Low-Shot Learning for Fictional Claim Verification

Viswanath Chadalapaka; Derek Nguyen; JoonWon Choi; Shaunak Joshi; Mohammad Rostami

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arXiv · 2304.02769

Low-Shot Learning for Fictional Claim Verification

Viswanath Chadalapaka·Derek Nguyen·JoonWon Choi·Shaunak Joshi·Mohammad Rostami

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Abstract

In this paper, we study the problem of claim verification in the context of claims about fictional stories in a low-shot learning setting. To this end, we generate two synthetic datasets and then develop an end-to-end pipeline and model that is tested on both benchmarks. To test the efficacy of our pipeline and the difficulty of benchmarks, we compare our models' results against human and random assignment results. Our code is available at https://github.com/Derposoft/plot_hole_detection.

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Viswanath Chadalapaka, Derek Nguyen, JoonWon Choi, Shaunak Joshi, Mohammad Rostami. 2023-04-05. Low-Shot Learning for Fictional Claim Verification. https://arxiv.org/abs/2304.02769

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