5 citations · 5 across the 10 of their papers we have counts for
4 papers · 1 filter
RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting
Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
Despite the widespread use of LLMs due to their superior performance in various tasks, their high computational costs often lead potential users to opt for the pretraining-finetuni…
P-TA: Using Proximal Policy Optimization to Enhance Tabular Data Augmentation via Large Language Models
Shuo Yang, Chenchen Yuan, Yao Rong +2
A multitude of industries depend on accurate and reasonable tabular data augmentation for their business processes. Contemporary methodologies in generating tabular data revolve ar…
Is Crowdsourcing Breaking Your Bank? Cost-Effective Fine-Tuning of Pre-trained Language Models with Proximal Policy Optimization
Shuo Yang, Gjergji Kasneci
Wide usage of ChatGPT has highlighted the potential of reinforcement learning from human feedback. However, its training pipeline relies on manual ranking, a resource-intensive pro…
User Intent Recognition and Satisfaction with Large Language Models: A User Study with ChatGPT
Anna Bodonhelyi, Efe Bozkir, Shuo Yang +2
The rapid evolution of LLMs represents an impactful paradigm shift in digital interaction and content engagement. While they encode vast amounts of human-generated knowledge and ex…