38 citations · 53 across the 5 of their papers we have counts for
5 papers
Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model Behavior
Rahul Nadkarni, Yanai Elazar, Hila Gonen +1
We present an experimental recipe for studying the relationship between training data and language model (LM) behavior. We outline steps for intervening on data batches -- i.e., ``…
AFEN: Respiratory Disease Classification using Ensemble Learning
Rahul Nadkarni, Emmanouil Nikolakakis, Razvan Marinescu
We present AFEN (Audio Feature Ensemble Learning), a model that leverages Convolutional Neural Networks (CNN) and XGBoost in an ensemble learning fashion to perform state-of-the-ar…
Third-Party Language Model Performance Prediction from Instruction
Rahul Nadkarni, Yizhong Wang, Noah A. Smith
Language model-based instruction-following systems have lately shown increasing performance on many benchmark tasks, demonstrating the capability of adapting to a broad variety of…
Binding Language Models in Symbolic Languages
Zhoujun Cheng, Tianbao Xie, Peng Shi +9
Though end-to-end neural approaches have recently been dominating NLP tasks in both performance and ease-of-use, they lack interpretability and robustness. We propose Binder, a tra…
Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical Study
Rahul Nadkarni, David Wadden, Iz Beltagy +3
Biomedical knowledge graphs (KGs) hold rich information on entities such as diseases, drugs, and genes. Predicting missing links in these graphs can boost many important applicatio…