Knowledge catalogue
arXiv:2608.03077v1 Announce Type: new Abstract: Multi-domain machine translation (MDMT) requires more than fluent generation: it demands domain-sensitive translation decisions such as domain disambigu
arXiv:2608.03055v1 Announce Type: cross Abstract: Automatic radiology report generation (RRG) aims to simulate the workflow of radiologists, assisting them in clinical diagnosis. However, existing met
arXiv:2608.03155v1 Announce Type: new Abstract: Autonomous exploration missions require decision-making under sensor uncertainty and computational constraints, yet integrating scientific representatio
arXiv:2608.02887v1 Announce Type: new Abstract: Choosing which features to collect is a deployment decision: the same limited questionnaire, test panel, or sensor set may need to serve several heterog
arXiv:2608.02774v1 Announce Type: cross Abstract: AI verification crosses a trust boundary: a verifier must learn enough to establish an authorized claim, yet the same evidence can reveal sensitive de
arXiv:2608.02831v1 Announce Type: cross Abstract: Audio reasoning is essential for machine understanding of the acoustic world. Reinforcement learning with verifiable rewards can elicit such reasoning
arXiv:2608.03836v1 Announce Type: new Abstract: A framework that persists execution state so a run can be interrupted, survive a crash, and continue must decide what a resume means for effects that al
arXiv:2608.03069v1 Announce Type: new Abstract: Deep Q-Networks (DQNs) learn value functions through bootstrapped temporal-difference updates, where future returns are approximated using a greedy maxi
arXiv:2608.03059v1 Announce Type: new Abstract: Inversion-free flow-based image editing avoids latent inversion, but still requires a target-side state at every editing step. The widely used equal-dis
arXiv:2608.02937v1 Announce Type: cross Abstract: Designing an effective electromagnetic inverse-scattering solver requires faithful enforcement of nonlinear full-wave physics together with an express
arXiv:2607.15196v2 Announce Type: replace-cross Abstract: We present a novel viewpoint for uncertainty quantification. Uncertainty measures are not primitives, in need of axioms and argumentation, but
arXiv:2608.03158v1 Announce Type: new Abstract: Daily activities require humans to coordinate whole-body motion with the motion of surrounding objects. Despite recent progress in human-object interact
arXiv:2511.21095v2 Announce Type: replace Abstract: Early Stage Ranking (ESR) in large-scale recommendation systems is dominated by ''user--item decoupling'' Two Tower architectures, which scale effic
arXiv:2608.03675v1 Announce Type: new Abstract: Citation excerpts can be used to increase the reliability of generated outputs and their faithfulness to cited sources, which is especially important in
arXiv:2505.12715v2 Announce Type: replace Abstract: Although fusing multiple sensor modalities can enhance object detection performance, existing fusion approaches often overlook subtle variations in
arXiv:2505.22850v2 Announce Type: replace Abstract: Referring Expression Counting (REC) requires distinguishing visually similar objects described by fine-grained text cues. Existing methods tackle th
arXiv:2608.00180v1 Announce Type: new Abstract: Conflicting objectives are general in RL alignment, and training on them data-efficiently is hard. Training a safety guard with RL means optimizing two
arXiv:2608.00130v1 Announce Type: cross Abstract: Fortran has been the cornerstone of high-performance computing for decades and remains unmatched in many domains. Yet the language faces an expertise
arXiv:2608.00879v1 Announce Type: cross Abstract: Leaf Area Index (LAI) is a fundamental biophysical variable governing land-atmosphere interactions; however, LAI forecasting at high spatial resolutio
arXiv:2608.00800v1 Announce Type: new Abstract: Injection molding is the cornerstone of mass-producing plastic components. While current algorithms can automate mold design for basic geometries using
arXiv:2608.02088v1 Announce Type: new Abstract: Reliable photovoltaic (PV) forecasts are needed for low-carbon energy systems, but newly deployed sites often have short, imperfect records. This makes
arXiv:2608.02310v1 Announce Type: new Abstract: The rapid spread of false and misleading health information through digital platforms has become a major public health challenge, particularly during in
arXiv:2602.12244v2 Announce Type: replace Abstract: Open world language conditioned task planning is crucial for robots operating in large-scale household environments. While many recent works attempt
arXiv:2608.00602v1 Announce Type: cross Abstract: Disordered traffic flow is characterized by weak or non-existent lane discipline in the presence of strong vehicle heterogeneity and continuous latera
arXiv:2608.00562v1 Announce Type: new Abstract: Autoregressive image generators are commonly pretrained with token-level cross-entropy under teacher forcing, yet evaluated by the distributional qualit
arXiv:2608.01090v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) are attractive for resource-constrained remote-sensing systems, but reliable out-of-distribution (OOD) detection remains
arXiv:2606.20389v2 Announce Type: replace Abstract: Continuum robots offer strong potential for manipulation tasks due to their high degrees of freedom, compliant structures, and operational safety. H
arXiv:2608.02331v1 Announce Type: new Abstract: The same body posture can convey entirely different emotions depending on its surrounding context, yet most methods for recognising bodily emotions trea
arXiv:2608.00119v1 Announce Type: new Abstract: Rapid estimation of impacted structures - critical for conflict-zone humanitarian response - is frequently hindered by post-strike satellite data embarg
arXiv:2608.00371v1 Announce Type: new Abstract: We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We speci
