# Low-Resource Clickbait Spoiling for Indonesian via Question Answering

Source: [Low-Resource Clickbait Spoiling for Indonesian via Question Answering](<https://www.sota2.com/research/paper/68fa70da1e209131cea4db62>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:51:52.116Z

Authors: Ni Putu Intan Maharani, Ayu Purwarianti, Alham Fikri Aji

Published: 2023-10-12T07:17:17.000Z

## Abstract

Clickbait spoiling aims to generate a short text to satisfy the curiosity induced by a clickbait post. As it is a newly introduced task, the dataset is only available in English so far. Our contributions include the construction of manually labeled clickbait spoiling corpus in Indonesian and an evaluation on using cross-lingual zero-shot question answering-based models to tackle clikcbait spoiling for low-resource language like Indonesian. We utilize selection of multilingual language models. The experimental results suggest that XLM-RoBERTa (large) model outperforms other models for phrase and passage spoilers, meanwhile, mDeBERTa (base) model outperforms other models for multipart spoilers.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2310.08085>)

[PDF](<https://arxiv.org/pdf/2310.08085.pdf>)