Knowledge catalogue
Today, we announced the preview of Spanner Omni, a downloadable version of Spanner, that expands its industry-leading distributed database capabilities beyond Google Cloud. This enables enterprises to
arXiv:2603.16497v2 Announce Type: replace-cross Abstract: Time series foundation models (TSFMs) require diverse, real-world datasets to adapt across varying domains and temporal frequencies. However,
arXiv:2604.19488v1 Announce Type: new Abstract: Large language models (LLMs) have achieved substantial advances in logical reasoning, yet they continue to lag behind human-level performance. In-contex
arXiv:2604.19318v1 Announce Type: new Abstract: Multi-view crowd tracking estimates each person's tracking trajectories on the ground of the scene. Recent research works mainly rely on CNNs-based mult
This Databricks resource discusses production-ready architectural approaches for integrating multimodal data (structured, unstructured, images, text, etc.) in healthcare AI systems. It likely covers b
arXiv:2601.13729v2 Announce Type: replace Abstract: In recent years, the non-deterministic properties of language models have garnered considerable attention and have shown a significant influence on
arXiv:2604.18864v1 Announce Type: new Abstract: Generalized Additive Models (GAMs) can be used to create non-linear glass-box (i.e. explicitly interpretable) models, where the predictive function is f
arXiv:2510.18333v2 Announce Type: replace-cross Abstract: Despite progress in watermarking algorithms for large language models (LLMs), real-world deployment remains limited. We argue that this gap st
The future is taking shape in Las Vegas this week, where the world’s leading startups are showcasing their groundbreaking AI work at Google Cloud Next. Whether they need the top AI models, infrastruct
arXiv:2508.16846v5 Announce Type: replace-cross Abstract: Sycophancy (overly agreeable or flattering behavior) poses a fundamental challenge for human-AI collaboration, particularly in high-stakes dec
arXiv:2604.18399v1 Announce Type: new Abstract: Daily infrastructure management in preparation for disasters is critical for urban resilience. When bridges remain resilient against disaster-induced ex
arXiv:2604.17500v1 Announce Type: new Abstract: Scene text editing (STE) has achieved remarkable progress in accurately rendering target text through diffusion-based methods. However, we identify a cr
arXiv:2505.21282v2 Announce Type: replace Abstract: Data-driven navigation algorithms are critically dependent on large-scale, high-quality real-world data collection for successful training and robus
arXiv:2505.00986v2 Announce Type: replace-cross Abstract: Continual Test-time adaptation (CTTA) continuously adapts the deployed model on every incoming batch of data. While achieving optimal accuracy
arXiv:2604.17956v1 Announce Type: new Abstract: Machine learning has become integral to medical research and is increasingly applied in clinical settings to support diagnosis and decision-making; howe
arXiv:2511.16698v2 Announce Type: replace Abstract: SNOMED CT is a biomedical ontology with a hierarchical representation, modelling terminological concepts at a large scale. Knowledge retrieval in SN
arXiv:2604.16953v1 Announce Type: cross Abstract: Breast cancer diagnosis through thermographic image analysis remains a critical challenge in medical AI, with classical deep learning approaches facin
arXiv:2604.16988v1 Announce Type: new Abstract: Non-stationary sequences arise naturally in control, forecasting, and decision-making. The data-generating process shifts at unknown times, and models m
The Databricks Excel Add-in is a tool that enables business users to directly access and analyze data from Databricks within Microsoft Excel without requiring advanced technical skills. This integrati
arXiv:2604.18381v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) typically relies on large quantities of high-quality annotated data, or questions with well-defined ground tr
arXiv:2601.19079v2 Announce Type: replace Abstract: Conventional robotic Braille readers typically rely on discrete, character-by-character scanning, limiting reading speed and disrupting natural flow
arXiv:2503.08478v2 Announce Type: replace Abstract: Privacy concerns around ever increasing number of cameras are increasing in today's digital age. Although existing anonymization methods are able to
arXiv:2506.06024v2 Announce Type: replace-cross Abstract: Signal restoration and inverse problems are key elements in most real-world data science applications. In the past decades, with the emergence
arXiv:2604.18327v1 Announce Type: cross Abstract: Reward models (RMs) are central to aligning large language models (LLMs) with human preferences, powering RLHF and advanced decoding strategies. While
arXiv:2604.17278v1 Announce Type: new Abstract: Effective pest recognition and management are crucial for sustainable agricultural development. However, collecting pest data in real scenarios is often
arXiv:2604.17543v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challeng
arXiv:2504.07415v2 Announce Type: replace-cross Abstract: Automated radiology report generation (RRG) holds potential to reduce the workload of radiologists, and recent advances in multimodal large la
arXiv:2604.16817v1 Announce Type: new Abstract: Imbalanced data is commonly present in real-world applications. While data synthesis can effectively mitigate the data scarcity problem of rare-classes,
arXiv:2410.05248v4 Announce Type: replace Abstract: To acquire instruction-following capabilities, large language models (LLMs) undergo instruction tuning, where they are trained on instruction-respon
arXiv:2506.10060v2 Announce Type: replace Abstract: Although large language models (LLMs) are becoming increasingly capable of solving challenging real-world tasks, accurately quantifying their uncert
