3 citations · 3 across the 3 of their papers we have counts for
3 papers
NodeSyn: Socially Aligned Synthetic Data for AI Evaluation
Qazi Mamunur Rashid, Xuan Yang, Zhengzhe Yang +5
Recent advancements in generative AI facilitate large-scale synthetic data generation for model evaluation. However, without targeted approaches, these datasets often lack the soci…
Improving Neutral Point-of-View Generation with Data- and Parameter-Efficient RL
Jessica Hoffmann, Christiane Ahlheim, Zac Yu +8
The paper shows that parameter-efficient reinforcement learning (PE-RL) is a highly effective training regime to improve large language models' (LLMs) ability to answer queries on…
Socially Responsible Data for Large Multilingual Language Models
Andrew Smart, Ben Hutchinson, Lameck Mbangula Amugongo +12
Large Language Models (LLMs) have rapidly increased in size and apparent capabilities in the last three years, but their training data is largely English text. There is growing int…