no code implementations • 21 Nov 2023 • Sai Munikoti, Anurag Acharya, Sridevi Wagle, Sameera Horawalavithana
We train a graph neural network on the curated document graph to act as a structural encoder for the corresponding passages retrieved during the model pretraining.
1 code implementation • 15 Nov 2023 • Sridevi Wagle, Sai Munikoti, Anurag Acharya, Sara Smith, Sameera Horawalavithana
This research investigates how uncertainty scores vary when scientific knowledge is incorporated as pretraining and retrieval data and explores the relationship between uncertainty scores and the accuracy of model-generated outputs.
no code implementations • 7 Nov 2023 • Sai Munikoti, Anurag Acharya, Sridevi Wagle, Sameera Horawalavithana
Despite the dramatic progress in Large Language Model (LLM) development, LLMs often provide seemingly plausible but not factual information, often referred to as hallucinations.
1 code implementation • 17 Oct 2023 • Anurag Acharya, Sai Munikoti, Aaron Hellinger, Sara Smith, Sridevi Wagle, Sameera Horawalavithana
As LLMs have become increasingly popular, they have been used in almost every field.
no code implementations • 12 Apr 2022 • W. Victor H. Yarlott, Armando Ochoa, Anurag Acharya, Laurel Bobrow, Diego Castro Estrada, Diana Gomez, Joan Zheng, David McDonald, Chris Miller, Mark A. Finlayson
We briefly describe an annotation effort to produce data for training motif detection, which is on-going.
no code implementations • 11 Sep 2020 • Anurag Acharya, Kartik Talamadupula, Mark A. Finlayson
Existing commonsense reasoning datasets for AI and NLP tasks fail to address an important aspect of human life: cultural differences.