Knowledge catalogue
arXiv:2505.08784v2 Announce Type: replace-cross Abstract: As machine learning (ML) enters high-stakes domains, trustworthy uncertainty quantification (UQ) is essential for safety. In this paper we int
arXiv:2606.12112v1 Announce Type: new Abstract: This paper presents the design, development, and experimental verification of PEBRE, an open-hardware add-on for fast software development on the Pepper
arXiv:2506.21855v2 Announce Type: replace Abstract: In this paper, we propose Periodic-MAE, a self-supervised framework for learning generalizable spatio-temporal representations of periodic physiolog
arXiv:2606.11860v1 Announce Type: new Abstract: In this paper, we introduce Representation Prediction via Autoencoding using Iterative Refinement (RePAIR) - a novel self-supervised representation lear
arXiv:2602.22962v2 Announce Type: replace Abstract: Data-driven models are revolutionizing weather forecasting. To optimize training efficiency and model performance, this paper analyzes empirical sca
arXiv:2606.11320v1 Announce Type: new Abstract: In this paper, we present a novel set of related models for semantic segmentation of node-link diagrams. These diagrams are frequently used to represent
arXiv:2606.11836v1 Announce Type: cross Abstract: This paper presents a novel data-free and training-free compression approach for speech foundation models using channelwise clustering via k-means. Mo
arXiv:2512.19245v2 Announce Type: replace-cross Abstract: This paper tackles the problem of estimating the relative position, orientation, and velocity between a UAV and a planar platform undergoing a
arXiv:2606.10489v1 Announce Type: new Abstract: Automated Planning is a subfield of Artificial Intelligence (AI) where the main objective is generating a sequence of actions, known as a plan, that hel
arXiv:2606.10200v1 Announce Type: cross Abstract: An improved GAN-based imaging logging image restoration method is presented in this paper for solving the problem of partially missing micro-resistivi
arXiv:2606.11188v1 Announce Type: new Abstract: This paper introduces ARM, a discrete representation-based AutoRegressive Model that unifies image understanding, generation, and editing within a next-
arXiv:2606.10281v1 Announce Type: cross Abstract: This paper presents AuditBench, a new benchmark dataset for evaluating the capabilities of LLMs at investigating security-related system audit logs. W
arXiv:2606.10377v1 Announce Type: cross Abstract: This paper analyzes bidirectional random projections for ordinary least squares (OLS) regression under the fixed design setting. Let (X,Y) in R^{n ime
arXiv:2606.10119v1 Announce Type: cross Abstract: Current-status data arise when an event time is observed only through an indicator of whether it occurred before an examination time. This paper studi
arXiv:2606.11182v1 Announce Type: cross Abstract: In this paper, we propose EEVEE, the first multi-dataset test-time prompt learning framework for LLM agents, enabling test-time prompt learning under
arXiv:2606.10698v1 Announce Type: cross Abstract: In this paper, we use machine learning to discover a new seeding strategy for integration-by-parts reduction of Feynman integrals, which is a frequent
arXiv:2606.10113v1 Announce Type: cross Abstract: This paper investigates whether LLM translations exhibit identifiable emotional profiles and how post-editing reshapes them toward human-like norms. W
arXiv:2606.10086v1 Announce Type: new Abstract: This paper develops a theory of exploratory adaptation under AI-assisted optimization. The central argument is that the long-run adaptive effects of AI
arXiv:2606.09543v2 Announce Type: replace Abstract: This short paper introduces a stylometric interpretation method inspired by genome-wide association studies (GWAS). Each 'gene' token's association
arXiv:2504.17080v3 Announce Type: replace Abstract: In this paper, we present an impedance control framework on the SE(3) manifold, which enables force tracking while guaranteeing passivity. Building
arXiv:2606.09842v1 Announce Type: cross Abstract: Applying Human Pose Estimation (HPE) in real world environments remains a challenging task, this paper explores and surveys real time HPE approaches a
arXiv:2606.10088v1 Announce Type: new Abstract: Reduced facial expressivity is a common motor manifestation of Parkinson's disease (PD), often described as hypomimia or facial bradykinesia. This paper
arXiv:2606.10931v1 Announce Type: new Abstract: Warning: This paper contains several toxic and offensive statements. Modern large language models (LLMs) are typically aligned through large-scale post-
arXiv:2606.10170v1 Announce Type: new Abstract: This paper extends the concept of Learning Entropy (LE) from temporal adaptive systems to spatial learning in multilayer perceptron networks (MLPs) appl
arXiv:2507.17188v2 Announce Type: replace-cross Abstract: This paper investigates secure communications in rate-splitting multiple access (RSMA) enabled heterogeneous UAV networks, where multiple UAVs
arXiv:2606.10111v1 Announce Type: new Abstract: This paper presents a nonlinear parameter estimator for Wiener-type state-space models obtained as a fixed-point architecture that couples two affine mi
arXiv:2606.10154v1 Announce Type: new Abstract: Quantized checkpoints are often screened first with quality metrics and only later, if at all, with direct safety tests. This paper audits that shortcut
arXiv:2606.10916v1 Announce Type: cross Abstract: This paper introduces range regularization for federated learning with linear systematic components to enhance statistical accuracy and induce cross-c
arXiv:2606.10228v1 Announce Type: cross Abstract: Safe exploration is a prerequisite for deploying reinforcement learning (RL) agents in safety-critical domains. In this paper, we approach safe explor
arXiv:2606.10069v1 Announce Type: new Abstract: In this paper we build upon a previous study in which we demonstrated, using XGBoost and earthquake catalogue data from Japan and Chile, that a set of 6
