Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Szlichta, Jaroslaw"'
Expert search and team formation systems operate on collaboration networks, with nodes representing individuals, labeled with their skills, and edges denoting collaboration relationships. Given a keyword query corresponding to the desired skills, the
Externí odkaz:
http://arxiv.org/abs/2405.12881
This paper demonstrates RAGE, an interactive tool for explaining Large Language Models (LLMs) augmented with retrieval capabilities; i.e., able to query external sources and pull relevant information into their input context. Our explanations are cou
Externí odkaz:
http://arxiv.org/abs/2405.13000
Autor:
Rorseth, Joel, Godfrey, Parke, Golab, Lukasz, Kargar, Mehdi, Srivastava, Divesh, Szlichta, Jaroslaw
Towards better explainability in the field of information retrieval, we present CREDENCE, an interactive tool capable of generating counterfactual explanations for document rankers. Embracing the unique properties of the ranking problem, we present c
Externí odkaz:
http://arxiv.org/abs/2302.04983
Autor:
Zheng, Zheng, Zheng, Longtao, Langouri, Morteza Alipour, Chiang, Fei, Golab, Lukasz, Szlichta, Jaroslaw
Functional Dependencies (FDs) define attribute relationships based on syntactic equality, and, when usedin data cleaning, they erroneously label syntactically different but semantically equivalent values as errors. We explore dependency-based data cl
Externí odkaz:
http://arxiv.org/abs/2105.08105
Autor:
Karegar, Reza, Godfrey, Parke, Golab, Lukasz, Kargar, Mehdi, Srivastava, Divesh, Szlichta, Jaroslaw
Order dependencies (ODs) capture relationships between ordered domains of attributes. Approximate ODs (AODs) capture such relationships even when there exist exceptions in the data. During automated discovery of ODs, validation is the process of veri
Externí odkaz:
http://arxiv.org/abs/2101.02174
Variational Autoencoders (VAEs) have recently shown promising performance in collaborative filtering with implicit feedback. These existing recommendation models learn user representations to reconstruct or predict user preferences. We introduce join
Externí odkaz:
http://arxiv.org/abs/2008.07577
Autor:
Karegar, Reza, Mirsafian, Melicaalsadat, Godfrey, Parke, Golab, Lukasz, Kargar, Mehdi, Srivastava, Divesh, Szlichta, Jaroslaw
Much real-world data come with explicitly defined domain orders; e.g., lexicographic order for strings, numeric for integers, and chronological for time. Our goal is to discover implicit domain orders that we do not already know; for instance, that t
Externí odkaz:
http://arxiv.org/abs/2005.14068
We enhance constrained-based data quality with approximate band conditional order dependencies (abcODs). Band ODs model the semantics of attributes that are monotonically related with small variations without there being an intrinsic violation of sem
Externí odkaz:
http://arxiv.org/abs/1905.11948
A number of extensions to the classical notion of functional dependencies have been proposed to express and enforce application semantics. One of these extensions is that of order dependencies (ODs), which express rules involving order. The article e
Externí odkaz:
http://arxiv.org/abs/1905.02010
Autor:
Damasio, Guilherme, Corvinelli, Vincent, Godfrey, Parke, Mierzejewski, Piotr, Mihaylov, Alexandar, Szlichta, Jaroslaw, Zuzarte, Calisto
Query optimization is a hallmark of database systems enabling complex SQL queries of today's applications to be run efficiently. The query optimizer often fails to find the best plan, when logical subtleties in business queries and schemas circumvent
Externí odkaz:
http://arxiv.org/abs/1901.02049