Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Estornell, Andrew"'
Large language models (LLMs) have demonstrated a remarkable ability to serve as general-purpose tools for various language-based tasks. Recent works have demonstrated that the efficacy of such models can be improved through iterative dialog between m
Externí odkaz:
http://arxiv.org/abs/2411.00053
Autor:
Borza, Victor, Estornell, Andrew, Clayton, Ellen Wright, Ho, Chien-Ju, Rothman, Russell, Vorobeychik, Yevgeniy, Malin, Bradley
Large participatory biomedical studies, studies that recruit individuals to join a dataset, are gaining popularity and investment, especially for analysis by modern AI methods. Because they purposively recruit participants, these studies are uniquely
Externí odkaz:
http://arxiv.org/abs/2408.01375
Recommender systems serve the dual purpose of presenting relevant content to users and helping content creators reach their target audience. The dual nature of these systems naturally influences both users and creators: users' preferences are affecte
Externí odkaz:
http://arxiv.org/abs/2407.14094
Our society collects data on people for a wide range of applications, from building a census for policy evaluation to running meaningful clinical trials. To collect data, we typically sample individuals with the goal of accurately representing a popu
Externí odkaz:
http://arxiv.org/abs/2407.00170
In today's competitive financial landscape, understanding and anticipating customer goals is crucial for institutions to deliver a personalized and optimized user experience. This has given rise to the problem of accurately predicting customer goals
Externí odkaz:
http://arxiv.org/abs/2406.19399
LLM hallucination, i.e. generating factually incorrect yet seemingly convincing answers, is currently a major threat to the trustworthiness and reliability of LLMs. The first step towards solving this complicated problem is to measure it. However, ex
Externí odkaz:
http://arxiv.org/abs/2402.10412
The integrity of elections is central to democratic systems. However, a myriad of malicious actors aspire to influence election outcomes for financial or political benefit. A common means to such ends is by manipulating perceptions of the voting publ
Externí odkaz:
http://arxiv.org/abs/2205.00102
The use of algorithmic decision making systems in domains which impact the financial, social, and political well-being of people has created a demand for these decision making systems to be "fair" under some accepted notion of equity. This demand has
Externí odkaz:
http://arxiv.org/abs/2112.02746
In many societal resource allocation domains, machine learning methods are increasingly used to either score or rank agents in order to decide which ones should receive either resources (e.g., homeless services) or scrutiny (e.g., child welfare inves
Externí odkaz:
http://arxiv.org/abs/2012.09147
Publikováno v:
UAI. 2020
Integrity of elections is vital to democratic systems, but it is frequently threatened by malicious actors. The study of algorithmic complexity of the problem of manipulating election outcomes by changing its structural features is known as election
Externí odkaz:
http://arxiv.org/abs/2007.09786