Knowledge catalogue
arXiv:2605.15418v2 Announce Type: cross Abstract: Hybrid optical systems combining refractive and diffractive optical responses have the potential to support new types of optical behavior, but they ar
arXiv:2609.21221v1 Announce Type: new Abstract: Perceptual planning tasks require two key capabilities: accurately perceiving uncertain scenes and planning valid action sequences following logical rul
arXiv:2609.20835v1 Announce Type: new Abstract: Background: The Voynich Manuscript is a fifteenth-century codex written in an unknown script whose content remains undeciphered. Previous studies sugges
arXiv:2609.21584v1 Announce Type: new Abstract: Wall-climbing robots capable of scaling vertical surfaces could help automate hazardous or labor intensive tasks such as window washing, inspection, mai
arXiv:2511.16923v1 Announce Type: cross Abstract: Single-cell RNA sequencing (scRNA-seq) enables transcriptomic profiling at cellular resolution but suffers from pervasive dropout events that obscure
arXiv:2609.21996v1 Announce Type: new Abstract: Large language models can hold knowledge they do not report. A model may sandbag on a capability evaluation, or answer against what it internally knows,
arXiv:2609.21044v1 Announce Type: new Abstract: Covariate-rich time-series forecasting requires deciding how external variables enter the target forecasting path. Existing Transformer-based forecaster
arXiv:2609.21718v1 Announce Type: new Abstract: Fully autonomous tractor--trailer systems are increasingly deployed in logistics, agriculture, and industrial environments, where precise and robust pat
arXiv:2609.21800v1 Announce Type: new Abstract: Traditional unsupervised anomaly detection (UAD) methods are designed to flag or localise deviations from a normative distribution, ignoring the underly
arXiv:2509.21653v2 Announce Type: replace-cross Abstract: We propose a conversion scheme that turns regret minimizing algorithms into fixed point iterations, with convergence guarantees following from
arXiv:2609.21400v1 Announce Type: new Abstract: Open-vocabulary 3D scene mapping aims to build a persistent representation of the objects in an environment. Existing systems typically rely on engineer
arXiv:2609.21817v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become a prominent paradigm for mapping multimodal inputs, including semantic instructions, visual observations
arXiv:2609.21017v1 Announce Type: cross Abstract: We study data-driven early stopping for spectral regularisation methods in the classical non-parametric regression setting. Building on the discrepanc
arXiv:2608.25285v2 Announce Type: replace-cross Abstract: Partial deepfake speech, where only limited segments of an utterance are synthesized or manipulated, poses a significant challenge to existing
arXiv:2609.21416v1 Announce Type: new Abstract: Collaborative robots are increasingly deployed in industrial scenarios characterized by frequent product changeovers. As an intuitive programming method
arXiv:2609.21214v1 Announce Type: new Abstract: Cognitive diagnosis infers students' concept mastery from response logs. However, students' responses are not determined by mastery alone: non-cognitive
arXiv:2609.22005v1 Announce Type: cross Abstract: Gating the value pathway of attention reportedly improves language model pretraining, and prior studies disagree on why. We argue and provide experime
arXiv:2609.21672v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance but suffer from slow and costly inference. Existing acceleration methods often lead to noticeabl
arXiv:2609.21792v1 Announce Type: new Abstract: Navigating toward human callers is an important capability for rescue robots operating where visual contact is degraded or occluded. We present Acoustic
arXiv:2609.21024v1 Announce Type: new Abstract: This paper extends an existing algorithm for the first-order derivatives of rigid-body dynamics to the case of closed-chain kinematic systems modeled us
arXiv:2609.21169v1 Announce Type: cross Abstract: Independent control of tonescale regions (e.g., shadows, highlights) is essential for painters, photographers and cinematographers to bring 2D images
arXiv:2609.21482v1 Announce Type: cross Abstract: Accurate neural world models are central to model-based robotics, where they enable robots to predict future states from previously observed trajector
arXiv:2609.21821v1 Announce Type: cross Abstract: This paper presents a novel framework integrating Bayesian physiological modeling with optimal control strategies to achieve uncertainty-aware, person
arXiv:2609.21502v1 Announce Type: new Abstract: Recent 3D foundation models enable generalizable geometric reasoning from RGB images but remain limited in persistent memory, scalability, and renderabl
arXiv:2511.14458v2 Announce Type: replace Abstract: Flexible robots hold great promise for enhancing minimally invasive surgery (MIS) by providing superior dexterity, precise control, and safe tissue
arXiv:2609.20965v1 Announce Type: new Abstract: Close-proximity pipeline inspection is challenging for standard drones due to high hovering power consumption, airflow sensitivity, and propeller wash i
arXiv:2609.21716v1 Announce Type: new Abstract: Multi UAV missions in complex environments require the system to understand both the surrounding scene and the intent of a human operator while maintain
arXiv:2609.21386v1 Announce Type: cross Abstract: Comprehensive video understanding is crucial for advancing artificial intelligence toward the intricate dynamics of the physical world. While recent a
arXiv:2609.20999v1 Announce Type: cross Abstract: Latent variable generative models are commonly fit using simple priors over latent variables, but draws from these priors often fail to produce realis
arXiv:2609.21192v1 Announce Type: new Abstract: Organizations deploying agentic artificial intelligence must determine more than whether a model is trustworthy; they must establish what to validate, c
