Knowledge catalogue
arXiv:2608.00137v1 Announce Type: cross Abstract: Underwater image enhancement (UIE) aims to recover clear images from observations affected by wavelength-dependent absorption, scattering, and spatial
arXiv:2607.28971v1 Announce Type: cross Abstract: Contrastive learning is widely used for user modeling in large-scale recommender systems, where standard in-batch negatives implicitly assume universa
arXiv:2607.29596v1 Announce Type: cross Abstract: Vision-language-action models (VLAs), which leverage the cognition of multimodal information to infer physical-world actions, provide a generalized so
arXiv:2601.07048v5 Announce Type: replace-cross Abstract: Approximate nearest neighbor search (ANNS) is a core problem in machine learning and information retrieval applications. GPUs offer a promisin
arXiv:2607.28855v1 Announce Type: cross Abstract: Dense 3D sensors in various real-world fields produce point clouds that are geometrically redundant for real-time processing. In this paper, we propos
arXiv:2507.05113v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) are susceptible to backdoor attacks, where adversaries poison training data to implant backdoor into the victim mo
arXiv:2607.27635v1 Announce Type: cross Abstract: Wearable sensors continuously capture fine-grained multivariate time-series data, providing opportunities to model behavioural patterns associated wit
arXiv:2607.28442v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled new possibilities for 3D question answering (3D-QA), a ke
As the benchmarks that test frontier AI on get more complex, we are losing one of the most important aspects of benchmarking: comparisons to humans Validated benchmarks need to have human (ideally mul
arXiv:2310.19043v3 Announce Type: replace-cross Abstract: Recent years have witnessed growing concerns about the privacy of sensitive data. In response to these concerns, differential privacy has emer
arXiv:2607.26909v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to infer missing facts in knowledge graphs (KGs), thereby improving their completeness and supporting downstream i
arXiv:2607.26780v1 Announce Type: new Abstract: The ability of large language models (LLMs) to process and generate text has introduced potential for applications in information extraction (IE). While
arXiv:2607.26473v1 Announce Type: cross Abstract: Personalizing large language models (LLMs) to individual users is essential for improving user experience, yet existing approaches typically rely on e
arXiv:2607.26485v1 Announce Type: cross Abstract: Resource allocation across multiple agent groups arises in many applications including e-commerce recommendation systems, housing assignment, and cour
arXiv:2607.26108v1 Announce Type: cross Abstract: Realistic animal motion for virtual production is typically obtained either through motion capture of highly trained performers who accurately mimic a
arXiv:2607.24790v1 Announce Type: new Abstract: Low-Earth orbit (LEO) satellite Internet has become an important infrastructure for enabling ubiquitous connectivity to align with the International Tel
arXiv:2511.03443v2 Announce Type: replace-cross Abstract: In this paper, we investigate optimization problems with nonnegative and orthogonal constraints, where any feasible matrix of size n imes p ex
arXiv:2607.25371v1 Announce Type: new Abstract: Hyperspectral intrinsic decomposition (HID) aims to disentangle material-related spectral properties and photometric effects in hyperspectral images (HS
arXiv:2607.23867v1 Announce Type: new Abstract: Trajectory tracking performance of Uncrewed Aerial Vehicles (UAVs) degrades during high-speed and agile flight due to the depletion of the battery and s
arXiv:2510.23942v2 Announce Type: replace Abstract: We describe a theory and implementation of an intuitionistic decentralized framework for causal discovery using judo calculus, which is formally def
arXiv:2602.10381v2 Announce Type: replace Abstract: Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches ar
arXiv:2607.23446v1 Announce Type: cross Abstract: A small language model can receive the governing statutory provision and still answer incorrectly. We test whether fine-tuning on examples containing
arXiv:2607.23710v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into software development workflows, yet their ability to autonomously generate secure authen
arXiv:2512.13219v2 Announce Type: replace Abstract: This paper presents PyCAALP (Python-based Computer-Aided Assembly Line Planning), a framework for automated Assembly Sequence Planning (ASP) and Pro
arXiv:2512.06143v2 Announce Type: replace Abstract: Despite a large corpus of recent work on scaling up Gaussian processes, a stubborn trade-off between computational speed, prediction and uncertainty
arXiv:2607.21843v1 Announce Type: cross Abstract: Empirical Bayes (EB) performs simultaneous inference across many related latent variables. Classical EB assumes that the likelihood p(x | z) is tracta
arXiv:2606.20295v2 Announce Type: replace-cross Abstract: Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large mode
arXiv:2607.20493v1 Announce Type: new Abstract: Deep learning has led to remarkable progress in artificial intelligence, particularly in robotics, imaging and sound processing. However, a major limita
arXiv:2607.21184v1 Announce Type: new Abstract: Inductive Logic Programming (ILP) originated within the Logic Programming community in the Nineties as a framework for combining symbolic learning with
arXiv:2607.20521v1 Announce Type: new Abstract: The state of a dynamic system evolves over time, switching among several latent modes that govern its observable behavior. Filtering methods infer the l
