20 citations · 28 across the 7 of their papers we have counts for
7 papers
Whose story is it? Personalizing story generation by inferring author styles
Nischal Ashok Kumar, Chau Minh Pham, Mohit Iyyer +1
Personalization is critical for improving user experience in interactive writing and educational applications, yet remains understudied in story generation. We study the task of pe…
PRACTIQ: A Practical Conversational Text-to-SQL dataset with Ambiguous and Unanswerable Queries
Mingwen Dong, Nischal Ashok Kumar, Yiqun Hu +9
Previous text-to-SQL datasets and systems have primarily focused on user questions with clear intentions that can be answered. However, real user questions can often be ambiguous w…
Improving Socratic Question Generation using Data Augmentation and Preference Optimization
Nischal Ashok Kumar, Andrew Lan
The Socratic method is a way of guiding students toward solving a problem independently without directly revealing the solution to the problem. Although this method has been shown…
Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science Education
Nischal Ashok Kumar, Andrew Lan
In computer science education, test cases are an integral part of programming assignments since they can be used as assessment items to test students' programming knowledge and pro…
Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank
Nischal Ashok Kumar, Nigel Fernandez, Zichao Wang +1
Reading comprehension is a crucial skill in many aspects of education, including language learning, cognitive development, and fostering early literacy skills in children. Automate…
A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing
Nischal Ashok Kumar, Wanyong Feng, Jaewook Lee +3
In this paper, we take a preliminary step towards solving the problem of causal discovery in knowledge tracing, i.e., finding the underlying causal relationship among different ski…
Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection
Jan Philip Wahle, Nischal Ashok, Terry Ruas +3
A drastic rise in potentially life-threatening misinformation has been a by-product of the COVID-19 pandemic. Computational support to identify false information within the massive…