activity
20122024
most citedRAGE Against the Machine: Retrieval-Augmented LLM Explanations

7 citations · 33 across the 14 of their papers we have counts for

collaborators

15 papers

cs.CL2024★ 7 cited

RAGE Against the Machine: Retrieval-Augmented LLM Explanations

Joel Rorseth, Parke Godfrey, Lukasz Golab +2

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 r…

cs.IR2023★ 7 cited

CREDENCE: Counterfactual Explanations for Document Ranking

Joel Rorseth, Parke Godfrey, Lukasz Golab +3

Towards better explainability in the field of information retrieval, we present CREDENCE, an interactive tool capable of generating counterfactual explanations for document rankers…

cs.DB2021★ 3 cited

Discovery and Contextual Data Cleaning with Ontology Functional Dependencies

Zheng Zheng, Longtao Zheng, Morteza Alipour Langouri +3

Functional Dependencies (FDs) define attribute relationships based on syntactic equality, and, when usedin data cleaning, they erroneously label syntactically different but semanti…

cs.DB2021★ 4 cited

Efficient Discovery of Approximate Order Dependencies

Reza Karegar, Parke Godfrey, Lukasz Golab +3

Order dependencies (ODs) capture relationships between ordered domains of attributes. Approximate ODs (AODs) capture such relationships even when there exist exceptions in the data…

cs.LG2020★ 3 cited

Joint Variational Autoencoders for Recommendation with Implicit Feedback

Bahare Askari, Jaroslaw Szlichta, Amirali Salehi-Abari

Variational Autoencoders (VAEs) have recently shown promising performance in collaborative filtering with implicit feedback. These existing recommendation models learn user represe…

cs.DB2020

Discovering Domain Orders through Order Dependencies

Reza Karegar, Melicaalsadat Mirsafian, Parke Godfrey +4

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 im…

cs.DB2019★ 2 cited

Errata Note: Discovering Order Dependencies through Order Compatibility

Parke Godfrey, Lukasz Golab, Mehdi Kargar +2

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…

cs.DB2019

ABC of Order Dependencies

Pei Li, Michael Bohlen, Jaroslaw Szlichta +1

We enhance constrained-based data quality with approximate band conditional order dependencies (abcODs). Band ODs model the semantics of attributes that are monotonically related w…

cs.DB2019

Guided Automated Learning for query workload re-Optimization

Guilherme Damasio, Vincent Corvinelli, Parke Godfrey +4

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 pl…

cs.SI2016★ 6 cited

Authority-based Team Discovery in Social Networks

Morteza Zihayat, Aijun An, Lukasz Golab +2

Given a social network of experts, we address the problem of discovering a team of experts that collectively holds a set of skills required to complete a given project. Most prior…

cs.DB2016

Efficient Discovery of Ontology Functional Dependencies

Sridevi Baskaran, Alexander Keller, Fei Chiang +2

Poor data quality has become a pervasive issue due to the increasing complexity and size of modern datasets. Constraint based data cleaning techniques rely on integrity constraints…

cs.DB2016

Effective and Complete Discovery of Order Dependencies via Set-based Axiomatization

Jaroslaw Szlichta, Parke Godfrey, Lukasz Golab +2

Integrity constraints (ICs) provide a valuable tool for expressing and enforcing application semantics. However, formulating constraints manually requires domain expertise, is pron…

cs.DB2015★ 1 cited

Effective Keyword Search in Graphs

Mehdi Kargar, Lukasz Golab, Jaroslaw Szlichta

In a node-labeled graph, keyword search finds subtrees of the graph whose nodes contain all of the query keywords. This provides a way to query graph databases that neither require…

cs.DB2015

OptImatch: Semantic Web System with Knowledge Base for Query Performance Problem Determination

Guilherme Damasio, Piotr Mierzejewski, Jaroslaw Szlichta +1

Database query performance problem determination is often performed by analyzing query execution plans (QEPs) in addition to other performance data. As the query workloads that org…

cs.DB2012

Fundamentals of Order Dependencies

Jaroslaw Szlichta, Parke Godfrey, Jarek Gryz

Dependencies have played a significant role in database design for many years. They have also been shown to be useful in query optimization. In this paper, we discuss dependencies…