arXiv:2608.02408v1 Announce Type: new Abstract: Accurate gait analysis in Parkinson's disease (PD) typically relies on laboratory-based systems to capture biomechanical data, such as ground reaction f
arXiv:2608.00835v1 Announce Type: cross Abstract: Fragile X Syndrome (FXS) is a neurodevelopmental disorder caused by reduced expression of fragile X mental retardation protein (FMRP), leading to disr
arXiv:2608.02332v1 Announce Type: new Abstract: In offline reinforcement learning (RL), the distribution shift between behavioral data and the learned policy can lead to erroneous Q-value estimation,
arXiv:2405.06945v4 Announce Type: replace Abstract: Jointly recovering explicit surface geometry and high-quality appearance from multi-view images remains challenging. This capability is essential fo
arXiv:2608.01338v1 Announce Type: new Abstract: High-definition (HD) maps are essential for autonomous driving systems. In constructing such maps, onboard multi-view camera images, standard-definition
early sparks of rsi? Ali Taha @waterloo_intern explains how http://Z.ai's GLM-5.2 (@Zai_org) profiled its SGLang serving path and rewrote bottlenecked GPU kernels, (still lacks reliable judgment) grea
arXiv:2608.02284v1 Announce Type: new Abstract: Open-vocabulary segmentation identifies and segments objects from arbitrary textual descriptions. SAM 3 supports noun-phrase-guided segmentation and ach
arXiv:2510.21457v2 Announce Type: replace Abstract: Estimating heterogeneous treatment effects in network settings is complicated by interference, meaning that the outcome of an instance can be influe
arXiv:2608.01648v1 Announce Type: new Abstract: Hardware error logs in high-performance computing (HPC) systems provide early signals of abnormal behavior, yet there remain challenges in effectively f
arXiv:2608.00869v1 Announce Type: cross Abstract: Internet of Medical Things (IoMT) networks are hard to protect: devices are heterogeneous, computing resources are scarce, and traffic must be analyze
arXiv:2608.00568v1 Announce Type: new Abstract: Fairness audits are increasingly mandated in high-stakes applications such as hiring, lending, and automated decision-making. Recent work has establishe
arXiv:2607.17142v3 Announce Type: replace-cross Abstract: Prior case retrieval (PCR) aims to identify the precedent cases relevant to the facts of a query case. Incoming citation context, the text wit
arXiv:2608.00695v1 Announce Type: new Abstract: Zero-shot anomaly detection (ZSAD) aims to detect anomalies and localize defective regions in unseen target domains without target training data. Recent
arXiv:2608.01726v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in photorealistic and efficient rendering, leading to a rapid increase in 3D assets represented by
arXiv:2608.02177v1 Announce Type: new Abstract: Existing rainfall simulation methods for autonomous driving remain limited in physical controllability and multi-view consistency. This paper presents G
arXiv:2608.01194v1 Announce Type: cross Abstract: Artificial intelligence has been transformed by deep neural networks, yet the search for new learning architectures continues. Quantum machine learnin
arXiv:2608.02324v1 Announce Type: new Abstract: Longitudinal multiparametric MRI is central to follow-up imaging in oncology, yet real-world clinical data are characterised by missing sequences, heter
arXiv:2510.15127v3 Announce Type: replace-cross Abstract: Identifying the effects of mechanical ventilation (MV) protocols in critical care requires analyzing data from heterogeneous patient-ventilato
arXiv:2511.05969v2 Announce Type: replace Abstract: We propose a new approach to multi-factor classification of natural language texts based on weighted structured patterns such as N-grams, taking int
arXiv:2608.00075v1 Announce Type: new Abstract: Accelerated magnetic resonance imaging (MRI) aims to recover the k-space signal from acquired measurements, where accurate estimation of missing samples
arXiv:2608.00079v1 Announce Type: new Abstract: Long-form and real-time talking-head generation remains challenging due to a latency-quality trade-off: inefficient multi-step diffusion prohibits strea
arXiv:2608.02257v1 Announce Type: new Abstract: Mobile manipulation is a key capability for embodied intelligence, enabling robots to accomplish complex multi-stage tasks in open-world environments. H
arXiv:2608.00464v1 Announce Type: new Abstract: Based on vision and prior experience, humans can make rough physical predictions and adjust their manipulation strategies. This paper aims to endow robo
arXiv:2608.01771v1 Announce Type: new Abstract: We present LiveLight, the first diffusion-based framework for real-time streaming video relighting with interactive 3D lighting control. Achieving this
arXiv:2608.00868v1 Announce Type: new Abstract: Many open educational resources are lacking in accessibility, especially in-depth image descriptions. In subjects like Science and Mathematics, however,
arXiv:2608.00973v1 Announce Type: new Abstract: Text-to-image (T2I) systems typically have prompt-level safety filters before the generator to block unsafe requests, yet such systems remain vulnerable
arXiv:2511.19849v2 Announce Type: replace-cross Abstract: Recurrence objectives, where a target region must be visited infinitely often, are a fundamental class of specifications for Markov decision p
arXiv:2407.20432v3 Announce Type: replace Abstract: Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some s
arXiv:2608.00713v1 Announce Type: new Abstract: This paper describes Observatorio Lazaro, a language resource that monitors unassimilated lexical borrowings (predominantly English lexical borrowings o
arXiv:2608.01041v1 Announce Type: cross Abstract: Machine-learning predictors estimate processor performance far faster than cycle-level simulation. For design-space exploration, however, the valuable