3 citations · 4 across the 6 of their papers we have counts for
7 papers
The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study
Victoria Lin, Taedong Yun, Maja Matarić +3
Large language models (LLMs) show potential as simulators of human behavior, offering a scalable way to study responses to interventions. However, because LLMs are trained largely…
When Can Proxies Improve the Sample Complexity of Preference Learning?
Yuchen Zhu, Daniel Augusto de Souza, Zhengyan Shi +4
We address the problem of reward hacking, where maximising a proxy reward does not necessarily increase the true reward. This is a key concern for Large Language Models (LLMs), as…
Mind the Graph When Balancing Data for Fairness or Robustness
Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki +5
Failures of fairness or robustness in machine learning predictive settings can be due to undesired dependencies between covariates, outcomes and auxiliary factors of variation. A c…
Proxy Methods for Domain Adaptation
Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen +5
We study the problem of domain adaptation under distribution shift, where the shift is due to a change in the distribution of an unobserved, latent variable that confounds both the…
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner +3
We study the effectiveness of data-balancing for mitigating biases in contrastive language-image pretraining (CLIP), identifying areas of strength and limitation. First, we reaffir…
Predictive Churn with the Set of Good Models
Jamelle Watson-Daniels, Flavio du Pin Calmon, Alexander D'Amour +3
Issues can arise when research focused on fairness, transparency, or safety is conducted separately from research driven by practical deployment concerns and vice versa. This separ…
Choosing a Proxy Metric from Past Experiments
Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour +2
In many randomized experiments, the treatment effect of the long-term metric (i.e. the primary outcome of interest) is often difficult or infeasible to measure. Such long-term metr…