65 citations · 165 across the 6 of their papers we have counts for
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cs.LG2023★ 2 cited
The Bias Amplification Paradox in Text-to-Image Generation
Preethi Seshadri, Sameer Singh, Yanai Elazar
Bias amplification is a phenomenon in which models exacerbate biases or stereotypes present in the training data. In this paper, we study bias amplification in the text-to-image do…
cs.LG2023
Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors
Kolby Nottingham, Yasaman Razeghi, Kyungmin Kim +4
Large language models (LLMs) are being applied as actors for sequential decision making tasks in domains such as robotics and games, utilizing their general world knowledge and pla…
cs.LG2023★ 6 cited
TABLET: Learning From Instructions For Tabular Data
Dylan Slack, Sameer Singh
Acquiring high-quality data is often a significant challenge in training machine learning (ML) models for tabular prediction, particularly in privacy-sensitive and costly domains l…