Xi Chen, Wei Hu, Arijit Khan, Shreya Shankar, Haofen Wang, Jianguo Wang, and Tianxing Wu

Large Language Models, Knowledge Graphs, and Vector Databases: Synergy and Opportunities for Data Management (A Report on the LLM+KG@VLDB24 Workshop’s Panel Discussion)

knowledge graphs, LLMs, vector databases

Introduction Large language models (LLMs) and vector databases (Vector DBs) are becoming two vital enablers of generative AI (GenAI), a form of artificial intelligence that learns from massive datasets to generate new data, showcasing human-like creativity in text, images to code, speech, and video. In particular, LLMs are currently revolutionizing the field of natural language […]

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Eugene Wu

Where Does Database Research Go From Here?

Databases, Machine Learning

The past few years of generative AI have upended research agendas across academia. Having just spent my sabbatical in the Bay Area, where the San Francisco fog is mixed with a tinge of forest fire and LLMs, I wanted to reflect on the role of the academic database research community within this sea change from the […]

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Dimitris Sacharidis - Giorgos Giannopoulos - Loukas Kavouras

Auditing bias of recourse in classifiers (part II) 

Fairness

Introduction  Fairness is a fundamental principle reflecting our innate sense of justice and equity. The essence of fairness lies in the equitable, unbiased and just treatment of all individuals.  In our previous post (part I), we provided an introduction to the bias of recourse problem. In this post (part II), we describe our framework for […]

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Paul Boniol - Themis Palpanas

Time Series Anomaly Detection

Time Series

What it is, how it works, where we are, and where we are heading Anomaly detection is an important problem in data analytics with applications in many domains. In recent years, there has been an increasing interest in anomaly detection tasks applied to time series. In this post, we take a holistic view on anomaly […]

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Dimitris Sacharidis - Giorgos Giannopoulos - Loukas Kavouras

Auditing bias of recourse in classifiers (part I)

Fairness

Introduction  Fairness is a fundamental principle reflecting our innate sense of justice and equity. The essence of fairness lies in the equitable, unbiased and just treatment of all individuals. Nevertheless, translating this principle to specific rules, people, and systems can adhere to is highly context specific, with context meaning, social and cultural circumstances, as well […]

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