7 papers
The MediaSpin Dataset: Post-Publication News Headline Edits Annotated for Media Bias
Preetika Verma, Kokil Jaidka
We present MediaSpin, a large-scale language resource capturing how major news outlets modify headlines after publication, and MediaSpin-in-the-Wild, a complementary dataset linkin…
GitSearch: Enhancing Community Notes Generation with Gap-Informed Targeted Search
Sahajpreet Singh, Kokil Jaidka, Min-Yen Kan
Community-based moderation offers a scalable alternative to centralized fact-checking, yet it faces significant structural challenges, and existing AI-based methods fail in "cold s…
Layer of Truth: Probing Belief Shifts under Continual Pre-Training Poisoning
Svetlana Churina, Niranjan Chebrolu, Kokil Jaidka
We show that continual pretraining on plausible misinformation can overwrite specific factual knowledge in large language models without degrading overall performance. Unlike prior…
Incivility and Rigidity: Evaluating the Risks of Fine-Tuning LLMs for Political Argumentation
Svetlana Churina, Kokil Jaidka
Incivility on platforms such as Twitter (now X) and Reddit complicates the development of AI systems that can support productive, rhetorically sound political argumentation. We pre…
Improving User Behavior Prediction: Leveraging Annotator Metadata in Supervised Machine Learning Models
Lynnette Hui Xian Ng, Kokil Jaidka, Kaiyuan Tay +2
Supervised machine-learning models often underperform in predicting user behaviors from conversational text, hindered by poor crowdsourced label quality and low NLP task accuracy.…
"Reasoning" with Rhetoric: On the Style-Evidence Tradeoff in LLM-Generated Counter-Arguments
Preetika Verma, Kokil Jaidka, Svetlana Churina
Large language models (LLMs) play a key role in generating evidence-based and stylistic counter-arguments, yet their effectiveness in real-world applications has been underexplored…