Knowledge catalogue
arXiv:2502.02068v3 Announce Type: replace-cross Abstract: This paper introduces RoSeMary, the first-of-its-kind ML/Crypto codesign watermarking framework that regulates LLM-generated code to avoid int
arXiv:2608.09999v1 Announce Type: cross Abstract: In transfer learning, the choice of source model largely influences the performance on a target dataset. Still, selecting a fitting source remains a c
arXiv:2608.11080v1 Announce Type: new Abstract: Rail transit systems play a vital role in urban mobility and economic development. As key components of such systems, rail transit stations function as
arXiv:2608.10766v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) seeks to explain how an Artificial Intelligence (AI) system arrived at a particular decision. We propose ''Rul
arXiv:2608.10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments. However, providing complete
arXiv:2608.10708v1 Announce Type: new Abstract: Recent Vision Foundation Models (VFMs) predict depth, camera pose, and pointmap in a single forward pass without per-scene optimization, achieving stron
arXiv:2608.10240v1 Announce Type: cross Abstract: Multi-modal sequential recommenders assume every item carries every modality, but real product catalogs often miss images or text, and a model trained
arXiv:2608.10392v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models have recently moved beyond routing a fixed number of complete experts. Shared-expert designs preserve reusable knowled
arXiv:2608.10091v1 Announce Type: new Abstract: We present a method for training imperceptible visual watermarks to coexist with other such watermarks. Recent work has shown that independently trained
arXiv:2608.10615v1 Announce Type: new Abstract: Discrete diffusion models for categorical generation are defined by a corruption kernel, which determines the intermediate state space and the associate
arXiv:2608.11079v1 Announce Type: new Abstract: Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated
arXiv:2608.11136v1 Announce Type: new Abstract: Logic Tensor Networks (LTN) provide a neurosymbolic framework in which first-order logic is interpreted through tensor operations, enabling logical cons
arXiv:2608.10519v1 Announce Type: new Abstract: InfinityStar extends visual autoregressive generation to video through a sequence of image and clip pyramids. Its changing scale and cross-clip context,
arXiv:2608.09994v1 Announce Type: cross Abstract: Spherical Equivalent Refraction (SER) and Axial Length (AL) are core indicators for pediatric myopia screening, yet their measurements require dedicat
arXiv:2608.10845v1 Announce Type: cross Abstract: Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplac
arXiv:2608.10709v1 Announce Type: new Abstract: Quantization-Aware Training (QAT) enables the deployment of quantized models with minimal accuracy degradation. However, in practical scenarios, trainin
arXiv:2608.10249v1 Announce Type: new Abstract: We present a scalable framework for unsupervised clustering of maritime trajectories derived from terabyte-scale Automatic Identification System (AIS) a
arXiv:2608.10277v1 Announce Type: cross Abstract: We present a stochastic coupled emulator of E3SM version 3, built on the SamudrACE framework, which couples an atmosphere emulator (ACE2) with a full-
arXiv:2608.10949v1 Announce Type: cross Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under
arXiv:2506.13058v2 Announce Type: replace-cross Abstract: Diffusion probabilistic models (DPMs) have demonstrated remarkable success in visual generation. However, their iterative sampling mechanism r
arXiv:2608.11044v1 Announce Type: new Abstract: Hierarchical Text Classification (HTC), as a critical text mining task, faces challenges such as complex label hierarchies and class imbalance. Existing
arXiv:2608.10936v1 Announce Type: cross Abstract: We study a Restart POMDP (Partially Observable Markov Decision Process) on a general Borel state space, where the controller either lets the hidden st
arXiv:2608.10983v1 Announce Type: cross Abstract: Multi-modal recommenders fuse collaborative signals with item modalities such as text, images, and audio, but the usefulness of each drifts over time
arXiv:2509.21263v2 Announce Type: replace Abstract: Semantic matching aims to establish pixel-level correspondences between instances of the same category and represents a fundamental task in computer
arXiv:2608.00422v2 Announce Type: replace Abstract: Large language models (LLMs) can generate fluent reasoning traces that nevertheless lead to incorrect answers, making response-level uncertainty est
arXiv:2607.10410v2 Announce Type: replace-cross Abstract: Reliable forecasting of several interrelated environmental variables - such as regional precipitation and temperature, or other correlated geo
arXiv:2608.11114v1 Announce Type: cross Abstract: Probabilistic forecasting plays an essential role in risk-sensitive decision-making, particularly in long-horizon settings. However, existing approach
arXiv:2608.11054v1 Announce Type: new Abstract: Deep learning models have emerged as the standard computational tool for a wide range of applications in genomics. Yet, uncertainty quantification (UQ)
arXiv:2608.10522v1 Announce Type: cross Abstract: While vision-language models dominate medical representation learning, unstructured text lacks the dense, quantitative diagnostic phenotypes inherent
arXiv:2608.10233v1 Announce Type: cross Abstract: Groundwater variability in Ghana remains poorly characterized due to limited long-term in-situ observations. This study investigates groundwater stora
arXiv:2604.07557v2 Announce Type: replace Abstract: Small longitudinal cohorts, common in maternal health, rare diseases, and early-phase trials, limit computational modeling because enrollment is slo
