11 citations · 13 across the 12 of their papers we have counts for
3 papers · 1 filter
A Large Language Model-Driven Reward Design Framework via Dynamic Feedback for Reinforcement Learning
Shengjie Sun, Runze Liu, Jiafei Lyu +3
Large Language Models (LLMs) have shown significant potential in designing reward functions for Reinforcement Learning (RL) tasks. However, obtaining high-quality reward code often…
Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately
Liang Zhang, Katherine Jijo, Spurthi Setty +4
Large Language Models (LLMs) generate responses to questions; however, their effectiveness is often hindered by sub-optimal quality of answers and occasional failures to provide ac…
Improving Classification Performance With Human Feedback: Label a few, we label the rest
Natan Vidra, Thomas Clifford, Katherine Jijo +2
In the realm of artificial intelligence, where a vast majority of data is unstructured, obtaining substantial amounts of labeled data to train supervised machine learning models po…