arXiv:2510.00479v2 Announce Type: replace-cross
Abstract: We numerically investigate the feasibility and limits of jointly estimating flow fields and unknown particle properties (e.g., position, size, and density) from Lagrangian particle tracking (LP…
arXiv:2603.24333v1 Announce Type: cross
Abstract: Recently, Forr\’e (arXiv:2104.11547, 2021) introduced transitional conditional independence, a notion of conditional independence that provides a unified framework for both random and non-stochastic va…
arXiv:2508.01517v3 Announce Type: replace-cross
Abstract: We develop a central limit theorem (CLT) for a non-parametric estimator of the transition matrices in controlled Markov chains (CMCs) with finite state-action spaces. Our results establish prec…
arXiv:2603.23923v1 Announce Type: cross
Abstract: Predictive inference is a fundamental task in statistics, traditionally addressed using parametric assumptions about the data distribution and detailed analyses of how models learn from data. In recent…
arXiv:2603.23688v1 Announce Type: cross
Abstract: Background: Determining an adequate sample size is essential for developing reliable and generalisable clinical prediction models, yet practical guidance on selecting appropriate methods remains limite…
arXiv:2603.24413v1 Announce Type: new
Abstract: Poetry generation in Sanskrit typically requires the verse to be semantically coherent and adhere to strict prosodic rules. In Sanskrit prosody, every line of a verse is typically a fixed length sequence…
arXiv:2603.03339v3 Announce Type: replace-cross
Abstract: Artificial intelligence (AI) and large language models (LLMs) are transforming educational technology by enabling conversational tutoring, personalized explanations, and inquiry-driven learning…
arXiv:2603.24375v1 Announce Type: new
Abstract: Evaluating the pedagogical quality of AI tutors remains challenging: standard NLG metrics do not determine whether responses identify mistakes, scaffold reasoning, or avoid revealing the answers. For the…
arXiv:2602.11224v2 Announce Type: replace-cross
Abstract: We present Agent-Diff, a novel benchmarking framework for evaluating agentic Large Language Models (LLMs) on real-world productivity software API tasks via code execution. Agentic LLM performan…
arXiv:2603.24372v1 Announce Type: new
Abstract: Autoformalization – automatically translating natural language mathematical texts into formal proof language such as Lean4 – can help accelerate AI-assisted mathematical research, be it via proof verific…