Knowledge catalogue
arXiv:2609.18228v1 Announce Type: new Abstract: Journal Entry Tests (JETs) are a mandatory part of annual audits to evaluate and assess both highrisk audit areas and potential material misstatements.
arXiv:2609.18320v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit hallucinations, presenting a major barrier to reliability in complex reasoning tasks. While traditional
arXiv:2609.18338v1 Announce Type: cross Abstract: Adaptive security at the network edge increasingly relies on automated planners, including rule-based controllers, learned policies, and LLM-assisted
arXiv:2609.17562v1 Announce Type: cross Abstract: Hybrid Spiking Neural Network (SNN)-Artificial Neural Network (ANN) architectures combine the energy efficiency of SNNs with the superior detection ac
arXiv:2406.13668v4 Announce Type: replace Abstract: A set of probabilistic forecasts is calibrated if each prediction of the forecaster closely approximates the empirical distribution of outcomes on t
arXiv:2609.18051v1 Announce Type: new Abstract: Fresh-market blueberries require selective, gentle picking, which is labor-intensive and expensive. Over-the-row machine harvesters are fast but non-sel
arXiv:2609.18736v1 Announce Type: new Abstract: Despite recent advances in large language models (LLMs), performing logically consistent deductive reasoning over extended interactions remains challeng
arXiv:2609.17921v1 Announce Type: new Abstract: Vision-language model (VLM) agents combine specialized perception, tools, and reasoning to address complex visual tasks. In multi-agent settings, differ
arXiv:2609.17697v1 Announce Type: new Abstract: Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining
arXiv:2609.18836v1 Announce Type: new Abstract: A surveillance system that detects an anomaly often has to repair the footage as well, yet the two tasks are studied in isolation: training-free anomaly
arXiv:2412.16555v4 Announce Type: replace Abstract: Large language models (LLMs) are widely applied in various fields of society due to their powerful reasoning, understanding, and generation capabili
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:2609.17981v1 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:2609.18900v1 Announce Type: new Abstract: Prototyping and evaluating human-robot teaming (HRT) scenarios in the real-world is costly. Virtual simulation of HRT scenarios has been adopted as an a
arXiv:2609.17786v1 Announce Type: new Abstract: Fairness-aware model compression requires selecting methods and configurations that balance accuracy, fairness, and deployment cost. These decisions bec
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: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:2609.18416v1 Announce Type: cross Abstract: Stochastic subspace methods have gained popularity as gradient descent based techniques for large scale optimisation problems, especially in distribut
arXiv:2609.18034v1 Announce Type: new Abstract: Novel view synthesis from unposed multi-view images remains challenging, as the model must jointly learn scene representations and camera parameters wit
arXiv:2412.07255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate remarkable capabilities in generative tasks but pose potential risks due to their tendency to generat
arXiv:2609.18127v1 Announce Type: new Abstract: Many real-world processes exhibit long-range dependence, where the current state depends on a slowly decaying trace of past states rather than on the mo
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:2609.18148v1 Announce Type: new Abstract: The remarkable success of large language models (LLMs) has provided important inspiration for the next generation of recommender systems. Structurally,
arXiv:2609.19062v1 Announce Type: new Abstract: Automatic sleep staging is fundamental to personal health monitoring, yet many existing approaches are ill-suited for real-world applications. Tradition
arXiv:2609.17888v1 Announce Type: cross Abstract: We study the problem of demonstration selection, which involves selecting a subset of examples for prepending to a query to a language model. This pro
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:2609.18716v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) match the event-driven nature of event cameras and naturally extract spatiotemporal features. These properties have motiv
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
arXiv:2502.14254v3 Announce Type: replace-cross Abstract: Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, en
arXiv:2609.18260v1 Announce Type: new Abstract: Recent advances in artificial intelligence and computer vision are reshaping sports performance analysis by enabling automated detection, tracking, and
