Knowledge catalogue
arXiv:2603.11611v2 Announce Type: replace-cross Abstract: Rotary Positional Embedding (RoPE) is widely used in transformers to encode relative positional information, yet the effect of applying RoPE t
arXiv:2603.15270v3 Announce Type: replace-cross Abstract: Medical coding, which assigns standardized ICD codes to clinical documents, is a fundamental yet challenging task in modern healthcare. It req
arXiv:2610.22213v1 Announce Type: new Abstract: Randomized block coordinate descent (RBCD) is a popular optimization algorithm for many large-scale machine learning problems. The existing theoretical
arXiv:2610.21297v1 Announce Type: new Abstract: Panoramic 3D reconstruction enables the holistic recovery of complete 360 ^irc scene geometry, offering significant benefits for robotics and AR/VR appl
arXiv:2610.21361v1 Announce Type: new Abstract: Autonomous delivery in large scale buildings requires coordinated planning across multiple spatial levels, including building, floor, and room, while en
arXiv:2610.21038v1 Announce Type: cross Abstract: Machine learning models for tabular prediction typically assume that training data are representative of the population on which they will be deployed
arXiv:2610.21502v1 Announce Type: new Abstract: Internal solitary wave (ISW) remote sensing requires task parameters and spatial information to be transferred across image acquisition, detection, stri
arXiv:2601.21132v2 Announce Type: replace Abstract: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) w
arXiv:2610.20870v1 Announce Type: cross Abstract: We present a generative surrogate for charged-current (nu_mu)-nucleus scattering that can be calibrated to measured differential cross sections withou
arXiv:2610.20939v1 Announce Type: new Abstract: Online reinforcement learning (RL) with verifiable rewards has driven rapid progress in mathematics, coding, and tool use, but scaling this success to G
I evaluate new models by giving them actual work tasks that have already been completed by a trusted model and then comparing the results. My typical workflow is to plan tasks/requests in Gemini and c
arXiv:2610.21026v1 Announce Type: cross Abstract: In stochastic (strongly) convex optimization, establishing last-iterate convergence guarantees for first-order methods has recently garnered increasin
arXiv:2610.22358v1 Announce Type: new Abstract: Time series foundation models are becoming increasingly popular for general-purpose forecasting. However, most leading models predict marginal quantiles
arXiv:2610.21295v1 Announce Type: new Abstract: Federated minimax problems, such as distributionally robust optimization and adversarial training, include an inner maximization variable built from eac
arXiv:2610.20973v1 Announce Type: new Abstract: Geo-foundation models (GFMs) are typically evaluated by downstream task predictive performance, revealing little about which physical features they are
arXiv:2610.20631v1 Announce Type: cross Abstract: Romance scam has become a serious problem via social media, and the improvement of artificial intelligence enable to fake identify easily. In the stud
arXiv:2610.21220v1 Announce Type: cross Abstract: Recommender systems often need to balance multiple conflicting objectives. Controllable Multi-Objective Recommendation (CMOR) enables dynamic adjustme
arXiv:2610.21642v1 Announce Type: new Abstract: Vision Transformer architectures have showcased impressive performance on semantic segmentation, yet their quadratic attention complexity hinders practi
arXiv:2406.18397v4 Announce Type: replace-cross Abstract: In this article, we introduce the novel concept of the second maximum of a Gaussian random field defined on a Riemannian manifold: Once the fi
arXiv:2610.21089v1 Announce Type: new Abstract: Slip-induced falls when riding motorcycles are difficult to avoid even for expert riders and represent a major cause of single-vehicle accidents. Despit
arXiv:2602.03737v2 Announce Type: replace Abstract: Monitoring bottom-hole variables in petroleum wells is essential for production optimization, safety, and emissions reduction. Permanent Downhole Ga
arXiv:2610.20826v1 Announce Type: new Abstract: We investigate whether per-layer, per-task-phase (prompt/reasoning/response) expert-routing statistics in a Mixture-of-Experts (MoE) language model can
arXiv:2411.16164v2 Announce Type: replace Abstract: Text-to-image synthesis (T2I) focuses on generating high-quality images from textual descriptions In this survey, we review 490 papers on T2I spanni
arXiv:2610.20860v1 Announce Type: cross Abstract: We propose the Time-partitioning Gaussian Process Mixture Model (TPGPMM), a Bayesian nonparametric framework for identifying persistent regimes and mo
arXiv:2606.19729v3 Announce Type: replace-cross Abstract: Planning under uncertainty is an essential capability for autonomous robots. The Partially Observable Markov Decision Process (POMDP) provides
arXiv:2610.21964v1 Announce Type: cross Abstract: Neural networks often learn low-frequency components before high-frequency ones --- a phenomenon called spectral bias or termed F-principle. Many nume
arXiv:2511.10831v3 Announce Type: replace Abstract: Quantum kernel methods are a promising branch of quantum machine learning, but their per- formance across data types and encoding choices remains in
arXiv:2610.14356v1 Announce Type: new Abstract: AI-enabled systems must remain dependable when the conditions under which they operate change (e.g., due to input perturbations, distribution shifts, or
arXiv:2604.03925v2 Announce Type: replace Abstract: Large language models (LLMs) struggle to accumulate evidence across multiple rounds of user interactions, failing to update their beliefs in a manne
