Knowledge catalogue
arXiv:2608.03666v1 Announce Type: new Abstract: Self-supervised monocular depth estimation has emerged as an appealing solution to design lightweight and effective models for deployment on computation
arXiv:2608.02322v1 Announce Type: new Abstract: Accurate and efficient reconstruction of cloud-contaminated and noise-corrupted NDVI time series remains a challenge in remote sensing. Deep learning pr
In the Medium blog post, 'From MARS to SETOF REFCURSOR: Migrating Multi-Result Stored Procedures to PostgreSQL,' we explored the fundamental architectural differences between SQL Server and PostgreSQL
As artificial intelligence applications become ever hungrier for faster access to data, Nvidia Corp. today announced it is open-sourcing the application programming interface for its powerful cuFile v
arXiv:2606.18997v2 Announce Type: replace Abstract: Uncovering the true informational architecture of real-world complex systems requires disentangling how their components uniquely store, redundantly
arXiv:2607.27598v1 Announce Type: cross Abstract: Hasse clustering is an algorithm that extracts common patterns in sequential data and represents them in graphical forms. As the number of expected cl
Written by: Kelli Vanderlee, Stuart Carrera For years, the cybersecurity industry's understanding of software supply chain compromise has been anchored by a few watershed events, including Russian cyb
arXiv:2607.25681v1 Announce Type: new Abstract: Cognitive distortion amplifies negative emotions and contributes to mental health disorders. Cognitive Behavioral Therapy (CBT) is an effective way to a
arXiv:2607.21848v1 Announce Type: new Abstract: Recent conditional video generation models have shown promising potentials to transform 3D engine renderings, such as depth maps and untextured geometry
arXiv:2601.12349v3 Announce Type: replace-cross Abstract: Large multimodal model powered GUI agents are emerging as high-privilege operators on mobile platforms, entrusted to perceive screen content a
arXiv:2607.06291v1 Announce Type: new Abstract: Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and e
arXiv:2211.15590v2 Announce Type: replace Abstract: Analyzing the behavior of complex interdependent networks requires complete information about the network topology and the interdependent links acro
arXiv:2507.08905v2 Announce Type: replace-cross Abstract: We explore the use of Hamiltonian Monte Carlo (HMC) sampling as a probabilistic last layer approach for deep neural networks (DNNs). While HMC
arXiv:2607.03046v1 Announce Type: new Abstract: Establishing correspondence between projector and camera images in a procam (projector + camera) system is essential for achieving high-resolution pixel
arXiv:2410.00296v2 Announce Type: replace Abstract: Vision-language Models (VLMs) are essential for contextual understanding of both visual and textual information. However, their vulnerability to adv
arXiv:2510.20441v2 Announce Type: replace-cross Abstract: Neural audio codecs have largely promoted the application of language models (LMs) for speech applications. However, the effectiveness of auto
arXiv:2603.13859v2 Announce Type: replace Abstract: Intrinsic image decomposition aims to estimate physically based rendering (PBR) parameters such as albedo, roughness, and metallicity from images. W
arXiv:2606.28674v1 Announce Type: cross Abstract: Generative models in finance face the dual challenge of producing realistic data while satisfying strict regulatory and economic objectives, a require
arXiv:2406.07147v3 Announce Type: replace-cross Abstract: This study employs cutting-edge wearable monitoring technology to conduct high-precision, high-temporal-resolution (1-second interval) cogniti
arXiv:2606.24901v1 Announce Type: new Abstract: Continual learning capability is critical for Industrial LLMs, as deployed models must be continuously updated to meet evolving requirements and environ
arXiv:2503.13505v3 Announce Type: replace-cross Abstract: Generative Pretrained Transformers (GPTs) are foundational Large Language Models (LLMs) for text generation. However, individual LLMs often pr
arXiv:2509.24118v2 Announce Type: replace Abstract: Electronic health Records (EHRs) have become a cornerstone in modern-day healthcare. They are a crucial part for analyzing the progression of patien
arXiv:2606.22519v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) allows computations to be performed directly on encrypted data without decryption, offering strong privacy guarante
arXiv:2606.21386v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) achieve state-of-the-art performance on many robotic manipulation tasks, yet they can still behave unpredictably
arXiv:2606.10023v1 Announce Type: cross Abstract: Accurate posterior estimation is central to scientific inference, as uncertainties determine what can be reliably learned from observational data. Whi
arXiv:2407.05886v3 Announce Type: replace Abstract: Continuum and soft robots can transform automation tasks requiring compliant interaction in constrained or unstructured environments, including heal
Gary Marcus discusses a paradox in the agentic AI market: while developers are creating numerous new applications powered by agentic AI systems, these applications are failing to achieve meaningful us
arXiv:2606.01362v1 Announce Type: cross Abstract: Video generative models have achieved remarkable progress in synthesizing photorealistic video sequences. However, enabling broader and more creative
arXiv:2510.03745v2 Announce Type: replace Abstract: Low-discrepancy points are designed to efficiently fill the space in a uniform manner. This uniformity is highly advantageous in many problems in sc
arXiv:2307.04722v2 Announce Type: replace Abstract: Meta-learning empowers learning systems with the ability to acquire knowledge from multiple tasks, enabling faster adaptation and generalization to