arXiv:2512.02201v3 Announce Type: replace Abstract: This paper introduces Swivuriso, a 3000-hour multilingual speech dataset developed as part of the African Next Voices project, to support the develo
arXiv:2606.10894v1 Announce Type: new Abstract: This paper presents an overview of the inaugural PortraitCraft Challenge, held as one of the official competitions at CVPR 2026. The challenge focuses o
arXiv:2102.05314v2 Announce Type: replace Abstract: In modern time series problems, one aims at forecasting multiple time series with possible missing and noisy values. In this paper, we introduce the
arXiv:2603.28054v2 Announce Type: replace Abstract: In this paper, we introduce GhostWriteBench, a dataset for LLM authorship attribution. It comprises long-form texts (50K+ words per book) generated
arXiv:2512.14614v2 Announce Type: replace Abstract: This paper presents WorldPlay, a streaming video diffusion model that enables real-time, interactive world modeling with long-term geometric consist
This is likely a discussion of Alan Kay's seminal 1984 paper on computer software that emphasizes the importance of understanding and working with the materiality of computational systems rather than
arXiv:2606.08554v1 Announce Type: new Abstract: This paper provides a theoretical account of memorization in stochastic interpolation models. By leveraging closed-form expressions for the optimal velo
arXiv:2502.06819v2 Announce Type: replace Abstract: This paper presents a framework for generating 3D indoor scenes from text prompts. Existing methods often formulate scene synthesis as an object lay
arXiv:2606.08433v1 Announce Type: cross Abstract: This paper reads six engine-level measurements together -- 1.1 host attack surface, 1.2 information leakage, 1.3 defense-in-depth stackability, 1.4 pu
arXiv:2403.06013v2 Announce Type: replace-cross Abstract: This paper delves into the critical area of deep learning robustness, challenging the conventional belief that classification robustness and e
This paper benchmarks frontier automatic speech recognition (ASR) systems on their ability to handle code-switched speech, where bilingual speakers mix languages within a single conversation. The rese
Commonwealth Fusion Systems published five peer-reviewed physics basis papers on its ARC fusion power plant in June 2026 in the Journal of Plasma Physics. The analysis validates that the ARC plant wil
arXiv:2606.09160v1 Announce Type: cross Abstract: This paper presents a unified system designed to support precision agriculture by integrating advanced weather prediction, crop recommendation, and a
arXiv:2509.20714v2 Announce Type: replace-cross Abstract: In this paper we show that cryptographic backdoors in a neural network (NN) can be highly effective in two directions, namely mounting the att
arXiv:2606.07924v1 Announce Type: cross Abstract: This paper presents our system description for the 2nd Workshop on Multimodal Augmented Generation via MultimodAl Retrieval (MAGMaR). Addressing the c
arXiv:2606.08259v1 Announce Type: new Abstract: This paper investigates the problem of generating synthetic tabular data with differential privacy (DP) guarantees, enabling data sharing in sensitive d
arXiv:2606.08532v1 Announce Type: new Abstract: A scientific hypothesis is the first step in research and undergoes experimental validation, yet it also reflects a deep understanding of and reasoning
arXiv:2606.09292v1 Announce Type: new Abstract: Reliable navigation in GPS-denied environments remains a fundamental challenge in robotics, aerospace, and autonomous vehicle applications. This paper p
arXiv:2606.08980v1 Announce Type: new Abstract: This paper introduces EPS3D, a new end-to-end feed-forward framework for open-vocabulary 3D panoptic segmentation. Unlike existing methods relying on ad
arXiv:2606.08941v1 Announce Type: cross Abstract: This paper proposes a collapsible method for estimating causal effects that maintains the estimator's consistency before and after marginalization ove
arXiv:2606.07623v1 Announce Type: new Abstract: This paper develops a model-theoretic framework for verifying context-conditioned language-model behavior by replacing benchmark labels with finite sema
arXiv:2606.09663v1 Announce Type: new Abstract: Recursive self-design refers to AI-assisted modification of the mechanisms by which an AI system is built, evaluated, and improved. This paper treats Me
arXiv:2509.21925v2 Announce Type: replace-cross Abstract: This paper investigates the theoretical behavior of generative models under finite training populations. Within the stochastic interpolation g
arXiv:2606.08303v1 Announce Type: new Abstract: This paper investigates a novel concept of time series geolocalization, where the goal is to infer the geographic origin of each raw time series. Succes
Humanity's ability to know, reason, judge, and act well is the foundation of science, democracy, crisis response, & management of AI itself. AI poses serious risks to that foundation. New paper on epi
June 9th Researcher Reciprocity License 'if you train on it, you let us generate - reverse terms of use void' Status quo 1. We teach frontier devs with ICLR/NeurIPS papers, OSS Github contributions 2.
arXiv:2606.07578v1 Announce Type: new Abstract: This paper extends MST-Direct, a Matching-via-Sinkhorn-Transport approach for multivariate geostatistical simulation, from the original bivariate, uncon
arXiv:2506.04480v2 Announce Type: replace-cross Abstract: This paper focuses on Geodesic Principal Component Analysis (GPCA) on a collection of probability distributions using the Otto-Wasserstein geo
arXiv:2606.08654v1 Announce Type: new Abstract: In this paper, we propose a perturbation-based conformal prediction framework for uncertainty quantification in operator learning, with a focus on the 2
arXiv:2606.07527v1 Announce Type: cross Abstract: The prevailing paradigm for training LLMs has evolved to rely on a massive post-training phase consisting of SFT and RL. In this position paper, we ar