43 citations · 120 across the 48 of their papers we have counts for
7 papers · 1 filter
How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation
Eduardo Tenorio, Karuna Bhaila, Xintao Wu
Large language models (LLMs) trained on web-scale corpora can memorize sensitive training data, posing significant privacy risks. Differential privacy (DP) has emerged as a princip…
Soft Prompting for Unlearning in Large Language Models
Karuna Bhaila, Minh-Hao Van, Xintao Wu
The widespread popularity of Large Language Models (LLMs), partly due to their unique ability to perform in-context learning, has also brought to light the importance of ethical an…
Privacy Preserving Prompt Engineering: A Survey
Kennedy Edemacu, Xintao Wu
Pre-trained language models (PLMs) have demonstrated significant proficiency in solving a wide range of general natural language processing (NLP) tasks. Researchers have observed a…
In-Context Learning Demonstration Selection via Influence Analysis
Vinay M. S., Minh-Hao Van, Xintao Wu
Large Language Models (LLMs) have showcased their In-Context Learning (ICL) capabilities, enabling few-shot learning without the need for gradient updates. Despite its advantages,…
Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model
Minh-Hao Van, Xintao Wu
Recently, large language models (LLMs) have taken the spotlight in natural language processing. Further, integrating LLMs with vision enables the users to explore more emergent abi…
Classifying Math KCs via Task-Adaptive Pre-Trained BERT
Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar +4
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labo…