no code implementations • 19 Feb 2024 • Matthew Shu, Nishant Balepur, Shi Feng, Jordan Boyd-Graber
Flashcard schedulers are tools that rely on 1) student models to predict the flashcards a student knows; and 2) teaching policies to schedule cards based on these predictions.
1 code implementation • 19 Feb 2024 • Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger
We hope to motivate the use of stronger baselines in MCQA benchmarks, the design of robust MCQA datasets, and further efforts to explain LLM decision-making.
1 code implementation • 13 Nov 2023 • Nishant Balepur, Shramay Palta, Rachel Rudinger
Chain-of-thought (COT) prompting can help large language models (LLMs) reason toward correct answers, but its efficacy in reasoning toward incorrect answers is unexplored.
1 code implementation • 23 Oct 2023 • Nishant Balepur, Jie Huang, Kevin Chen-Chuan Chang
Text style transfer is a prominent task that aims to control the style of text without inherently changing its factual content.
no code implementations • 24 May 2023 • Nishant Balepur, Jie Huang, Samraj Moorjani, Hari Sundaram, Kevin Chen-Chuan Chang
When answering complex questions, large language models (LLMs) may produce answers that do not satisfy all criteria of the question.
1 code implementation • 5 May 2023 • Nishant Balepur, Jie Huang, Kevin Chen-Chuan Chang
Expository documents are vital resources for conveying complex information to readers.