most citedAssertion Enhanced Few-Shot Learning: Instructive Technique for Large Language Models to Generate Educational Explanations

2 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CY2024★ 2 cited

Leveraging Prompts in LLMs to Overcome Imbalances in Complex Educational Text Data

Jeanne McClure, Machi Shimmei, Noboru Matsuda +1

In this paper, we explore the potential of Large Language Models (LLMs) with assertions to mitigate imbalances in educational datasets. Traditional models often fall short in such…

cs.CL2024★ 2 cited

Assertion Enhanced Few-Shot Learning: Instructive Technique for Large Language Models to Generate Educational Explanations

Tasmia Shahriar, Kelly Ramos, Noboru Matsuda

Human educators possess an intrinsic ability to anticipate and seek educational explanations from students, which drives them to pose thought-provoking questions when students cann…