90 citations · 133 across the 7 of their papers we have counts for
7 papers
Sequential Bayesian Evaluation of Large Language Model Behavior
Rachel Longjohn, Shang Wu, Saatvik Kher +2
It is increasingly important to evaluate the characteristics of systems based on large language models (LLMs). Evaluations in this context often rely on a curated benchmark set of…
FairGBM: Gradient Boosting with Fairness Constraints
André F Cruz, Catarina Belém, Sérgio Jesus +3
Tabular data is prevalent in many high-stakes domains, such as financial services or public policy. Gradient Boosted Decision Trees (GBDT) are popular in these settings due to thei…
Weakly Supervised Multi-task Learning for Concept-based Explainability
Catarina Belém, Vladimir Balayan, Pedro Saleiro +1
In ML-aided decision-making tasks, such as fraud detection or medical diagnosis, the human-in-the-loop, usually a domain-expert without technical ML knowledge, prefers high-level c…
Promoting Fairness through Hyperparameter Optimization
André F. Cruz, Pedro Saleiro, Catarina Belém +2
Considerable research effort has been guided towards algorithmic fairness but real-world adoption of bias reduction techniques is still scarce. Existing methods are either metric-…
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations
Sérgio Jesus, Catarina Belém, Vladimir Balayan +4
There have been several research works proposing new Explainable AI (XAI) methods designed to generate model explanations having specific properties, or desiderata, such as fidelit…
Teaching the Machine to Explain Itself using Domain Knowledge
Vladimir Balayan, Pedro Saleiro, Catarina Belém +2
Machine Learning (ML) has been increasingly used to aid humans to make better and faster decisions. However, non-technical humans-in-the-loop struggle to comprehend the rationale b…
A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization
André F. Cruz, Pedro Saleiro, Catarina Belém +2
Considerable research effort has been guided towards algorithmic fairness but there is still no major breakthrough. In practice, an exhaustive search over all possible techniques a…