2 citations · 3 across the 8 of their papers we have counts for
8 papers
Disentangling Hate Across Target Identities
Yiping Jin, Leo Wanner, Aneesh Moideen Koya
Hate speech (HS) classifiers do not perform equally well in detecting hateful expressions towards different target identities. They also demonstrate systematic biases in predicted…
ARAIDA: Analogical Reasoning-Augmented Interactive Data Annotation
Chen Huang, Yiping Jin, Ilija Ilievski +2
Human annotation is a time-consuming task that requires a significant amount of effort. To address this issue, interactive data annotation utilizes an annotation model to provide s…
GPT-HateCheck: Can LLMs Write Better Functional Tests for Hate Speech Detection?
Yiping Jin, Leo Wanner, Alexander Shvets
Online hate detection suffers from biases incurred in data sampling, annotation, and model pre-training. Therefore, measuring the averaged performance over all examples in held-out…
Towards Weakly-Supervised Hate Speech Classification Across Datasets
Yiping Jin, Leo Wanner, Vishakha Laxman Kadam +1
As pointed out by several scholars, current research on hate speech (HS) recognition is characterized by unsystematic data creation strategies and diverging annotation schemata. Su…
Plot Writing From Pre-Trained Language Models
Yiping Jin, Vishakha Kadam, Dittaya Wanvarie
Pre-trained language models (PLMs) fail to generate long-form narrative text because they do not consider global structure. As a result, the generated texts are often incohesive, r…
Seed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error Estimation
Yiping Jin, Akshay Bhatia, Dittaya Wanvarie
Weakly-supervised text classification aims to induce text classifiers from only a few user-provided seed words. The vast majority of previous work assumes high-quality seed words a…
Toward Improving Coherence and Diversity of Slogan Generation
Yiping Jin, Akshay Bhatia, Dittaya Wanvarie +1
Previous work in slogan generation focused on utilising slogan skeletons mined from existing slogans. While some generated slogans can be catchy, they are often not coherent with t…
Learning Only from Relevant Keywords and Unlabeled Documents
Nontawat Charoenphakdee, Jongyeong Lee, Yiping Jin +2
We consider a document classification problem where document labels are absent but only relevant keywords of a target class and unlabeled documents are given. Although heuristic me…