arXiv:2608.10665v1 Announce Type: new Abstract: Multimodal large language models often generate reasoning chains containing subtle errors that lead to incorrect answers. Current verification approache
arXiv:2608.11174v1 Announce Type: new Abstract: Regulating the latent space to an isotropic Gaussian distribution provides a stable and information-maximized landscape for world model planning. Howeve
arXiv:2505.01656v2 Announce Type: replace Abstract: Analyzing tree morphology, particularly trunk and branch extraction, is valuable for genetic breeding and forestry management. Existing image-based
arXiv:2307.03587v4 Announce Type: replace Abstract: In non-stationary linear contextual bandits, existing efficient algorithms typically rely on the Weighted Regularized Least-Squares (WRLS) estimator
arXiv:2608.10528v1 Announce Type: cross Abstract: Anchor-based pointwise LLM reranking scores each candidate against a shared reference passage to recover cross-document context at pointwise cost. We
arXiv:2608.10758v1 Announce Type: new Abstract: Vision-language models can describe an image with remarkable accuracy, yet a more fundamental question remains unanswered: what visual information actua
arXiv:2608.10836v1 Announce Type: cross Abstract: The signal ambiguity of whispered speech drives ASR systems toward two opposing failure modes: failing to capture whispered speech or hallucinatory tr
arXiv:2608.10309v1 Announce Type: cross Abstract: Advanced air mobility operations hold the potential to enhance and expand regional transportation of both people and goods in populated areas. However
arXiv:2608.10878v1 Announce Type: new Abstract: Accurate and responsive turn-taking is essential for spoken dialogue systems, which must distinguish in real time between user interruptions, backchanne
arXiv:2607.28646v2 Announce Type: cross Abstract: This article analyses narrative mechanisms that are common in dialogues with LLM chatbots. In combination, these mechanisms produce an interactional s
arXiv:2406.03143v4 Announce Type: replace Abstract: Adversarial purification is a kind of defense technique that can defend against various unseen adversarial attacks without modifying the victim clas
arXiv:2608.08521v1 Announce Type: cross Abstract: Face recognition systems face two distinct, commonly-separated failure modes: spoofing, where an impostor presents a photograph or video of an authori
arXiv:2608.09452v1 Announce Type: new Abstract: Pixel permutation is a fundamental tool in image processing, image encryption, and data hiding (including watermarking and steganography) that rearrange
arXiv:2608.08319v1 Announce Type: new Abstract: Brain magnetic resonance imaging (MRI) is central to neuroscience and clinical assessment, but models are commonly developed for individual diseases, po
arXiv:2608.08294v1 Announce Type: cross Abstract: Knowledge distillation trains a smaller student to match the outputs of a larger teacher. Feature-based methods also align intermediate representation
arXiv:2608.08040v1 Announce Type: cross Abstract: We introduce conditional cylindrical neural networks for approximating functionals of conditional laws in McKean-Vlasov equations with common noise. F
arXiv:2608.08920v1 Announce Type: new Abstract: Perioperative risk prediction models are often limited by narrow surgical populations, incomplete intraoperative data, poor calibration, and limited int
arXiv:2607.28432v2 Announce Type: replace Abstract: Intelligence is commonly understood as the ability to acquire and apply knowledge, adapt to unfamiliar situations and solve new problems. Large lang
arXiv:2608.09604v1 Announce Type: cross Abstract: Over the past decade, microfacet-based BRDF models have formed the foundation of real-time rendering pipelines. Despite their widespread use, they oft
arXiv:2608.08770v1 Announce Type: cross Abstract: Diffusion models are increasingly used as controllable samplers, whose generations can be steered at inference time according to a chosen reward funct
arXiv:2608.09417v1 Announce Type: new Abstract: Deep decoder-only Transformers often replace the original Post-Norm architecture with Pre-Norm variants because Post-Norm training is highly sensitive t
arXiv:2608.08192v1 Announce Type: new Abstract: Standard approaches to abductive reasoning can retain multiple candidate explanations, but they do not generally combine explicit compositional cross-hy
arXiv:2608.07887v1 Announce Type: new Abstract: Robotic grasping of thin, flat objects such as coins on hard surfaces remains challenging because conventional methods require reorienting the object, a
arXiv:2608.09088v1 Announce Type: new Abstract: Mixed emotions represent a clinically relevant but still underexplored target for automatic emotion recognition. EEG provides millisecond-level access t
arXiv:2608.08898v1 Announce Type: cross Abstract: Characterising optimisation problem instances is a fundamental part of understanding the behaviour and performance of different algorithms as well as
arXiv:2608.09117v1 Announce Type: new Abstract: Probabilistic Circuits (PCs) are tractable generative models whose internal nodes encode a hierarchy of probabilistic sum- maries over different variabl
arXiv:2608.08632v1 Announce Type: new Abstract: Airport landside traffic centers connect terminal arrivals with taxis, ride-hailing vehicles, private cars, buses, metro services, parking facilities, a
arXiv:2608.07624v1 Announce Type: new Abstract: Tracked robots are widely used in unstructured environments; however, their obstacle traversal capability is fundamentally limited by a tradeoff between
arXiv:2603.23016v2 Announce Type: replace-cross Abstract: Tabular data is more challenging to generate than text and images, due to its heterogeneous features and much lower sample sizes. On this task