1 citations · 2 across the 8 of their papers we have counts for
10 papers
Auditing Preferences for Brands and Cultures in LLMs
Jasmine Rienecker, Katarina Mpofu, Naman Goel +4
Large language models (LLMs) based AI systems increasingly mediate what billions of people see, choose and buy. This creates an urgent need to quantify the systemic risks of LLM-dr…
Causal Pre-training Under the Fairness Lens: An Empirical Study of TabPFN
Qinyi Liu, Mohammad Khalil, Naman Goel
Foundation models for tabular data, such as the Tabular Prior-data Fitted Network (TabPFN), are pre-trained on a massive number of synthetic datasets generated by structural causal…
Whose Preferences? Differences in Fairness Preferences and Their Impact on the Fairness of AI Utilizing Human Feedback
Emilia Agis Lerner, Florian E. Dorner, Elliott Ash +1
There is a growing body of work on learning from human feedback to align various aspects of machine learning systems with human values and preferences. We consider the setting of f…
WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
Elliott Ash, Naman Goel, Nianyun Li +2
Machine learning based decision-support tools in criminal justice systems are subjects of intense discussions and academic research. There are important open questions about the ut…
Human-Guided Fair Classification for Natural Language Processing
Florian E. Dorner, Momchil Peychev, Nikola Konstantinov +3
Text classifiers have promising applications in high-stake tasks such as resume screening and content moderation. These classifiers must be fair and avoid discriminatory decisions…
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayuelas, Amit Deshpande +1
Training datasets for machine learning often have some form of missingness. For example, to learn a model for deciding whom to give a loan, the available training data includes ind…
Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain
Naman Goel, Cyril van Schreven, Aris Filos-Ratsikas +1
Blockchain based systems allow various kinds of financial transactions to be executed in a decentralized manner. However, these systems often rely on a trusted third party (oracle)…
Crowdsourcing with Fairness, Diversity and Budget Constraints
Naman Goel, Boi Faltings
Recent studies have shown that the labels collected from crowdworkers can be discriminatory with respect to sensitive attributes such as gender and race. This raises questions abou…
Deep Bayesian Trust : A Dominant and Fair Incentive Mechanism for Crowd
Naman Goel, Boi Faltings
An important class of game-theoretic incentive mechanisms for eliciting effort from a crowd are the peer based mechanisms, in which workers are paid by matching their answers with…
Parameter Database : Data-centric Synchronization for Scalable Machine Learning
Naman Goel, Divyakant Agrawal, Sanjay Chawla +1
We propose a new data-centric synchronization framework for carrying out of machine learning (ML) tasks in a distributed environment. Our framework exploits the iterative nature of…