arXiv Machine Learning

Fast Discovery of Inclusion Dependencies with Desbordante

arXiv:2608. 02213v1 Announce Type: cross Abstract: Inclusion dependency is a relation between attributes of tables that indicates possible Primary Key-Foreign Key references.

Hugging Face Trending Papers
Jul 4

Efficient Discovery of Conditional Dependencies with Desbordante

Conditional functional dependencies (CFDs) are functional dependencies with a restricted scope: they specify the context in which a dependency holds and are useful for data-quality tasks, specifying complex integrity constraints, and extracting valuable insights from data. We study the CFD discovery problem, which is computationally demanding.

arXiv AI
Jul 7

Efficient Discovery of Conditional Dependencies with Desbordante

arXiv:2607. 04030v1 Announce Type: cross Abstract: Conditional functional dependencies (CFDs) are functional dependencies with a restricted scope: they specify the context in which a dependency holds and are useful for data-quality tasks, specifying complex integrity constraints, and extracting valuable insights from data.

By Ivan Kozhukov, Dmitry Fedoseev, Maksim Emelyanov, Artem Smola, Pyotr Senichenkov, Pavel Anosov, George Chernishev
arXiv Machine Learning
Jul 22

Vectorizing the Trie: Efficient Constrained Decoding for LLM-based Generative Retrieval on Accelerators

arXiv:2602. 22647v2 Announce Type: replace-cross Abstract: Generative retrieval has emerged as a powerful paradigm for LLM-based recommendation.

By Zhengyang Su, Isay Katsman, Yueqi Wang, Ruining He, Lukasz Heldt, Raghunandan Keshavan, Shao-Chuan Wang, Xinyang Yi, Mingyan Gao, Onkar Dalal, Lichan Hong, Ed Chi, Ningren Han