Search Results for author:
Found 3 papers, 3 papers with code
CitePrompt: Using Prompts to Identify Citation Intent in Scientific Papers
For the ACL-ARC dataset, we report a 53. 86% F1 score for the zero-shot setting, which improves to 63. 61% and 66. 99% for the 5-shot and 10-shot settings, respectively.
Ranked #2 on
Citation Intent Classification
on ACL-ARC
Do Neural Topic Models Really Need Dropout? Analysis of the Effect of Dropout in Topic Modeling
Dropout is a widely used regularization trick to resolve the overfitting issue in large feedforward neural networks trained on a small dataset, which performs poorly on the held-out test subset.
Improving Contextualized Topic Models with Negative Sampling
Topic modeling has emerged as a dominant method for exploring large document collections.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
