Knowledge catalogue
arXiv:2608.16142v1 Announce Type: cross Abstract: UAV on-board vision systems are widely used for different activities, including monitoring in no-fly zones. In this case, the vision-equipped UAV stre
arXiv:2608.15056v1 Announce Type: new Abstract: Multimodal retrieval-augmented generation (RAG) systems often rely on long unstructured contexts or aggressively expanded evidence graphs, which can int
arXiv:2608.16029v1 Announce Type: new Abstract: Group Independent Component Analysis (gICA) is widely used to decompose high-dimensional functional MRI data into interpretable brain networks. However,
arXiv:2608.16712v1 Announce Type: new Abstract: Underactuated tendon-driven hands offer compact actuation and passive compliance, but tendon elongation under restoring-spring loading introduces config
arXiv:2608.16353v1 Announce Type: cross Abstract: Even well-aligned large language models confidently generate factually incorrect text, making hallucination a persistent reliability risk in high-stak
arXiv:2608.14709v1 Announce Type: cross Abstract: This demo presents real-time AI-based uplink channel-estimation inference using data collected from a hardware-in-the-loop 5G platform. The data-colle
arXiv:2608.16485v1 Announce Type: new Abstract: Boundary representation (B-Rep) generation is a fundamental task in computer-aided design, yet the direct synthesis of high-fidelity and structurally va
arXiv:2608.15466v1 Announce Type: new Abstract: Distributional changes can be invisible to means and covariances yet appear in skewness, asymmetric interactions, or other third-order structure. We dev
arXiv:2511.23043v2 Announce Type: replace-cross Abstract: We present a probabilistic data-driven weather model providing ensembles of high spatial resolution realizations of 87 variables at arbitrary
arXiv:2608.15420v1 Announce Type: new Abstract: Relocalising archival photographs within a contemporary scene model is challenging because historic and modern views can differ in photographic appearan
arXiv:2608.16628v1 Announce Type: new Abstract: Modern Multimodal Retrieval-Augmented Generation (M-RAG) systems are fundamentally limited by the binary connectivity paradigm of traditional simple gra
arXiv:2604.03904v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often produce confident but incorrect answers, in part because standard evaluation incentives reward guessing ove
arXiv:2608.15298v1 Announce Type: new Abstract: A spatial-local image-denoising filter is proposed, and its performance metrics are evaluated in comparison with baseline filtering algorithms, includin
arXiv:2608.15400v1 Announce Type: new Abstract: Large Language Models (LLMs) are notorious for struggling with assessing their own uncertainty, detecting knowledge conflicts, or recognizing when probl
arXiv:2608.16492v1 Announce Type: cross Abstract: This paper studies the regret analysis for parallel Gaussian process (GP) bandit optimization. The known regret upper bounds for the widely used GP ba
arXiv:2608.16884v1 Announce Type: cross Abstract: The current best bounds on the matrix multiplication exponent omega are obtained through a refinement of the laser method called combination loss anal
arXiv:2608.14663v1 Announce Type: new Abstract: As global populations age, enhancing neighborhood walkability through inclusive urban design is important for mitigating built environment (BE) barriers
arXiv:2601.10267v2 Announce Type: replace Abstract: Separate Source-Channel Coding (SSCC) remains attractive for text transmission due to its modularity and compatibility with mature entropy coders an
arXiv:2608.15626v1 Announce Type: new Abstract: Optical coherence tomography angiography (OCTA) images retinal blood flow, giving capillary-perfusion and foveal-avascular-zone biomarkers that grade di
arXiv:2608.14749v1 Announce Type: cross Abstract: Background and Objective: Image-guided surgical navigation has been actively studied because of its advantage of identifying subsurface targets and cr
arXiv:2608.14678v1 Announce Type: cross Abstract: With the progress of the semiconductor industry toward increasingly complex compute devices and tighter process tolerances, advanced process control h
arXiv:2608.15689v1 Announce Type: cross Abstract: This study presents a hybrid epidemiological and behavioural framework to simulate the spread of health misinformation on social media. We extend the
arXiv:2608.15755v1 Announce Type: new Abstract: User-centric multi-turn agents must act on an evolving task situation shaped by changing user intents, accumulated tool-grounded facts, missing informat
arXiv:2608.15412v1 Announce Type: cross Abstract: Encoder-based code representation models remain widely deployed for discriminative tasks such as clone detection and code classification, where their
arXiv:2608.14730v1 Announce Type: new Abstract: The rapid evolution of visual generative AI has introduced a wide range of intellectual property risks, spanning the unauthorized learning, reproduction
arXiv:2608.14803v1 Announce Type: new Abstract: A recent line of work recasts the post-memorization phase of grokking as constrained optimization: once a network interpolates the training set, weight
arXiv:2608.15910v1 Announce Type: cross Abstract: Expressive text-to-speech (TTS) systems that use explicit conditioning labels provide direct and interpretable control over expressive attributes, in
arXiv:2608.16424v1 Announce Type: new Abstract: Generative modeling has shown increasing promise for predicting cellular perturbation effects under chemical compound treatments. Existing approaches ei
arXiv:2603.06946v2 Announce Type: replace Abstract: Many distributional quantities in reinforcement learning are intrinsically joint across actions, including distributions of gaps and probabilities o
arXiv:2608.15395v1 Announce Type: new Abstract: Although text-to-image generative models produce impressive results, they struggle to generate densely detailed, high-resolution (HR) images. Current li
