Search Results for author:
Found 8 papers, 7 papers with code
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on.
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays
The critical component in our framework is an anatomy-guided attention module that aids the downstream observation network in focusing on the relevant anatomical regions generated by the anatomy network.
Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining
This paper presents an overview of the ImageArg shared task, the first multimodal Argument Mining shared task co-located with the 10th Workshop on Argument Mining at EMNLP 2023.
Predicting the Quality of Revisions in Argumentative Writing
The ability to revise in response to feedback is critical to students' writing success.
ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness Mining
The growing interest in developing corpora of persuasive texts has promoted applications in automated systems, e. g., debating and essay scoring systems; however, there is little prior work mining image persuasiveness from an argumentative perspective.
Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability
One major advantage of our proposed method is that it improves the model adaptation to a large number of heterogeneous tasks.
Ticket-BERT: Labeling Incident Management Tickets with Language Models
An essential aspect of prioritizing incident tickets for resolution is efficiently labeling tickets with fine-grained categories.
LogicPrpBank: A Corpus for Logical Implication and Equivalence
Logic reasoning has been critically needed in problem-solving and decision-making.