arXiv:2609.21226v1 Announce Type: new Abstract: Quadrotors are increasingly deployed in applications such as agriculture, infrastructure inspection, and maintenance. In each of these applications, the
arXiv:2609.21075v1 Announce Type: cross Abstract: As access to professional mental healthcare remains limited, many individuals turn to online platforms such as Reddit to seek peer support situated wi
arXiv:2406.08775v2 Announce Type: replace Abstract: Labels are the cornerstone of supervised machine learning algorithms. Most visual recognition methods are fully supervised, using bounding boxes or
arXiv:2603.22560v4 Announce Type: replace Abstract: Legged robots operate across a wide range of physical scales, but how their designs should be adapted as size changes remains unclear. Here, we tack
arXiv:2609.21805v1 Announce Type: cross Abstract: Background: Just-in-time adaptive interventions (JITAIs) can use behavioral data to adapt support to changing contexts, but many rely on predefined ru
arXiv:2609.22043v1 Announce Type: new Abstract: Memory systems for large language models have focused predominantly on efficient retrieval, whereas the decision of whether retrieved memories should be
arXiv:2609.21309v1 Announce Type: new Abstract: Any lossless compression algorithm (like gzip) may be converted into a machine learning method, via either Normalized Compression Distance or the Minimu
arXiv:2609.21655v1 Announce Type: new Abstract: We propose a framework to analyse how strongly different linguistic relations are linearly encoded in language model embedding spaces. We formalise line
arXiv:2607.17582v2 Announce Type: replace Abstract: Approximate Nearest Neighbor Search (ANNS) plays a pivotal role in modern deep learning pipelines. Recently, many ANNS systems have been proposed to
arXiv:2609.21378v1 Announce Type: new Abstract: Reinforcement learning has substantially improved large language model (LLM) agents in verifiable domains, but remains difficult to apply to open-ended
arXiv:2609.20982v1 Announce Type: new Abstract: Reinforcement learning (RL) controllers have been recently adopted for Unmanned Aerial Vehicles (UAV) navigation and control. However, they are suscepti
arXiv:2609.21995v1 Announce Type: new Abstract: The prediction of critical heat flux (CHF), a key safety-related quantity in nuclear thermal hydraulics, remains an important challenge due to its direc
arXiv:2609.21461v1 Announce Type: cross Abstract: Embodied foundation models are constrained by the limited scale and diversity of robot demonstrations, motivating the use of large-scale egocentric hu
arXiv:2609.20974v1 Announce Type: new Abstract: In Mixture-of-Experts language models, the router typically selects and weights experts based on the token's hidden state, utilizing limited contextual
arXiv:2510.07024v3 Announce Type: replace-cross Abstract: LLMs are remarkable artifacts that have revolutionized a range of knowledge-intensive tasks. A significant contributor is their factual knowle
arXiv:2609.21284v1 Announce Type: cross Abstract: Long-running AI agents outlive initiating processes through credentials, delegated tasks, queues, callbacks, reservations, and provider-side operation
arXiv:2609.20868v1 Announce Type: cross Abstract: Transfer and multi-nucleon transfer reactions are essential tools for probing nuclear structure and reaction dynamics, requiring precise determination
arXiv:2609.21863v1 Announce Type: new Abstract: Empirical evaluation is central to recommender-systems (RecSys) research, but turning experimental designs into executable code remains a manual and err
arXiv:2609.21940v1 Announce Type: new Abstract: Long-term memory is essential for large language model (LLM) agents to maintain consistency and personalization over extended interactions. Existing mem
arXiv:2609.22048v1 Announce Type: new Abstract: A selective predictor acts as a safety gate: it returns an output only when the prediction appears sufficiently trustworthy. Deployments increasingly re
arXiv:2609.21377v1 Announce Type: new Abstract: Robotic fabric comparison needs to actively combine visual appearance and tactile cues. Here, we present AVT-Fabric, an RGB-first framework that allocat
arXiv:2604.02401v2 Announce Type: replace Abstract: This paper revisits three backup-based safety filters -- Backup Control Barrier Functions (Backup CBF), Model Predictive Shielding (MPS), and gateke
arXiv:2609.21743v1 Announce Type: cross Abstract: Entropy minimization is a standard objective for test-time adaptation (TTA), but it can fail in imbalanced binary segmentation. Unlike image classific
arXiv:2609.21997v1 Announce Type: cross Abstract: LLM agents in social simulation revise their opinions implicitly, in context: how open an agent is to persuasion can neither be specified nor verified
arXiv:2609.21694v1 Announce Type: cross Abstract: Context: We developed a probabilistic machine learning method with the aim of performing the O(10)-way classification of low- and high-resolution spec
arXiv:2512.24493v3 Announce Type: replace-cross Abstract: Control barrier functions for port-Hamiltonian systems inherit model uncertainty when the Hamiltonian is learned from data. We show how to pro
arXiv:2601.07316v2 Announce Type: replace-cross Abstract: Automated electrocardiogram diagnosis using deep learning remains limited by signal-agnostic representations that treat multi-lead recordings
arXiv:2509.22754v2 Announce Type: replace-cross Abstract: Autonomous driving remains a highly active research domain that seeks to enable vehicles to perceive dynamic environments, predict the future
arXiv:2609.21490v1 Announce Type: new Abstract: Gender bias remains a persistent concern in machine translation (MT), affecting both generated translations and their automatic evaluation. When a sourc
arXiv:2609.21879v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have recently been proposed as promising tools for face recognition, as they can produce natural language explanations a