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arXiv:2602.10961v3 Announce Type: replace-cross Abstract: Standard geometric control relies on force-moment decoupling, an assumption that breaks down in many aerial platforms due to spurious forces...
arXiv:2602.12085v3 Announce Type: replace-cross Abstract: Renormalization group flows are constrained by symmetries. Traditionally, we have made the most of 't Hooft anomalies associated to the...
arXiv:2602.12780v2 Announce Type: replace-cross Abstract: We revisit the algorithmic problem of reconstructing a graph from homomorphism counts that has first been studied in (B\"oker et...
arXiv:2602.16731v1 Announce Type: new Abstract: This paper presents a longitudinal open dataset of Spanish public procurement extracted from the Official State Gazette (BOE) covering the...
arXiv:2602.16733v1 Announce Type: new Abstract: Reproducibility is central to research credibility, yet large-scale reanalysis of empricial data remains costly because replication packages vary widely in...
arXiv:2602.16973v1 Announce Type: new Abstract: We test whether lying aversion can steer equilibrium selection in mechanism design. In a principal-worker environment, the direct mechanism admits...
arXiv:2602.17086v1 Announce Type: new Abstract: Dynamic decision-making under model uncertainty is central to many economic environments, yet existing bandit and reinforcement learning algorithms rely on...
arXiv:2602.17052v1 Announce Type: cross Abstract: Generative modeling builds on and substantially advances the classical idea of simulating synthetic data from observed samples. This paper shows...
arXiv:2602.17543v1 Announce Type: cross Abstract: Efficient estimation of causal and structural parameters can be automated using the Riesz representation theorem and debiased machine learning (DML)....
arXiv:2305.17948v5 Announce Type: replace Abstract: We analyze the re-equilibration dynamics of matching markets with contracts following disruptions such as firm entry or worker exit. In...
arXiv:2307.15313v2 Announce Type: replace Abstract: We develop new changes-in-changes (CIC) and distributional synthetic controls (DSC) types of methods when there exists group-level heterogeneity. For CIC,...
arXiv:2501.15761v3 Announce Type: replace Abstract: We propose a new factor analysis framework and estimators of the factors and loadings that are robust to certain weak...
arXiv:2505.00282v3 Announce Type: replace Abstract: To analyze unstructured data (text, images, audio, video), economists typically first extract low-dimensional structured features with a neural network. Neural...
arXiv:2506.20749v2 Announce Type: replace Abstract: This paper studies analytic inference along two dimensions of clustering. In such setups, the commonly used approach has two drawbacks....
arXiv:2602.16071v2 Announce Type: replace Abstract: We demonstrate that a ubiquitous feature of network games, bilateral strategic interactions, is equivalent to having player utilities that are...
arXiv:2602.16211v2 Announce Type: replace Abstract: We study a model of auction design where a seller is selling a set of objects to a set of...
arXiv:2410.12306v2 Announce Type: replace-cross Abstract: Auction is applied for trade with various mechanisms. A simple but practical question is which mechanism, typically first-price or second-price...
arXiv:2602.16713v1 Announce Type: new Abstract: Recent advancements in civil infrastructure inspections underscore the need for precise three-dimensional (3D) damage visualization on digital twins, transcending traditional...
arXiv:2602.16714v1 Announce Type: new Abstract: Age assessment is crucial in forensic and judicial decision-making, particularly in cases involving undocumented individuals and unaccompanied minors, where legal...
arXiv:2602.16715v1 Announce Type: new Abstract: We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design Structure...
arXiv:2602.16716v1 Announce Type: new Abstract: Adaptive systems often operate across multiple contexts while reusing a fixed internal state space due to constraints on memory, representation,...
arXiv:2602.16717v1 Announce Type: new Abstract: In pattern mining, sequential rules provide a formal framework to capture the temporal relationships and inferential dependencies between items. However,...
arXiv:2602.16718v1 Announce Type: new Abstract: Episode mining is a fundamental problem in analyzing a sequence of numerous events. For discovering strong relationships between events in...
arXiv:2602.16719v1 Announce Type: new Abstract: Approximate Nearest Neighbor Search (ANNS) underpins many large-scale data mining and machine learning applications, with efficient retrieval increasingly hinging on...