arXiv:2610.17410v1 Announce Type: new Abstract: Advances in large-scale machine learning have enabled agentic AI systems: persistent, autonomous computational entities that pursue goals, initiate acti
arXiv:2610.18603v1 Announce Type: new Abstract: Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the c
arXiv:2610.14697v1 Announce Type: cross Abstract: Speech-conditioned generation maps speech signals to target audio outputs. Prior end-to-end speech-conditioned generative models achieve high fidelity
arXiv:2610.20327v1 Announce Type: new Abstract: India's 22 scheduled languages are spoken by over a billion people in conversations that mix languages, often within one turn, overlap freely, and take
arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m
arXiv:2610.20141v1 Announce Type: new Abstract: In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is
arXiv:2610.19080v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially improved the reasoning of autoregressive and discrete-diffusion language models. Language models that gene
arXiv:2610.20319v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, yet their susceptibility to backdoor attacks remains a fo
arXiv:2610.19352v1 Announce Type: new Abstract: Clinical assessments are often collected using heterogeneous assessment systems across centers and time, leading to records that mix different but relat
arXiv:2602.08519v2 Announce Type: replace Abstract: Attributed Graph Clustering (AGC) is a fundamental unsupervised task that integrates structural topology and node attributes to uncover latent patte
As enterprises shift their AI usage from experimental chatbots to autonomous agents, teams are hitting a critical bottleneck: accessing and reasoning over data scattered across multiple clouds, SaaS p
arXiv:2610.19291v1 Announce Type: new Abstract: In so-called 'Industry 4.0,' integrated sensors, analytics tools, and other digital technologies supplement industrial workflows, potentiating enhanced
arXiv:2610.20597v1 Announce Type: cross Abstract: Training language agents is bottlenecked by the high cost of long-horizon rollouts, yet standard agentic reinforcement learning (RL) learns only from
arXiv:2610.18583v1 Announce Type: new Abstract: Sampling-based test-time scaling enhances LLM reasoning by aggregating multiple reasoning paths for the same query. Existing methods use answer frequenc
arXiv:2610.20217v1 Announce Type: new Abstract: Building foundation models for MRI has emerged as a promising direction for advancing medical image analysis and improving accessibility of task specifi
arXiv:2607.09015v2 Announce Type: replace Abstract: We study contextual bandit problems with correlated arms and access to surrogate reward signals produced by a machine learning model, motivated by a
arXiv:2610.17670v1 Announce Type: new Abstract: Cowork agents navigate dependencies across tools and files while adapting to changing user requirements and edits to shared workspaces. Scaling such env
arXiv:2610.16050v1 Announce Type: new Abstract: Personality assessment from asynchronous video interviews (AVIs) plays a crucial role in recruitment by enabling standardized and behaviorally grounded
arXiv:2610.19028v1 Announce Type: new Abstract: Science fiction is widely credited with unsettling gender. This article asks whether that holds at the linguistic level, in how readily gendered referen
arXiv:2610.15503v1 Announce Type: new Abstract: This Article critically examines the contemporary regulatory framework and discourse surrounding data portability in the United States. Using recent reg
arXiv:2610.20158v1 Announce Type: new Abstract: Self-supervised joint embedding learning aligns representations of augmented views while regularizing their distribution to prevent collapse. Regulariza
arXiv:2506.06121v3 Announce Type: replace Abstract: Large-scale itinerary planning is a variant of the traveling salesman problem, aiming to determine an optimal path that maximizes the collected poin
arXiv:2610.17197v1 Announce Type: cross Abstract: In the age of 'Software 3.0', when a complete program can be rewritten in minutes by an agent, the traditional approach of relying on code as the sole
arXiv:2610.17831v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) are appealing for code generation because they can update many tokens in parallel, yet many are optimized for
arXiv:2610.20187v1 Announce Type: new Abstract: Tracking changing comparators is a central problem in online learning. For exp-concave losses, previous work established the T^{1/3}P_T^{2/3} dependence
arXiv:2606.15251v2 Announce Type: replace-cross Abstract: Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential
arXiv:2610.15976v1 Announce Type: cross Abstract: This paper investigates a new role of randomness in stochastic policies--as a medium for embedding and communicating information. Specifically, we con
arXiv:2610.19224v1 Announce Type: new Abstract: Surface navigation on the Moon is subject to extreme illumination contrast and deployment-time perceptual disturbances. While modular navigation pipelin
arXiv:2610.15350v1 Announce Type: cross Abstract: We present Gugak-VocalSet, the first publicly available audio dataset for Korean traditional singing with dense annotations of sigimsae, a structured
arXiv:2610.16078v1 Announce Type: new Abstract: Recent advances in self-improving LLM agents have demonstrated the potential of AI systems that drive their own intelligence. However, many domain-speci
arXiv:2610.19518v1 Announce Type: new Abstract: While multi-fingered dexterous robot hands have the potential to provide human-level dexterity, using them for functional manipulation remains difficult