Knowledge catalogue
arXiv:2609.13292v1 Announce Type: cross Abstract: Medium-range weather forecasting underpins operational and planning decisions across the energy industry. Developing competitive weather models was on
arXiv:2609.15555v1 Announce Type: new Abstract: Bayesian optimisation (BO) typically relies on a single global Gaussian process (GP) model as its surrogate model. However, GP regression has cubic comp
arXiv:2609.13819v1 Announce Type: new Abstract: Solving inverse problems with differentiable physics simulators holds the potential to revolutionize scientific discovery and engineering design, as it
arXiv:2609.15072v1 Announce Type: cross Abstract: Methods of Branched Optimal Transport (BOT) mimic the economy and efficiency of natural tree-like structures, such as those found in rivers and biolog
arXiv:2609.13807v1 Announce Type: new Abstract: Large language models reason in high-dimensional hidden-state spaces, while users observe only final outputs. We introduce Bypass Observation, a non-int
arXiv:2609.14726v1 Announce Type: cross Abstract: Large language models are increasingly used to scale codebook-based annotation in scientific research, but existing workflows provide limited support
arXiv:2609.15484v1 Announce Type: new Abstract: We report on the continued development of CatchMonitor, resulting in a prototype computer vision system designed to automatically quantify discarded fis
arXiv:2609.13876v1 Announce Type: new Abstract: Personal robots should adapt their co-speech gesture style to a new user without requiring model retraining. We present a training-free personalization
arXiv:2609.13397v1 Announce Type: new Abstract: In rendering, a camera is a sampling operator that maps each finite pixel to a bundle of rays. Different camera models change the geometry of this bundl
arXiv:2609.15225v1 Announce Type: new Abstract: Objective: To develop an intelligent framework, termed CUA-Net, for the automated classification of congenital uterine anomalies (CUA) without requiring
arXiv:2609.14129v1 Announce Type: cross Abstract: Ultra-High-Definition (UHD) video presents significant challenges for efficient storage and real-time decoding. Learning-based methods, such as Neural
arXiv:2509.24975v4 Announce Type: replace-cross Abstract: Diffusion large language models (dLLMs) enable parallel generation and are promising for unit test generation (UTG), where efficient and large
arXiv:2609.14256v1 Announce Type: new Abstract: Topic models are widely used to analyze public health-related social media short texts, yet their evaluation remains dominated by metrics that focus ent
arXiv:2609.13533v1 Announce Type: cross Abstract: Most hyperparameter configurations for Evolvable-Substrate HyperNEAT (ES-HyperNEAT) produce networks that stagnate at random-guessing performance, was
arXiv:2609.13440v1 Announce Type: new Abstract: We give a deterministic algorithm for online inverse linear optimization with regret O(d), uniform in the horizon and O(d^{2}) time per round. A bound o
arXiv:2609.13636v1 Announce Type: cross Abstract: Privacy-preserving inference via Torus Fully Homomorphic Encryption (TFHE) provides strong protection for sensitive data in outsourced deep learning a
arXiv:2609.15759v1 Announce Type: new Abstract: Full-duplex speech-to-speech (S2S) models enable natural conversational AI by allowing simultaneous listening and speaking. However, these models typica
arXiv:2512.10159v3 Announce Type: replace-cross Abstract: LLMs have shown strong performance in data-rich domains such as programming, but their reliability in engineering tasks remains limited. Circu
arXiv:2609.14187v1 Announce Type: cross Abstract: Memory-efficient feature representations are increasingly important in machine learning settings where storage, transmission cost, bandwidth, or priva
arXiv:2609.14654v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) are typically evaluated using held-out classification accuracy, an approach that presupposes predictions are based
arXiv:2601.16427v3 Announce Type: replace-cross Abstract: We study exact community recovery in sparse directed stochastic block models using neighborhood smoothing of connection-probability profiles.
