Knowledge catalogue
arXiv:2609.18566v1 Announce Type: cross Abstract: We present a physics-informed machine learning framework based on Neural Ordinary Differential Equations that solves the holographic inverse problem:
arXiv:2609.17759v1 Announce Type: cross Abstract: Muon updates matrix-valued neural-network parameters by orthogonalizing a gradient-based momentum matrix. Its reliance on derivatives limits its use w
arXiv:2506.00214v2 Announce Type: replace-cross Abstract: Rapid urbanization demands efficient monitoring of turbulent wind and pollutant dispersion, yet existing reconstruction and sensor placement s
arXiv:2609.18461v1 Announce Type: new Abstract: Personalized agents are required to reason over long-term history interactions to infer both explicit preferences and implicit behavioral evidence. Whil
arXiv:2609.18470v1 Announce Type: cross Abstract: Video-based Multimodal sentiment analysis (MSA) must handle information from text, audio, and image sequence in human speaking videos, yet current met
arXiv:2609.17883v1 Announce Type: cross Abstract: The rapid adoption of generative AI has made final artifacts unreliable evidence of student learning, and AI detectors that examine only the finished
arXiv:2407.06868v3 Announce Type: replace-cross Abstract: In this work, we propose a method for efficient resource utilization of simultaneously transmitting and reflecting reconfigurable intelligent
arXiv:2609.17766v1 Announce Type: new Abstract: Radar-based navigation is appealing for its robustness to adverse conditions involving airborne particles, such as precipitation, dust, fog, and smoke,
arXiv:2609.17655v1 Announce Type: cross Abstract: In an important recent work, Blanc (2026) gave an algorithm for robustly learning Boolean concept classes with respect to a fixed distribution that ou
arXiv:2609.19080v1 Announce Type: new Abstract: As robot capabilities increase, quadratic programming (QP)-based controllers must account for a similarly increasing number of constraints to ensure saf
arXiv:2609.17981v1 Announce Type: cross Abstract: Speech Large Language Models (Speech-LLMs), typically built from a pre-trained speech encoder, a modality projector, and an LLM fine-tuned with Low-Ra
arXiv:2609.17532v1 Announce Type: new Abstract: Invasive mechanical ventilation is a lifesaving therapy, but timely, safe discontinuation is essential to preventing extubation failure (EF) and related
arXiv:2603.02948v2 Announce Type: replace-cross Abstract: Physics-Informed Neural Networks (PINNs) incorporate physics into neural networks by embedding partial differential equations (PDEs) into thei
arXiv:2609.18381v1 Announce Type: new Abstract: Despite their high accuracy on point-wise metrics, machine learning weather forecasting models can exhibit different failure modes such as blurring, per
arXiv:2609.18852v1 Announce Type: new Abstract: Longitudinal electronic health records (EHRs) capture years of patient history across notes, codes, labs, and procedures, and contain evidence needed to
arXiv:2609.18256v1 Announce Type: new Abstract: Reliability under sparse and heterogeneous failures remains a fundamental challenge for medical image segmentation. High average accuracy can conceal a
arXiv:2609.18047v1 Announce Type: new Abstract: We characterize when compressed vector representations admit exact linear or affine readouts of a finite lexicon's truth conditions: one fixed map per p
arXiv:2609.18901v1 Announce Type: cross Abstract: In physics-informed machine learning, a target function u^* is learned from noisy value observations y_i=u^*(x_i)+ arepsilon_i, together with differen
arXiv:2609.18089v1 Announce Type: new Abstract: Vehicular federated learning (VFL) enables privacy-preserving collaborative model training for intelligent transportation systems, where communication r
arXiv:2601.13874v3 Announce Type: replace-cross Abstract: Accurately and efficiently estimating the variance of the Maximum Mean Discrepancy (MMD) remains challenging, particularly for unbalanced samp
arXiv:2607.17542v2 Announce Type: replace Abstract: Accurately steering a robot to a target configuration is fundamental in engineering, yet remains challenging for nonholonomic mobile robots. Vector
arXiv:2609.18983v1 Announce Type: cross Abstract: Adaptive loop filter (ALF) for video coding, which is designed to minimize the mean square error between original and reconstructed samples by using W
arXiv:2609.18989v1 Announce Type: new Abstract: How many dimensions does a language model's computation actually use? The question is ill-posed until one names a functional. Task-weighted charts make
arXiv:2609.18011v1 Announce Type: new Abstract: In collaborative tasks with asymmetric information, participants coordinate their understanding through interaction. We ask whether gaze provides eviden
arXiv:2609.18688v1 Announce Type: cross Abstract: AI models for multimodal medical imaging must balance modality-specific specialization with cross-modal shared representations, a trade-off that pure
arXiv:2507.05952v2 Announce Type: replace Abstract: Neural implicit representations have recently achieved impressive results in novel view synthesis and multi-view 3D reconstruction, yet both NeRF- a
arXiv:2305.16901v5 Announce Type: replace Abstract: One of the primary reasons behind the success of neural networks has been the emergence of an array of new, highly-successful optimizers, perhaps mo
arXiv:2609.17578v1 Announce Type: cross Abstract: Let a_1,ldots,a_m be distinct elements of a field K, and let Z(X)=prod_{i=1}^m (X-a_i). We study the arithmetic complexity of computing the unique nor
arXiv:2609.18634v1 Announce Type: cross Abstract: Video streaming dominates global internet traffic, yet conventional pipelines remain inefficient for structured, human-centric content such as sports,
arXiv:2609.18465v1 Announce Type: new Abstract: Feed-forward 3D foundation models such as VGGT predict cameras, depth, and point maps in a single pass, but can fail silently under low overlap, low par
