Knowledge catalogue
arXiv:2605.04135v1 Announce Type: cross Abstract: Readers of applied-domain LLM capability evaluations want to know what AI systems can currently do. That literature answers a related, but consequenti
arXiv:2605.05062v1 Announce Type: new Abstract: As time-to-market is crucial in the Integrated Circuit (IC) industry, speeding up layout manufacturability verifi-cation is essential. Chemical-Mechanic
arXiv:2501.14171v3 Announce Type: replace-cross Abstract: Multi-modal brain MRI provides essential complementary information for clinical diagnosis. However, acquiring all modalities in practice is of
arXiv:2605.05088v1 Announce Type: new Abstract: Achieving resilient and sustainable cities requires scalable approaches to decarbonising residential buildings, which account for about 20% of UK greenh
arXiv:2605.04770v1 Announce Type: new Abstract: While zero-shot appearance-based 3D gaze estimation offers significant cost-efficiency by directly mapping RGB images to gaze vectors, its reliability i
arXiv:2605.04449v1 Announce Type: new Abstract: Dialogue State Tracking (DST) requires precise extraction of structured information from multi-domain conversations, a task where Large Language Models
arXiv:2605.02927v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have garnered increasing attention as one of bio-inspired models due to their great potential in neuromorphic computing
arXiv:2605.04604v1 Announce Type: cross Abstract: High-performance computing (HPC) is increasingly important for scalable quantum chemistry workflows that couple classical generative models, quantum c
arXiv:2605.03383v1 Announce Type: new Abstract: Lithology classification aims to infer subsurface rock types from well-logging signals, supporting downstream applications like reservoir characterizati
arXiv:2604.07401v2 Announce Type: replace-cross Abstract: We study the thermodynamic memory capacity of modern Hopfield networks (Dense Associative Memory models) with continuous states under geometri
arXiv:2603.26178v2 Announce Type: replace Abstract: We introduce the Geometric Evolution Graph Convolutional Network (GEGCN), a novel framework that enhances graph representation learning through expl
arXiv:2605.04474v1 Announce Type: new Abstract: Geometry is central to PDE-governed systems, motivating shape optimization and inversion. Classical pipelines conduct costly forward simulation with geo
arXiv:2605.05164v1 Announce Type: new Abstract: Accurate analysis of histopathological images is critical for disease diagnosis and treatment planning. Whole-slide images (WSIs), which digitize tissue
arXiv:2605.03410v2 Announce Type: new Abstract: Out-of-distribution (OOD) detection identifies test samples that fall outside a model's training distribution, a capability critical for safe deployment
arXiv:2605.04246v1 Announce Type: cross Abstract: In this article, we study unbalanced optimal transport (UOT) and establish a control-theoretic dynamical extension, which we call the unbalanced densi
arXiv:2605.04279v1 Announce Type: new Abstract: Transformer self-attention can be interpreted as a gradient flow on the unit sphere, in which tokens evolve under softmax interaction potentials and ten
arXiv:2605.04502v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) often struggle to train reliably on stiff and oscillatory dynamical systems due to poor optimization conditioni
arXiv:2605.04638v1 Announce Type: new Abstract: Uncertainty quantification (UQ) is an important technique for ensuring the trustworthiness of LLMs, given their tendency to hallucinate. Existing state-
arXiv:2605.04643v1 Announce Type: new Abstract: Approximating the ideological position of Members of Parliament (MPs) is a fundamental task in political science, helping researchers understand legisla
arXiv:2605.05020v1 Announce Type: new Abstract: System Neural Diversity (SND) measures behavioral heterogeneity in multi-agent reinforcement learning by averaging pairwise distances over all inom{n}{2
arXiv:2605.04376v1 Announce Type: new Abstract: The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite thes
arXiv:2605.04698v1 Announce Type: cross Abstract: Modern malware detection pipelines rely on continuous data ingestion and machine learning to counter the high volume of novel threats. This work inves
arXiv:2605.04435v1 Announce Type: new Abstract: Feedforward Gaussian Splatting has recently emerged as an efficient paradigm for 4D reconstruction in autonomous driving. However, in unstructured off-r
arXiv:2605.04581v1 Announce Type: new Abstract: Light field (LF) image super-resolution benefits from Epipolar Plane Images (EPIs), whose line slopes explicitly encode disparity. However, existing Tra
arXiv:2605.04759v1 Announce Type: new Abstract: Transformer based pre-trained large language models have become ubiquitous. There is increasing evidence to suggest that even with large scale pre-train
arXiv:2605.04282v1 Announce Type: new Abstract: Visual SLAM is a core component of spatial computing systems, yet deploying learned local feature extractors on microcontroller-class hardware remains c
arXiv:2605.04500v1 Announce Type: new Abstract: Low-resource language varieties used by specific groups remain neglected in the development of Multilingual Language Models. A great deal of cross-lingu
arXiv:2605.04525v1 Announce Type: new Abstract: Recent advances in generative models have shown promise in generating behavior plans for long-horizon, sparse reward tasks. While these approaches have
arXiv:2605.05072v1 Announce Type: new Abstract: 3D occupancy prediction aims to infer dense, voxel-wise scene semantics from sensor observations, where the 2D-to-3D view transformation serves as a cru
arXiv:2602.23010v3 Announce Type: replace-cross Abstract: We present Helmlab, a family of two purpose-built color spaces for UI design systems sharing a common 11-stage analytical structure: MetricSpa
