4 citations · 5 across the 10 of their papers we have counts for
4 papers · 1 filter
CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback
Wenbo Zhang, Aditya Majumdar, Asif Ekbal +1
Large language models (LLMs) show strong performance across many tasks but remain weak at understanding code-mixed (CM) language. Despite this limitation, improving LLMs for CM tas…
Hey GPT, Can You be More Racist? Analysis from Crowdsourced Attempts to Elicit Biased Content from Generative AI
Hangzhi Guo, Pranav Narayanan Venkit, Eunchae Jang +7
The widespread adoption of large language models (LLMs) and generative AI (GenAI) tools across diverse applications has amplified the importance of addressing societal biases inher…
Have LLMs Reopened the Pandora's Box of AI-Generated Fake News?
Xinyu Wang, Wenbo Zhang, Sai Koneru +5
With the rise of AI-generated content spewed at scale from large language models (LLMs), genuine concerns about the spread of fake news have intensified. The perceived ability of L…
Watermarking Counterfactual Explanations
Hangzhi Guo, Firdaus Ahmed Choudhury, Tinghua Chen +1
Counterfactual (CF) explanations for ML model predictions provide actionable recourse recommendations to individuals adversely impacted by predicted outcomes. However, despite bein…