3 citations · 4 across the 8 of their papers we have counts for
5 papers · 1 filter
ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science
Sai Munikoti, Anurag Acharya, Sridevi Wagle +1
Large language models record impressive performance on many natural language processing tasks. However, their knowledge capacity is limited to the pretraining corpus. Retrieval aug…
Empirical evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science
Sridevi Wagle, Sai Munikoti, Anurag Acharya +2
Large language models (LLMs) have shown remarkable achievements in natural language processing tasks, producing high-quality outputs. However, LLMs still exhibit limitations, inclu…
Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning
Sai Munikoti, Anurag Acharya, Sridevi Wagle +1
Despite the dramatic progress in Large Language Model (LLM) development, LLMs often provide seemingly plausible but not factual information, often referred to as hallucinations. Re…
NuclearQA: A Human-Made Benchmark for Language Models for the Nuclear Domain
Anurag Acharya, Sai Munikoti, Aaron Hellinger +3
As LLMs have become increasingly popular, they have been used in almost every field. But as the application for LLMs expands from generic fields to narrow, focused science domains,…
Interactive Decision Tree Creation and Enhancement with Complete Visualization for Explainable Modeling
Boris Kovalerchuk Andrew Dunn, Alex Worland, Sridevi Wagle
To increase the interpretability and prediction accuracy of the Machine Learning (ML) models, visualization of ML models is a key part of the ML process. Decision Trees (DTs) are e…