arXiv:2605.31434v1 Announce Type: new Abstract: Robot-Assisted Minimally Invasive Surgery (RAMIS) enhances surgeon dexterity, with newer platforms leveraging haptic feedback to further improve perform
arXiv:2605.29939v1 Announce Type: cross Abstract: Integrated sensing, communication, and computation (ISCC) provides a promising framework for indoor human-centric applications. In these applications,
A developer created an open-source GUI application with a brutalist design for interacting with Ollama models and the Personal Iris (PI) platform. The application is compatible with both ARM64 and Int
This post from Replit outlines a 4-step security framework for protecting vibecoded applications in production environments. It emphasizes that application speed must not come at the expense of securi
arXiv:2605.27920v1 Announce Type: new Abstract: Driven by the wave of large language models, Video-Language Models (VLMs) have become a significant yet challenging technology to bridge the gap between
arXiv:2605.28711v1 Announce Type: new Abstract: The distortion-perception (D-P) tradeoff is a fundamental phenomenon of Bayesian inverse problems, which characterizes the inherent tension between dist
arXiv:2205.14090v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) has well-documented merits for optimizing black-box functions with an expensive evaluation cost. Such functions eme
arXiv:2605.24515v1 Announce Type: new Abstract: With climate change and increasing human pressure on natural landscapes, inland water resources are becoming progressively scarcer, more vulnerable, and
arXiv:2605.24411v1 Announce Type: new Abstract: Existing language model applications struggle to meet the demand for emotionally oriented support, primarily due to their inability to maintain deep, pe
arXiv:2605.23775v1 Announce Type: new Abstract: This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for mat
Ollama can be installed on Mac by downloading the application and placing it in the Applications folder, after which you use Terminal to run commands that download and launch models . The best model c
arXiv:2510.25348v2 Announce Type: replace Abstract: Information cascade popularity prediction is a key problem in analyzing content diffusion in social networks. However, current related works suffer
arXiv:2504.17548v2 Announce Type: replace-cross Abstract: Anomaly Detection (AD) defines the task of identifying observations or events that deviate from typical - or normal - patterns, a critical cap
arXiv:2605.16966v1 Announce Type: new Abstract: Solving inverse partial differential equation (PDE) problems is a fundamental topic in scientific research due to its broad significance across a wide r
arXiv:2605.14488v1 Announce Type: new Abstract: Large Language Models (LLMs) augmented with Retrieval-Augmented Generation (RAG) techniques are revolutionizing applications across multiple domains, su
arXiv:2605.13360v1 Announce Type: new Abstract: There is a growing demand for agentic AI technologies for a range of downstream applications like customer service and personal assistants. For applicat
arXiv:2605.13041v1 Announce Type: new Abstract: With recent advances in embodied agents and AR devices, egocentric observations are readily available as input for real-world interactive online applica
arXiv:2605.12668v1 Announce Type: cross Abstract: Conformal prediction provides a principled framework for uncertainty quantification with finite-sample coverage guarantees. While recent work has exte
arXiv:2511.16868v2 Announce Type: replace Abstract: The Gromov-Wasserstein (GW) distance serves as a powerful tool for matching objects in metric spaces. However, its traditional formulation is constr
arXiv:2512.03199v2 Announce Type: replace Abstract: Biometric facial recognition models often demonstrate significant decreases in accuracy when processing real-world images, often characterized by po
arXiv:2605.11526v1 Announce Type: cross Abstract: Training a deep neural network with the outputs of selected layers satisfying linear constraints is required in many contemporary data-driven applicat
Databases have introduced new AI-powered SQL functions which take natural language instructions as input and are evaluated using LLMs. They leverage the power of LLMs to answer new kinds of queries: W
arXiv:2605.08138v1 Announce Type: new Abstract: Synthetic data has emerged as a crucial solution to the data scarcity bottleneck in large language models (LLMs), particularly for specialized domains a
arXiv:2605.08971v1 Announce Type: cross Abstract: Computer-Aided Design is ubiquitous in todays world, as almost every manufactured object begins as a digital model across industries. At the same time
arXiv:2605.08093v1 Announce Type: cross Abstract: The use of chatbots for various forms of companionship is growing rapidly, raising a myriad of questions about simulated relationships, emotional depe
arXiv:2605.05121v1 Announce Type: new Abstract: Automated mental health prediction using textual data has shown promising results with deep learning and large language models. However, deploying these
arXiv:2512.22588v3 Announce Type: replace Abstract: One of the main limitations of multirotor UAVs is their short flight time due to battery constraints. A practical solution for continuous operation
arXiv:2507.13305v2 Announce Type: replace Abstract: Team modeling remains a fundamental challenge at the intersection of Artificial Intelligence and Social Sciences. Although a variety of computationa
arXiv:2605.02901v1 Announce Type: cross Abstract: This work aims to establish an end-to-end system for tracking of physical 3D objects for virtual reality (VR) applications. We focus on training appli
arXiv:2409.14500v5 Announce Type: replace Abstract: Although data that can be naturally represented as graphs is widespread in real-world applications across diverse industries, popular graph ML bench