activity
20172026
most citedR-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning

5 citations · 6 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Making COMET Comparable Across Scripts: Diagnosis and Correction of Tokeniser-Induced Script Bias in Indic MT Evaluation

G. L. John Salvin, Swapnil Hingmire

COMET reports translation quality as a single number, and that number is routinely compared across target languages written in different scripts. Such a comparison assumes Script I…

cs.SE2026

The Nature of Technical Debt in Research Software

Neil A. Ernst, Ahmed Musa Awon, Swapnil Hingmire +1

Research software (also called scientific software) is essential for advancing scientific endeavours. Research software encapsulates complex algorithms and domain-specific knowledg…

cs.CL2025

Objectifying the Subjective: Cognitive Biases in Topic Interpretations

Swapnil Hingmire, Ze Shi Li, Shiyu +4

Interpretation of topics is crucial for their downstream applications. State-of-the-art evaluation measures of topic quality such as coherence and word intrusion do not measure how…

cs.CL2022

A Transfer Learning Pipeline for Educational Resource Discovery with Application in Leading Paragraph Generation

Irene Li, Thomas George, Alexander Fabbri +7

Effective human learning depends on a wide selection of educational materials that align with the learner's current understanding of the topic. While the Internet has revolutionize…

cs.CL2021

CLICKER: A Computational LInguistics Classification Scheme for Educational Resources

Swapnil Hingmire, Irene Li, Rena Kawamura +11

A classification scheme of a scientific subject gives an overview of its body of knowledge. It can also be used to facilitate access to research articles and other materials relate…

cs.CL2020★ 5 cited

R-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning

Irene Li, Alexander Fabbri, Swapnil Hingmire +1

The task of concept prerequisite chain learning is to automatically determine the existence of prerequisite relationships among concept pairs. In this paper, we frame learning prer…