Knowledge catalogue
arXiv:2505.13569v3 Announce Type: replace Abstract: The use of machine learning for modeling, understanding, and controlling large-scale physics systems is quickly gaining in popularity, with examples
arXiv:2609.12997v1 Announce Type: new Abstract: Single Ventricle Physiology (SVP) is a rare subtype of congenital heart disease characterized by the presence of a single functional cardiac ventricle w
arXiv:2609.12653v1 Announce Type: new Abstract: Russian state propaganda spreads across many languages and online spaces. Yet, most computational work examines only one such space, usually social medi
arXiv:2210.11003v3 Announce Type: replace-cross Abstract: We propose a generalization of the synthetic control methods to the setting with dynamic treatment effects, in which each unit receives multip
arXiv:2609.12353v1 Announce Type: new Abstract: Large language models trained recursively on their own or other models' outputs undergo model collapse, in which distributional tails and factual accura
arXiv:2609.13005v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance on a wide range of natural language tasks, and recent benchmarks suggest that they are inc
arXiv:2609.12531v1 Announce Type: new Abstract: In streaming tasks, recurrent models can carry latent computation across time, allowing each update to build on representations produced earlier. This r
arXiv:2504.04981v3 Announce Type: replace Abstract: This paper studies continual test-time adaptation (CTTA), the task of adapting a model to constantly changing unseen domains in testing while preser
arXiv:2609.11940v1 Announce Type: cross Abstract: The rapid diffusion of generative artificial intelligence raises privacy, latency, and performance concerns that motivate a shift toward 'local-first'
arXiv:2609.12111v1 Announce Type: new Abstract: Factual hallucination in closed-book question answering is often treated as a coverage problem: a model fails because the relevant fact is absent from i
arXiv:2609.12537v1 Announce Type: new Abstract: AI-assisted writing can flatten meaning in human storytelling, enabling the production of homogeneous outputs without the intentional effort and sense-m
arXiv:2609.12328v1 Announce Type: cross Abstract: This paper presents the iterative equivariant filter (IterEqF). The iterative extended Kalman filter (IterEKF) replaces the standard EKF correction st
arXiv:2609.12259v1 Announce Type: new Abstract: Matrix-valued memories make rank the natural budget of a learned representation: the number of independent directions a state spans bounds what it can b
arXiv:2603.02638v2 Announce Type: replace-cross Abstract: Machine learning for mobile network analysis, planning, and optimization is often limited by the lack of large, comprehensive real-world datas
arXiv:2609.12337v1 Announce Type: new Abstract: We study compute reduction in neural networks through a unified partial versus full computation view, captured by one-shot magnitude pruning in the stat
arXiv:2609.12590v1 Announce Type: cross Abstract: We investigate the stochastic-gradient query complexity of sampling smooth strongly log-concave distributions in any fixed Euclidean dimension. The po
arXiv:2609.13013v1 Announce Type: new Abstract: Flat roofs are among the most influential components of the building envelope, governing both structural performance and thermal efficiency, and thereby
arXiv:2609.12563v1 Announce Type: new Abstract: Neural audio codecs discretize speech into token sequences, but the resulting token spaces differ in vocabulary and codebook structure, preventing direc
arXiv:2609.12018v1 Announce Type: new Abstract: Railway engineers need simulation models that predict vehicle responses across operating scenarios that cannot be tested exhaustively. Agreement with re
arXiv:2609.11933v1 Announce Type: cross Abstract: Hydrogen supply chains are expected to play a central role in future low-carbon energy systems by enabling renewable energy integration, long-duration
arXiv:2609.12248v1 Announce Type: new Abstract: Dynamically feasible trajectory optimization for rigid-body systems is naturally formulated on the special Euclidean group SE(3) but is challenging when
arXiv:2603.08045v2 Announce Type: replace-cross Abstract: This paper presents a systematic framework for computing formally guaranteed trajectory tracking error bounds for autonomous helicopters based
arXiv:2609.13039v1 Announce Type: new Abstract: Transfer learning explores how to leverage knowledge from various tasks or domains (sources) to enhance predictive performance in related tasks or domai
arXiv:2603.07357v3 Announce Type: replace Abstract: Latent generative models have emerged as powerful priors for solving inverse problems. These models typically represent a class of natural signals a
arXiv:2609.12971v1 Announce Type: new Abstract: Robots are increasingly used in diverse application areas, where autonomous navigation plays a central role. As these systems become more widespread, im
arXiv:2609.13144v1 Announce Type: new Abstract: Compositional generalisation has been divided into lexical and structural generalisation. Previous work has found that structural generalisation is hard
arXiv:2609.12397v1 Announce Type: new Abstract: Multi-modal image generation, particularly subject-driven customization, has garnered growing attention in recent years. Despite the rapid advancement o
arXiv:2609.12095v1 Announce Type: new Abstract: Strategic flight plan validation in Advanced Air Mobility (AAM) environments requires robust methods for predicting aircraft state uncertainty and detec
arXiv:2609.12384v1 Announce Type: new Abstract: This work investigates the control strategies of complex whole-body robot teleoperation that coordinate active perception, bimanual manipulation, and na
arXiv:2609.13043v1 Announce Type: new Abstract: Robust medical image segmentation across imaging modalities is challenging because of large differences in appearance and intensity distributions. Model