arXiv:2608.14757v1 Announce Type: cross Abstract: Whole slide image analysis is commonly formulated as multiple instance learning (MIL), where instance features are contextually updated and aggregated
arXiv:2608.15815v1 Announce Type: new Abstract: WiFi Channel State Information (CSI) has emerged as a privacy-preserving alternative to cameras for human pose estimation. However, existing approaches
arXiv:2608.14716v1 Announce Type: cross Abstract: Abrupt transitions in complex systems are often preceded by early warning signals. However, most indicators rely on the notion of critical slowing dow
arXiv:2608.15797v1 Announce Type: new Abstract: KV-cache eviction caps the memory cost of long reasoning traces but is inherently lossy because the model decodes from a partial view of its history. Un
arXiv:2608.15669v1 Announce Type: new Abstract: Scientific discovery often involves optimising expensive-to-evaluate objectives over vast, structured, and open-ended hypothesis spaces, such as molecul
arXiv:2608.15909v1 Announce Type: cross Abstract: Background: Planning multi-study analyses requires identifying cohorts with the relevant participants, phenotypes, and data modalities. This process c
arXiv:2608.15396v1 Announce Type: new Abstract: Battery energy storage systems (BESS) are increasingly used in distribution networks for voltage regulation and demand response, which increases the vol
arXiv:2608.15871v1 Announce Type: cross Abstract: Large language models (LLMs) trained on large-scale internet corpora encode extensive statistical regularities about social identities, attitudes, and
arXiv:2608.16507v1 Announce Type: new Abstract: Due to the limited amount of information, modeling longitudinal rare-disease data can benefit from integrating clinical knowledge. Yet, elicitation of e
arXiv:2608.15725v1 Announce Type: new Abstract: Predictive models in clinical and regulated settings must be accurate and fully auditable. Tree ensembles deliver strong accuracy on tabular data, but t
arXiv:2608.14556v1 Announce Type: new Abstract: Physical fields on meshes require a separation between topology and geometry: conservation laws are topological and should be exact, while geometry, mat
arXiv:2608.16569v1 Announce Type: new Abstract: Accurate reconstruction of long-duration neural recordings is challenging because local field potentials (LFPs) are high-resolution, multichannel, trans
arXiv:2608.16699v1 Announce Type: cross Abstract: Motivated by modern marketplaces, where the platform or the seller routinely gathers detailed user profiles, we study a novel learning theoretic model
arXiv:2608.15317v1 Announce Type: new Abstract: Scene coordinate regression (SCR) achieves strong performance in outdoor LiDAR localization, but it usually requires scene-specific training that can ta
arXiv:2507.09627v3 Announce Type: replace-cross Abstract: Next-generation wireless technologies such as 6G aim to meet demanding requirements such as ultra-high data rates, low latency, and enhanced c
arXiv:2608.15036v1 Announce Type: new Abstract: The Lipschitz bandit problem extends the traditional multi-armed bandit framework to continuous action spaces by assuming that the reward functions sati
arXiv:2608.14717v1 Announce Type: new Abstract: A query-relation deletion can improve the edited slot while reducing the utility of the prediction set that contains it. We study this tension in two re
arXiv:2608.15325v1 Announce Type: cross Abstract: We propose a new framework for machine-learning-oriented argument analysis tasks. Our proposal involves replacing traditional contextualized word embe
arXiv:2608.14578v1 Announce Type: new Abstract: Early identification of adolescent substance-use risk is an important prevention challenge, yet the relative value of baseline characteristics, longitud
arXiv:2608.15388v1 Announce Type: new Abstract: Topological deep learning (TDL) methods rely on lifting raw data into higher-order discrete domains such as simplicial complexes, cell complexes, and hy
arXiv:2608.14942v1 Announce Type: cross Abstract: This paper presents the first known empirical investigation of annotator and reviewer performance across multi-source remotely sensed imagery, evaluat
arXiv:2608.14847v1 Announce Type: new Abstract: Electroencephalogram (EEG) is a non-invasive and relatively low-cost procedure that measures brain electricity for the detection of cognitive diseases.
arXiv:2608.15760v1 Announce Type: cross Abstract: Decoding is an essential component of quantum error correction (QEC), translating stabilizer measurement outcomes into corrective actions that suppres
arXiv:2608.14783v1 Announce Type: new Abstract: Part-aware 3D object generation is essential for graphics applications such as controllable modeling, editing, and articulation, where objects are repre
arXiv:2608.15277v1 Announce Type: new Abstract: Greedy sampling produces a compact yet representative summary of normal data, which is essential for reliable anomaly detection that relies on measuring
arXiv:2608.15451v1 Announce Type: new Abstract: Large language models process large amounts of information but usually lack an explicit mechanism for maintaining compact and evolving conceptual repres
arXiv:2608.16709v1 Announce Type: cross Abstract: A radiologist reading a model's output faces two problems. The model returns a number and no reason, and any system that turns that number into readab
arXiv:2608.14772v1 Announce Type: new Abstract: Minimally invasive and robot-assisted surgery offer many advantages over traditional open surgery, but deprive surgeons of tactile feedback and the abil
arXiv:2511.10076v3 Announce Type: replace Abstract: Reliable long-horizon co-speech gesture generation requires precise motion representation and consistent structural priors across all joints. Existi
arXiv:2603.07977v3 Announce Type: replace-cross Abstract: Machine Learning Interatomic Potentials (MLIPs) enable accurate large-scale atomistic simulations, yet improving their expressive capacity eff