arXiv:2604.16442v1 Announce Type: cross Abstract: Sleep staging is essential for the assessment of sleep quality and the diagnosis of sleep-related disorders. Conventional polysomnography (PSG), while
arXiv:2604.16443v1 Announce Type: cross Abstract: Data-driven models for building thermal dynamics are a scalable approach for enabling energy-efficient operation through fault detection & diagnosis o
arXiv:2512.22502v2 Announce Type: replace Abstract: Ball-end milling path planning on multiply connected freeform surfaces is pivotal for high-quality and efficient machining of components in automoti
arXiv:2604.15903v1 Announce Type: new Abstract: Shadows are prevalent in high-resolution aerospace imagery (ASI). They often cause spectral distortion and information loss, which degrade downstream in
arXiv:2604.15857v1 Announce Type: new Abstract: Recent digital media advancements have created increasing demands for sophisticated portrait manipulation techniques, particularly head swapping, where
arXiv:2604.15395v1 Announce Type: new Abstract: Over the recent years, the field of robotics has been undergoing a transformative paradigm shift from fixed, single-task, domain-specific solutions towa
arXiv:2604.15833v1 Announce Type: new Abstract: Spatiotemporal modeling has evolved beyond simple time series analysis to become fundamental in structural time series analysis. While current research
This post discusses the mathematical principle that when attempting a 1/n probability event n times, the probability of at least one success converges to approximately 63.2% (mathematically 1 - 1/e ≈
arXiv:2603.10992v3 Announce Type: replace-cross Abstract: Building local surrogates to accelerate stationary point searches on potential energy surfaces spans decades of effort. Done correctly, surrog
arXiv:2604.14186v1 Announce Type: cross Abstract: Large self-supervised speech (SSL) models achieve strong downstream performance, but their size limits deployment in resource-constrained settings. We
arXiv:2604.15109v1 Announce Type: new Abstract: Despite the rapid advancement of Large Language Models (LLMs), uncertainty quantification in LLM generation is a persistent challenge. Although recent a
arXiv:2604.14562v1 Announce Type: new Abstract: Accurate thermal modeling in metal additive manufacturing (AM) is essential for understanding the process-structure-performance relationship. While prio
arXiv:2604.15170v1 Announce Type: new Abstract: Adverse lighting conditions, such as cast shadows and irregular illumination, pose significant challenges to computer vision systems by degrading visibi
arXiv:2604.15027v1 Announce Type: new Abstract: Significant progress has been made in detecting synthetic images, however most existing approaches operate on a single image instance and overlook a key
arXiv:2604.14941v1 Announce Type: new Abstract: Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically gener
arXiv:2601.03523v2 Announce Type: replace Abstract: One of the most important queries in knowledge compilation is weighted model counting (WMC), which has been applied to probabilistic inference on va
arXiv:2604.13939v1 Announce Type: new Abstract: Computer vision techniques have advanced significantly in recent years, finding diverse and impactful applications within the medical field. In this pap
arXiv:2511.10946v3 Announce Type: replace Abstract: Vision-language models (VLMs) struggle with 3D-related tasks such as spatial cognition and physical understanding, which are crucial for real-world
Databricks Document Intelligence and Lakeflow are tools designed to extract structured data from unstructured documents using AI and machine learning capabilities. This resource covers how to build an
arXiv:2604.14025v1 Announce Type: new Abstract: Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and i
IBM Quantum is leveraging quantum computing technology to advance healthcare and biology research, with the company highlighting selected finalists in their quantum-for-biology (Q4Bio) initiative. The
arXiv:2604.13078v1 Announce Type: new Abstract: The Ramayana is among the most influential literary traditions of South and Southeast Asia, transmitted across numerous linguistic and cultural contexts
arXiv:2508.05663v4 Announce Type: replace-cross Abstract: Random walk (RW)-based algorithms have long been popular in distributed systems due to low overheads and scalability, with recent growing appl
arXiv:2604.13739v1 Announce Type: new Abstract: Thompson Sampling (TS) has attracted a lot of interest due to its good empirical performance, in particular in the computational advertising. Though suc
arXiv:2602.05971v2 Announce Type: replace Abstract: Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To
This Reddit discussion thread from r/MachineLearning explores the growing challenges faced by applicants from non-elite undergraduate institutions when applying to PhD programs in machine learning and
arXiv:2604.11928v1 Announce Type: new Abstract: Time-series forecasting aims to predict future values by modeling temporal dependencies in historical observations. It is a critical component of many r
arXiv:2410.04960v5 Announce Type: replace Abstract: The Segment Anything Model (SAM) is a foundational model for image segmentation tasks, known for its strong generalization across diverse applicatio
arXiv:2504.02169v3 Announce Type: replace-cross Abstract: We study the geometry of Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves in binary classification problems. The key f
arXiv:2501.17518v3 Announce Type: replace-cross Abstract: Hierarchical data is common in many domains like life sciences and e-commerce, and its embeddings often play a critical role. While hyperbolic