most citedOn the Algorithmic Bias of Aligning Large Language Models with RLHF: Preference Collapse and Matching Regularization

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cs.LG2024

DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation

Yinjun Wu, Mayank Keoliya, Kan Chen +7

Designing faithful yet accurate AI models is challenging, particularly in the field of individual treatment effect estimation (ITE). ITE prediction models deployed in critical sett…