most citedEvaluating Gender Bias of LLMs in Making Morality Judgements

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2024★ 2 cited

Evaluating Gender Bias of LLMs in Making Morality Judgements

Divij Bajaj, Yuanyuan Lei, Jonathan Tong +1

Large Language Models (LLMs) have shown remarkable capabilities in a multitude of Natural Language Processing (NLP) tasks. However, these models are still not immune to limitations…

cs.CV2021

Wisdom of (Binned) Crowds: A Bayesian Stratification Paradigm for Crowd Counting

Sravya Vardhani Shivapuja, Mansi Pradeep Khamkar, Divij Bajaj +2

Datasets for training crowd counting deep networks are typically heavy-tailed in count distribution and exhibit discontinuities across the count range. As a result, the de facto st…