arXiv:2601.04339v3 Announce Type: replace Abstract: Unified multimodal generation architectures that jointly produce text and images have recently emerged as a promising direction for text-to-image (T
arXiv:2512.08897v2 Announce Type: replace Abstract: Content-aware layout generation is a critical task in graphic design automation, focused on creating visually appealing arrangements of elements tha
arXiv:2609.12342v1 Announce Type: new Abstract: The conditional generation of 3D motion has emerged as a key research topic due to its wide applicability across robotics, AR/VR, gaming, and content cr
arXiv:2609.12898v1 Announce Type: new Abstract: Fine-grained robotic manipulation depends on understanding parts, not only whole objects. Existing 3D foundation models tend to be either generalized bu
arXiv:2609.11986v1 Announce Type: cross Abstract: Passive acoustic monitoring produces far more bat recordings than experts can label. We show that simple model-generated pseudo-labels turn this surpl
arXiv:2505.15063v3 Announce Type: replace Abstract: The rapid adoption of Large Language Models (LLMs) has raised important concerns about the factual reliability of their outputs, particularly in low
arXiv:2609.12168v1 Announce Type: new Abstract: Visual Question Answering (VQA) systems, jointly interpreting images and natural language queries, hold significant promise across many domains, yet the
arXiv:2609.12831v1 Announce Type: cross Abstract: As the number of autonomous robots continues to grow, safety becomes increasingly important. Control barrier functions (CBFs) provide a theoretically
arXiv:2609.12793v1 Announce Type: new Abstract: Stock price prediction remains challenging due to the non-stationary and noisy nature of financial time series. Existing deep learning models often rely
arXiv:2609.12853v1 Announce Type: cross Abstract: The widespread adoption of data-driven, energy-efficient model predictive control (MPC) in buildings remains hindered by substantial effort to collect
arXiv:2609.12874v1 Announce Type: new Abstract: Video tokenizers have emerged as a cornerstone of modern video modeling, underpinning progress in compression, reconstruction and generation by mapping
arXiv:2609.12343v1 Announce Type: new Abstract: Feed-forward Gaussian splatting models have demonstrated remarkable effectiveness in reconstructing three-dimensional (3D) objects from a few two-dimens
arXiv:2609.12875v1 Announce Type: new Abstract: Machine olfaction trains on pooled public descriptor corpora, but whether a shared descriptor word measures the same thing across corpora has not been t
arXiv:2609.12085v1 Announce Type: new Abstract: Checking Quran recitation from an ASR transcript requires distinguishing unresolved mistakes from repetitions, repairs, opening formulas and accepted sp
arXiv:2609.12663v1 Announce Type: cross Abstract: Audio-based Multimodal Large Language Models (MLLMs) can generate detailed natural-language descriptions of complex acoustic scenes, yet it remains un
arXiv:2609.12746v1 Announce Type: cross Abstract: Agentic pipelines for structured-query generation are rapidly expanding, but it is unclear which part of the loop produces the gain. We use LAST-CQ --
arXiv:2511.07318v3 Announce Type: replace Abstract: Despite substantial advances, large language models (LLMs) continue to exhibit hallucinations, generating plausible yet incorrect responses. In this
arXiv:2609.12356v1 Announce Type: new Abstract: SNAP-KG is a framework for assigning newly arriving entities to semantic communities in a growing knowledge graph (KG) using only their raw features, wi
arXiv:2606.21203v2 Announce Type: replace Abstract: Psycholinguistics studies show that human readers fall for coherence illusions: an incoherent discourse can seem coherent simply because a distracto
arXiv:2609.12169v1 Announce Type: new Abstract: Wheat streak mosaic virus (WSMV) is a destructive pathogen of sweet corn and other cereal crops, causing yield losses and complicating early detection b
arXiv:2609.12503v1 Announce Type: cross Abstract: Proactive in-cabin agents can help passengers understand automated-vehicle (AV) behavior, but communicating every ride event may introduce unnecessary
arXiv:2609.12591v1 Announce Type: new Abstract: Foundation models are increasingly adapted through fine-tuning, model editing, and alignment procedures while retaining previously acquired capabilities
arXiv:2609.12702v1 Announce Type: new Abstract: Capturing the digital trace of handwriting usually requires a specific stylus and a compatible substrate, be it a capacitive touchscreen, an ElectroMagn
arXiv:2609.12475v1 Announce Type: new Abstract: Comprehensive benchmark suites are essential for improving large language models (LLMs), but many widely used benchmarks are redundant, making evaluatio
arXiv:2609.10579v1 Announce Type: cross Abstract: We present a machine-checked Lean~4 formalization of Dong and Yang's classification of optimal finite-length (n,4) binary block codes for binary symme
arXiv:2508.16843v5 Announce Type: replace-cross Abstract: Voice authentication has undergone significant changes from traditional systems that relied on handcrafted acoustic features to deep learning
arXiv:2609.11713v1 Announce Type: cross Abstract: Artificial neural networks rely on vector-matrix multiplications (VMMs), whose implementation in von Neumann architectures is dominated by costly data
arXiv:2609.11498v1 Announce Type: new Abstract: Practical uncertainty quantification (UQ) for large language models must decide, from a single generation, whether a specific answer should be trusted.
arXiv:2609.11381v1 Announce Type: cross Abstract: Embedding an intelligent agent in an existing application creates a persistent coordination problem: users can revise goals and manipulate shared obje
arXiv:2609.11190v1 Announce Type: new Abstract: AI shopping assistants increasingly redirect consumer discovery, creating an urgent need for tools that support seller-side competitive decision-making.