cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers
Anirudh Sundar, Jin Xu, William Gay, Christopher Gordon Richardson, Larry Heck
Abstract
An emerging area of research in situated and multimodal interactive conversations (SIMMC) includes interactions in scientific papers. Since scientific papers are primarily composed of text, equations, figures, and tables, SIMMC methods must be developed specifically for each component to support the depth of inquiry and interactions required by research scientists. This work introduces $Conversational Papers$ (cPAPERS), a dataset of conversational question-answer pairs from reviews of academic papers grounded in these paper components and their associated references from scientific documents available on arXiv. We present a data collection strategy to collect these question-answer pairs from OpenReview and associate them with contextual information from $LaTeX$ source files. Additionally, we present a series of baseline approaches utilizing Large Language Models (LLMs) in both zero-shot and fine-tuned configurations to address the cPAPERS dataset.
BibTeX
@inproceedings{
sundar2024cpapers,
title={c{PAPERS}: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers},
author={Anirudh Sundar and Jin Xu and William Gay and Christopher Gordon Richardson and Larry Heck},
booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2024},
url={https://openreview.net/forum?id=DfhcOelEnP}
}