill is a folder containing a SKILL.md file with instructions for a language-model agent, optionally accompanied by scripts and reference fi
arXiv:2608.10963v1 Announce Type: new Abstract: We present the REAP system for the AKBC Shared Task 2026 on constructing knowledge bases from language models in a closed-book setting, subject to a bud
arXiv:2608.08941v1 Announce Type: cross Abstract: Operational Design Domain (ODD) specifications describe where an automated driving system (ADS) is permitted to operate, but they do not prescribe wha
arXiv:2608.09153v1 Announce Type: new Abstract: Production AI agents fail when their context sources -- system prompts, knowledge bases, tool descriptions, and procedural skills -- contain errors or g
arXiv:2608.06640v1 Announce Type: cross Abstract: The widespread integration of AI coding assistants offers undeniable boosts to engineering velocity. Yet, recent studies point to a growing trade-off,
Between chaotic levels of market fragmentation and economic volatility, marketing and communications agencies can no longer rely on the human intuition they’ve traditionally used to win clients and op
arXiv:2608.07077v1 Announce Type: new Abstract: The Tower of Hanoi is a simple planning puzzle that in prior work has proven challenging for large reasoning models (LRMs). Current models solve the sta
arXiv:2608.05159v1 Announce Type: new Abstract: Enterprise operations extensively rely on multiple heterogeneous business systems and information applications, which also result in severe data silos a
arXiv:2607.16465v2 Announce Type: replace Abstract: Edmund C. Berkeley is usually remembered as a mediator between symbolic logic and early computing, yet that standard description understates the sco
In a fast-paced digital economy, data is your most critical engine. Yet, many enterprises find themselves trapped in a costly paradox, spending over 100 hours a week building and fixing fragile, in-ho
arXiv:2608.04738v1 Announce Type: new Abstract: Autonomous research agents can generate hypotheses, execute experiments, and draft manuscripts, yet their outputs often contain unsupported claims and i
arXiv:2608.04307v1 Announce Type: cross Abstract: Text summarization is deceptively difficult. While condensing information seems straightforward, real-world enterprise summarization of support ticket
arXiv:2608.03874v1 Announce Type: new Abstract: Modern agent frameworks equip large language models with external skill libraries to solve complex tasks. However, it remains unclear whether these syst
arXiv:2608.03463v1 Announce Type: new Abstract: Long-term memory is essential for LLM-based agents to sustain interactions and reliably leverage distant history. However, existing memory systems typic
arXiv:2608.02606v1 Announce Type: new Abstract: Fault tolerance in classical computing has traditionally relied on static strategies like hardware redundancy and error-correcting codes. Biological sys
arXiv:2608.03145v1 Announce Type: new Abstract: Deep learning models can predict cancer recurrence from H&E stained slides, but the localized molecular states underlying these predictions remain large
arXiv:2603.20381v2 Announce Type: replace-cross Abstract: Understanding the fundamental mechanisms governing the production of meaning in the processing of natural language is critical for designing s
arXiv:2405.06945v4 Announce Type: replace Abstract: Jointly recovering explicit surface geometry and high-quality appearance from multi-view images remains challenging. This capability is essential fo
arXiv:2608.00401v1 Announce Type: new Abstract: Aerial robots generate structured aeroacoustic fields during flight, yet these signals have been underexplored as a source of onboard relative perceptio
As part of the Agentic Data Cloud launch at Google Cloud Next ‘26, we announced two AI-powered database agents to simplify database management. These include the Database Onboarding Agent for Day 0 op
arXiv:2608.02079v1 Announce Type: new Abstract: In vision-aided navigation and visual-inertial odometry, the quality of triangulated three-dimensional feature positions is a fundamental prerequisite f
arXiv:2608.00492v1 Announce Type: cross Abstract: Predictive coding offers a powerful theory of cortical computation, but corresponding scalable algorithmic implementations for artificial intelligence
arXiv:2607.29405v1 Announce Type: new Abstract: Agentic AI systems act through multi-step trajectories that combine planning, tool use, memory, interaction, and adaptation. This behavior stretches val
arXiv:2512.12816v2 Announce Type: replace Abstract: We study how to allocate resources for training and deployment of machine learning (ML) models under concept drift and limited budgets. We consider
arXiv:2607.29459v1 Announce Type: cross Abstract: Large-scale multivariate time series from heterogeneous IoT sensors demand accurate long-term forecasting for resource scheduling and predictive maint