arXiv:2609.13816v1 Announce Type: cross Abstract: JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approach
arXiv:2609.13733v1 Announce Type: new Abstract: Stable and reliable 4D spatial understanding is fundamental for autonomous driving systems. While feedforward reconstruction networks can estimate camer
arXiv:2609.14896v1 Announce Type: cross Abstract: A notable byproduct of LLM alignment training is mode collapse: the progressive loss of output diversity that narrows a model's expressivity at infere
arXiv:2609.13535v1 Announce Type: new Abstract: The EU AI Act introduces mandatory requirements for high-risk AI systems with the explicit goal of ensuring the development and operation of trustworthy
arXiv:2609.14802v1 Announce Type: cross Abstract: Importance weights are essential in domain adaptation under label shift, yet their utility is often undermined by the finite sample uncertainty associ
arXiv:2412.05445v3 Announce Type: replace-cross Abstract: Online reviews help people make better decisions. Review platforms usually depend on typed input, where leaving a good review requires signifi
arXiv:2609.13282v1 Announce Type: new Abstract: Industrial anomaly localization has advanced rapidly with feature-based, reconstruction-based, and distillation-based methods. Most of these methods sco
arXiv:2609.13406v1 Announce Type: new Abstract: When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intellig
arXiv:2609.14534v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) aims at predicting at runtime and as early as possible the future states of a process execution. Common tasks includ
arXiv:2609.15195v1 Announce Type: new Abstract: Embodied navigation requires agents to interpret visual observations, accumulate spatial knowledge, and execute actions to follow instructions or locate
arXiv:2603.23803v2 Announce Type: replace-cross Abstract: In this paper, we present DROP, high-Density Relocation-free sequential OPerations in automated valet parking. DROP addresses the challenges i
arXiv:2609.15257v1 Announce Type: cross Abstract: We analyze a stochastic algorithm with Halpern anchoring for constrained convex-concave problems and monotone variational inequalities. This algorithm
arXiv:2609.15833v1 Announce Type: new Abstract: Cultural heritage documentation increasingly relies on image-based 3D surface reconstruction, with photogrammetry software making such workflows accessi
From running build tools, to data analysis pipelines, to collaborative research, executing data-driven tasks is essential for any enterprise agent. Today, platform teams often stitch together custom w
arXiv:2502.21279v2 Announce Type: replace-cross Abstract: Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradi
arXiv:2609.14567v1 Announce Type: cross Abstract: Reinforcement learning (RL) has shown considerable promise for robotic decision-making, yet deploying multi-agent RL (MARL) on physical multi-robot sy
arXiv:2609.14926v1 Announce Type: cross Abstract: We propose a linearized Physics-Informed Neural Network (lPINN), a reduced-order neural basis method for forward and inverse differential equations. I
arXiv:2609.13287v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) achieve high decoding efficiency through block-parallel, arbitrary-order generation, making them attractive fo
arXiv:2609.14374v1 Announce Type: cross Abstract: Dynamic trajectory prediction has become an important paradigm for data-driven transient stability analysis (TSA), yet most existing predictors remain
arXiv:2512.24565v4 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly serving as autonomous agents, and their utilization of external tools via the Model Context Protocol (
memory has been a hot topic for the past ~2 years every time we bring it up or do anything there, gets ton of interest, but nothing sticks few takes on why below: - how to update and then use memory n
arXiv:2506.04166v3 Announce Type: replace Abstract: Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretic
arXiv:2609.14906v1 Announce Type: cross Abstract: The Hohenberg-Kohn theorem establishes that, in principle, the ground state (GS) charge density contains all GS information of a many-electron system,
arXiv:2403.12187v2 Announce Type: replace-cross Abstract: Motivated by the abundance of functional data, such as time series and images, we study the approximation and statistical learning of nonlinea
arXiv:2609.13655v1 Announce Type: new Abstract: On evolving graphs, node classifiers must satisfy two key requirements: inductive generalization to newly arriving nodes under distribution shift and ca
arXiv:2609.14376v1 Announce Type: new Abstract: Soft robots are commonly sought for safety-critical interactions in delicate environments, where accurate position and orientation control is imperative
Italian cybersecurity startup Exein SpA today announced that it has raised 270 million at a valuation of 1.7 billion to build security for robots, vehicles and other machines that run artificial intel
arXiv:2609.15562v1 Announce Type: cross Abstract: As generative models continue to advance, AI-generated content (AIGC) is becoming increasingly realistic, weakening the artifact cues commonly exploit
arXiv:2609.15657v1 Announce Type: cross Abstract: Keyed watermark detection tests dependence between observed tokens and pseudorandom variables reconstructed from a secret key. Building on the pivotal
arXiv:2609.14533v1 Announce Type: cross Abstract: Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2]. It underpins a wide rang
arXiv:2609.15894v1 Announce Type: cross Abstract: Some of the sharpest challenges in sampling from the energy functions of physical systems arise at phase transitions, where the density of states chan
arXiv:2609.15022v1 Announce Type: new Abstract: Defense is a knowledge-intensive domain that requires precise understanding of specialized terminology, doctrinal concepts, operational procedures, and
arXiv:2502.20099v3 Announce Type: replace-cross Abstract: We evaluate methods for causal representation learning (CRL) on a simple, real-world system that satisfies the basic problem setup of CRL. The
arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why i
arXiv:2609.15598v1 Announce Type: cross Abstract: Generative recommendation has emerged as a promising end-to-end paradigm for personalized recommendation. However, user preferences continuously evolv
arXiv:2609.14121v1 Announce Type: new Abstract: The Semantic Web set out to give information a machine-interpretable form so that software could integrate and reason over it. Its standards became scie
arXiv:2609.14902v1 Announce Type: cross Abstract: Shapley value (SV)-based methods are the prevailing framework for feature attribution in machine learning, yet existing population-level Shapley estim
arXiv:2609.13648v1 Announce Type: new Abstract: Solar energy decision support is fragmented across dashboards that provide data without explanation, research papers are slow to parse, and general-purp
arXiv:2609.13277v1 Announce Type: new Abstract: Lunar orbital missions, such as Lunar Reconnaissance Orbiter, Kaguya/SELENE, Gravity Recovery and Interior Laboratory, and Lunar Prospector, among other