arXiv:2609.17929v1 Announce Type: new Abstract: Accurate seafloor mapping is essential for marine science, archaeology, and environmental monitoring. However, integrating data from different sensors,
arXiv:2609.18007v1 Announce Type: cross Abstract: Text-to-image generative models are widely used in professional and creative settings, yet how they represent gender across occupations -- and whether
arXiv:2609.18084v1 Announce Type: cross Abstract: Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to ev
arXiv:2609.18031v1 Announce Type: new Abstract: Contact-rich physical human--robot interaction (pHRI) imposes time-varying demands associated with physical interaction, motor regulation, and physiolog
arXiv:2609.18588v1 Announce Type: new Abstract: For distribution system operators, short-term load forecasting (STLF) supports congestion management, voltage control, and asset protection. Most existi
arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, au
arXiv:2609.18056v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) has recently emerged as a pivotal research direction for adapting pre-trained point cloud transformers to diverse
arXiv:2609.17625v1 Announce Type: new Abstract: Runtime Verification is well suited to autonomous and robotic systems because it checks the behaviour that is actually observed during execution. Its ma
arXiv:2609.18535v1 Announce Type: new Abstract: Causal discovery aims to recover causal relationships from observed data. In various fields, exploring causal relationships among variables remains an i
arXiv:2609.18527v1 Announce Type: new Abstract: Structured prediction is the simultaneous prediction of multiple labels, and is widely used in various fields, such as natural language processing and c
arXiv:2509.16079v2 Announce Type: replace Abstract: Unsteady aerodynamic effects can have a profound impact on aerial vehicle flight performance, especially during agile maneuvers and in complex aerod
arXiv:2609.18844v1 Announce Type: new Abstract: Multimodal coding agents are expected to turn visual inputs into usable artifacts, and they act through a harness, the layer of tools, context managemen
arXiv:2609.18049v1 Announce Type: new Abstract: Model explainability is essential for understanding and trusting machine learning models. Existing explainable AI methods often explain predictions thro
arXiv:2609.19093v1 Announce Type: cross Abstract: Radiologists follow heterogeneous reporting practices. Two radiologists examining the same image and identifying the same clinical findings might neve
arXiv:2609.17555v1 Announce Type: cross Abstract: Efficient deployment of Deep Neural Networks (DNNs) on edge accelerators requires aggressive model compression while maintaining reliability in fault-
arXiv:2609.18656v1 Announce Type: new Abstract: Sign-based methods reduce communication costs in distributed environments, but aggregating local signs can introduce bias when data are heterogeneous. A
arXiv:2609.19104v1 Announce Type: cross Abstract: Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured sta
arXiv:2609.17545v1 Announce Type: new Abstract: Deep learning models for cervical cytology are almost always evaluated as if every prediction must be acted upon, yet a screening system deployed alongs
arXiv:2609.18493v1 Announce Type: new Abstract: Semantic labels for indoor mobile laser scanning (MLS) frames remain largely absent from current point cloud semantic segmentation benchmarks, which mai
arXiv:2607.14781v2 Announce Type: replace Abstract: The simultaneous arrival of multiple mobile robots at a target point is crucial for cooperation tasks such as cooperative encirclement, disaster rel
arXiv:2609.18929v1 Announce Type: cross Abstract: In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous re
arXiv:2609.18759v1 Announce Type: cross Abstract: Generating signals on graphs requires permutation-equivariant models that exhibit stability with respect to relative structural perturbations. While r
arXiv:2609.18133v1 Announce Type: new Abstract: Visible-infrared object detectors are used for robust perception under challenging illumination and weather conditions. Current physical attacks apply c
arXiv:2609.17808v1 Announce Type: cross Abstract: The increasing adoption of electric vehicles (EVs) is expected to place significant additional demand on residential distribution networks, creating a
arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp
arXiv:2512.24100v2 Announce Type: replace Abstract: Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language di
Today’s LLMs still write like typewriters: one token at a time. This sequential process creates a hard inference bottleneck. We're introducing Uno, a diffusion-augmented LLM that delivers autoregressi