arXiv:2609.18050v1 Announce Type: new Abstract: How do elephant trunks generate complex postures without relying solely on fine segmental activation? We propose that part of this complexity arises fro
arXiv:2609.18856v1 Announce Type: cross Abstract: Compact acoustic models face a challenging quality-capacity trade-off. We investigate two factors in this regime: encoder context and Mel-spectrogram
arXiv:2609.19107v1 Announce Type: new Abstract: Scaling laws predict how loss decreases with increases in computation. We show, contrary to conventional wisdom, that architectural interventions can mo
arXiv:2609.17540v1 Announce Type: new Abstract: We propose a framework that transfers tacit human subjective criteria to robotic systems for the appropriate grasping of deformable objects. Achieving s
arXiv:2609.17841v1 Announce Type: new Abstract: We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using
arXiv:2609.18481v1 Announce Type: new Abstract: Biomedical knowledge graphs combine ontology-derived hierarchies with transversal associations among heterogeneous entities such as phenotypes, diseases
arXiv:2609.17568v1 Announce Type: cross Abstract: Additive-congestion constraints in single-source unsplittable flow can enforce stable-set structure. This note isolates and generalises that mechanism
arXiv:2609.19012v1 Announce Type: new Abstract: We present a trajectory planning method that balances information collection and control effort to improve cislunar spacecraft-to-spacecraft absolute tr
arXiv:2609.17777v1 Announce Type: cross Abstract: AI and large language models can recover clinically meaningful features from electronic health records (EHRs), but predictive usefulness does not esta
arXiv:2609.18980v1 Announce Type: cross Abstract: This paper studies instrument classification of solo sheet music. Whereas previous work has focused on instrument recognition in audio data, we instea
arXiv:2609.19048v1 Announce Type: new Abstract: In the context of differentiated on-demand goods delivery services, this study proposes an integrated optimization method for automated guided vehicles
arXiv:2609.18825v1 Announce Type: new Abstract: Background: Molecular testing for NPM1 and FLT3-ITD mutations guides critical early treatment decisions in acute myeloid leukemia (AML), but results can
arXiv:2609.18555v1 Announce Type: cross Abstract: Wildfire spread is traditionally predicted using physics-based simulators, which are physically interpretable but whose cost increases with each addit
arXiv:2609.17762v1 Announce Type: cross Abstract: According to Christian tradition, Luke is credited with authoring a Gospel and the Acts of the Apostles, even if his name does not appear in either bo
arXiv:2609.17747v1 Announce Type: new Abstract: This study explores the vocabulary richness of oral political communication. A model explaining the lexicon growth is proposed by subdividing the whole
arXiv:2609.18971v1 Announce Type: new Abstract: Surgical phase recognition maps each video frame to a clinically meaningful workflow phase, supporting context-aware assistance, documentation, and post
arXiv:2609.18490v1 Announce Type: new Abstract: 'What I cannot create, I do not understand.'Human wisdom reveals that creation is one of the highest forms of learning. For example, Diffusion Models ha
arXiv:2609.18894v1 Announce Type: cross Abstract: Constructing Lyapunov functions for nonlinear dynamical systems is a central problem in stability analysis, yet remains challenging. Lyapunov function
arXiv:2609.17838v1 Announce Type: cross Abstract: Low-energy nuclear structure is encoded in a broad body of experimental information across the chart of nuclides. Learning how this information is org
arXiv:2604.08336v2 Announce Type: replace Abstract: Catastrophic forgetting remains a key challenge in Continual Learning (CL). In replay-based CL with severe memory constraints, performance criticall
arXiv:2006.12694v2 Announce Type: replace-cross Abstract: Transfer learning involves taking information and insight from one problem domain and applying it to a new problem domain. Although widely use
arXiv:2609.18991v1 Announce Type: new Abstract: Multimodal LLMs report strong performance on scientific reasoning benchmarks, yet most treat perception and reasoning as a single measurable process. We
arXiv:2609.19039v1 Announce Type: cross Abstract: We introduce the Long-Short-Range Neural Network (LSR-Net), a novel neural operator architecture designed for data-driven forward evolution modeling,
arXiv:2609.18165v1 Announce Type: new Abstract: A low-impedance robot finger reports through joint torque how strongly it is loaded, but the same torque can arise from a small force near the fingertip
arXiv:2609.18669v1 Announce Type: new Abstract: Multi-Modal Motion Planning (M^3P) requires joint reasoning over continuous motions and discrete mode transitions, making it difficult to solve efficien
arXiv:2609.18284v1 Announce Type: new Abstract: In recent years, three initiatives have emerged to develop generative language models in Hungary. The motivation behind them is the same. For Hungarian,
arXiv:2609.17602v1 Announce Type: new Abstract: Computational text-based ideal point estimation (CT-IPE) methods are usually compared as named algorithms, yet applying them involves numerous researche
arXiv:2609.18088v1 Announce Type: cross Abstract: Detection-free methods for image-to-point cloud registration are prone to erroneous correspondences caused by domain and modality discrepancies, limit
arXiv:2609.17973v1 Announce Type: cross Abstract: We introduce a new single-loop algorithmic framework for smooth nonconvex--concave minimax optimization. The resulting projected damped extragradient
arXiv:2609.17951v1 Announce Type: new Abstract: We study the maximum strong independent set problem in a finite hypergraph: find the largest vertex set that intersects every hyperedge in at most one v