38 citations · 77 across the 14 of their papers we have counts for
15 papers
Characterize Then Distill: Mechanistic Reasoning in Large Output Spaces
Debjyoti Saha Roy, Byron C. Wallace, Javed A. Aslam
Reasoning-trained language models can perform, zero-shot, multi-label tasks that require selecting a small set of relevant labels from a universe of thousands to hundreds of thousa…
Don't Pay Attention, PLANT It: Pretraining Attention via Learning-to-Rank
Debjyoti Saha Roy, Byron C. Wallace, Javed A. Aslam
State-of-the-art Extreme Multi-Label Text Classification models rely on multi-label attention to focus on key tokens in input text, but learning good attention weights is challengi…
Supervised Learning in the Presence of Noise: Application in ICD-10 Code Classification
Youngwoo Kim, Cheng Li, Bingyang Ye +2
ICD coding is the international standard for capturing and reporting health conditions and diagnosis for revenue cycle management in healthcare. Manually assigning ICD codes is pro…
An Ensemble Approach for Automatic Structuring of Radiology Reports
Morteza Pourreza Shahri, Amir Tahmasebi, Bingyang Ye +3
Automatic structuring of electronic medical records is of high demand for clinical workflow solutions to facilitate extraction, storage, and querying of patient care information. H…
A Complex KBQA System using Multiple Reasoning Paths
Kechen Qin, Yu Wang, Cheng Li +4
Multi-hop knowledge based question answering (KBQA) is a complex task for natural language understanding. Many KBQA approaches have been proposed in recent years, and most of them…
Adapting RNN Sequence Prediction Model to Multi-label Set Prediction
Kechen Qin, Cheng Li, Virgil Pavlu +1
We present an adaptation of RNN sequence models to the problem of multi-label classification for text, where the target is a set of labels, not a sequence. Previous such RNN models…