arXiv:2605.04103v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) has emerged as a powerful framework for automatically discovering neural architectures that balance accuracy and effi
arXiv:2605.04191v1 Announce Type: cross Abstract: Public attitudes toward artificial intelligence are heterogeneous, ordinally measured, and poorly captured by any single dependency graph. Existing or
arXiv:2605.04594v1 Announce Type: new Abstract: Many real-world heterogeneous graphs exhibit pronounced heterophily, where connected nodes often have dissimilar labels or play different semantic roles
arXiv:2605.04682v1 Announce Type: cross Abstract: Spatial transcriptomics offers spatially resolved gene expression profiling within tissue sections, but its cost and limited throughput hinder large-s
arXiv:2605.04254v1 Announce Type: new Abstract: We introduce State Vector Space Partitioning (SVSP), a novel method to mimic a black box reinforcement learning policy using a set of human-interpretabl
arXiv:2605.04304v1 Announce Type: cross Abstract: Advanced chart question answering requires both precise perception of small visual elements and multi-step reasoning across several subplots. While ex
arXiv:2605.04524v1 Announce Type: new Abstract: We present a single-image head mesh reconstruction framework that addresses the longstanding challenge of simultaneously preserving facial identity and
arXiv:2602.07608v2 Announce Type: replace Abstract: Metastatic Progression remains the leading cause of cancer-related mortality, yet predicting whether a primary tumor will metastasize and where it w
arXiv:2602.02924v2 Announce Type: replace Abstract: Diffusion policy sampling enables reinforcement learning (RL) to represent multimodal action distributions beyond suboptimal unimodal Gaussian polic
arXiv:2605.05113v1 Announce Type: new Abstract: We study signal propagation in linear recurrent models at finite width. While existing signal propagation theory relies predominantly on the infinite-wi
arXiv:2605.04257v1 Announce Type: new Abstract: Cold spraying is an increasingly common approach for repairing and manufacturing components due to its solid-state manufacturing capabilities. However,
arXiv:2605.05144v1 Announce Type: new Abstract: This paper reflects on a AI research project carried out by a team of high-school and early-undergraduate students under the mentorship of graduate rese
arXiv:2605.03210v1 Announce Type: cross Abstract: We argue that AI-saturated markets are likely to create Veblen-good premiums, which we term human-provenance premiums, for verified human presence, an
arXiv:2605.04752v1 Announce Type: new Abstract: Accurate traffic congestion classification requires models that jointly capture roadway scene context and non-stationary traffic motion, yet most prior
arXiv:2605.04853v1 Announce Type: new Abstract: We propose HIN-LRI, a hybrid framework that augments a classical numerical solver with a neural operator trained to correct the solver's structured trun
arXiv:2605.05024v1 Announce Type: cross Abstract: Hypergraphs model higher-order interactions, but realistic hypergraph generation remains difficult because incidence, hyperedge-size heterogeneity, an
arXiv:2605.04977v1 Announce Type: new Abstract: This companion paper reports the ICPR 2026 TVRID competition on privacy-aware top-view person re-identification. We present the competition setting, the
arXiv:2507.15736v2 Announce Type: replace Abstract: Innovation is a key driving force of human civilization. As the body of knowledge has grown considerably, bridging knowledge across different discip
arXiv:2605.04506v1 Announce Type: new Abstract: We introduce Ilov3Splat, a novel framework for instance-level open-vocabulary 3D scene understanding built on 3D Gaussian Splatting (3D-GS). Most prior
arXiv:2605.04262v1 Announce Type: new Abstract: Remaining useful life (RUL) estimation of synthetic fibre ropes (SFRs) is critical for safe operation in offshore-crane, wind turbine installation, and
arXiv:2605.05197v1 Announce Type: new Abstract: Grammaticality and likelihood are distinct notions in human language. Pretrained language models (LMs), which are probabilistic models of language fitte
arXiv:2407.14861v3 Announce Type: replace-cross Abstract: With the growing access to administrative health databases, retrospective studies have become crucial evidence for medical treatments. Yet, no
arXiv:2605.04825v1 Announce Type: new Abstract: Factorization machine with quadratic-optimization annealing (FMQA) is a black-box optimization method that combines a factorization machine (FM) surroga
arXiv:2605.04064v1 Announce Type: cross Abstract: Reasoning capabilities are crucial for reliable medical visual question answering (VQA); however, existing datasets rarely include reasoning explanati
arXiv:2605.03954v1 Announce Type: cross Abstract: The connection between subset-maximal repairs for inconsistent databases involving various integrity constraints and acceptable sets of arguments with
arXiv:2605.04475v1 Announce Type: new Abstract: Reliable autonomous driving requires scene understanding that is semantically consistent across heterogeneous sensors and verifiable at the reasoning st
arXiv:2603.11911v3 Announce Type: replace Abstract: We present InSpatio-WorldFM, an open-source real-time frame model for spatial intelligence. Unlike video-based world models that rely on sequential
arXiv:2512.17795v2 Announce Type: replace-cross Abstract: The unprecedented proliferation of digital data presents significant challenges in access, integration, and value creation across all data-int
arXiv:2605.04355v1 Announce Type: new Abstract: Autonomous driving systems rely heavily on robust sensor fusion to perceive complex envi- ronments. Traditional setups using RGB cameras and LiDAR often
arXiv:2605.04358v1 Announce Type: new Abstract: The rapid advancement in generative AI models has enabled the creation of photorealistic images. At the same time, there are growing concerns about the