arXiv:2607.20542v1 Announce Type: cross Abstract: A critical challenge in healthcare systems in low- and middle-income countries (LMICs) is the efficient and equitable allocation of scarce resources,
arXiv:2607.19430v1 Announce Type: cross Abstract: Multi-agent LLM applications chain a planner, worker agents, a verifier, and a synthesizer, and every hop between agents is an unmonitored channel thr
arXiv:2504.03707v2 Announce Type: replace-cross Abstract: Emotion recognition is crucial for advancing mental health, healthcare, and technologies such as brain-computer interfaces. EEG-based models,
arXiv:2607.14131v2 Announce Type: replace Abstract: Cross-dataset generalisation is a fundamental requirement for deploying text classifiers in real-world settings, yet systematic evaluation across co
As adversarial AI threats accelerate attacks on code, security teams must counter them with machine-speed defenses that can automate code remediation and fight AI with AI. CodeMender is our managed co
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,
arXiv:2505.09433v3 Announce Type: replace Abstract: Reflectance attributes in LiDAR point clouds provide essential information for downstream tasks but remain underexplored in neural compression metho
arXiv:2607.13669v1 Announce Type: new Abstract: Multimodal speaker identification systems typically assume the availability of complete and homogeneous audio-visual modalities during both training and
arXiv:2607.13499v1 Announce Type: new Abstract: 3D anomaly detection has recently emerged as an important research topic in computer vision. Although existing methods have achieved high performance, e
arXiv:2408.10581v3 Announce Type: replace Abstract: This work introduces a novel and generalizable multi-view Hand Mesh Reconstruction (HMR) model, named POEM, designed for practical use in real-world
arXiv:2607.13174v1 Announce Type: cross Abstract: Multimaterial 3D printing enables the fabrication of functionally graded components, but optimizing their spatial material distribution alongside stru
arXiv:2607.12634v1 Announce Type: new Abstract: This paper proposes a theoretical framework for understanding intelligence as a process of atomic compression and compositional reuse. We argue that cog
Creatio Inc. today introduced what it calls a major update to its customer relationship management and workflow platform that enables business users and information technology teams to build, deploy a
arXiv:2607.11464v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) addresses the limitations of Large Language Models (LLMs) when providing responses to domain-specific questions.
arXiv:2607.12627v1 Announce Type: new Abstract: We propose an architecture for learning the dynamics of mechanical systems based on discrete forced Euler-Lagrange equations on Lie groups using only po
arXiv:2607.12130v1 Announce Type: new Abstract: Spacecraft attitude control is traditionally achieved using momentum exchange devices or propellant-consuming thrusters. Meanwhile, a growing number of
arXiv:2607.12246v1 Announce Type: new Abstract: Personalization in two-sided marketplaces relies heavily on user-level features, yet for platforms with infrequent, high-consideration purchases, a larg
arXiv:2503.21204v3 Announce Type: replace Abstract: Rigid link flapping mechanisms remain the most practical choice for flapping wing micro-aerial vehicles (MAVs) to carry useful payloads and onboard
arXiv:2607.08595v1 Announce Type: new Abstract: Cardiovascular disease risk prediction models often rely on data from a single institution or centrally pooled datasets. Extending these models across i
arXiv:2503.08394v5 Announce Type: replace-cross Abstract: Multi-task optimization is typically characterized by a fixed and finite set of tasks. The present paper relaxes this condition by considering
arXiv:2606.21887v2 Announce Type: replace-cross Abstract: During hot tests on a production line, engine-sound analysis is crucial to ensuring product quality and performance. However, background noise
arXiv:2607.08003v1 Announce Type: cross Abstract: Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error
arXiv:2607.06766v1 Announce Type: cross Abstract: At Amazon Prime Video, we face the critical operational challenge of managing code deployments during live events and rapid feature releases without c
arXiv:2607.07083v1 Announce Type: cross Abstract: Subsampling significantly reduces the number of measurements, thereby streamlining data processing and transfer overhead, and shortening acquisition t
Cybersecurity startup QIZ Security Ltd. today announced it has raised 17 million in seed funding to expand a platform that discovers and governs the encryption buried across enterprise systems ahead o
Here’s a question we hear often at Google Cloud: How do you safely run AI-generated code or untrusted binaries without putting your host application, data, and cloud credentials at risk? In other word
arXiv:2607.07008v1 Announce Type: cross Abstract: A common method for the representation and analysis of time-series data is the hidden Markov model (HMM), where each observation is associated with a
Grok 4.5 is a new Opus-class AI model released by xAI that offers improved speed and cost efficiency compared to previous versions. The model is positioned as particularly well-suited for real-world c
Introducing VultronRetriever, a family of open visual document retrieval models built on Vultr. Achieve state-of-the-art retrieval performance with smaller indexes, higher throughput, and support for
A comprehensive evaluation of over 30 frontier embodied AI models reveals that current generalist robot policies lack the robustness needed for reliable real-world manipulation tasks. The analysis dem