8 citations · 10 across the 14 of their papers we have counts for
17 papers
Chatbot Engagement Does Not Always Beget Metalearning: Evidence from Three Countries
Kokil Jaidka, Insyirah Binte Imam Mujtahid, Peng Qi +5
Chatbots deliver real-time fact-checks, but whether a chatbot correction leaves anything behind once the chatbot is gone - metalearning, distinct from correcting misbeliefs - is un…
Durably Reducing Belief in Women's Health Misinformation Through Culturally Adaptive AI Videos
Anku Rani, Kokil Jaidka, Shruti Sharma +5
Health misinformation disproportionately harms women, yet interventions rarely address the community norms that sustain false beliefs. We test whether culturally adaptive AI-genera…
How Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment
Kokil Jaidka, Saifuddin Ahmed
This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView. The intervention, conducted by unknown, external researchers and ha…
CommunityFact: A Dynamic, Multilingual, Multi-domain Benchmark for Misinformation Detection in the Wild
Sahajpreet Singh, Insyirah Mujtahid, Min-Yen Kan +1
Misinformation verification increasingly occurs in public, fast-moving, and multilingual online settings, where static benchmarks provide an incomplete measure of model reliability…
Althea: The Fact-Checking--Metalearning Tradeoff in AI-Assisted Verification
Svetlana Churina, Kokil Jaidka, Anab Maulana Barik +5
Fact-checking systems must be scalable and epistemically trustworthy. We introduce Althea, a retrieval-augmented system for user-driven claim evaluation that matches standard pipel…
Learning Through Dialogue: Engagement and Efficacy Matter More Than Explanations
Shaz Furniturewala, Gerard Christopher Yeo, Kokil Jaidka
Large language models (LLMs) are increasingly used as conversational partners for learning, yet the interactional dynamics supporting users' learning and engagement are understudie…
Do You Trust Me? Cognitive-Affective Signatures of Trustworthiness in Large Language Models
Gerard Yeo, Svetlana Churina, Kokil Jaidka
Perceived trustworthiness underpins how users navigate online information, yet it remains unclear whether large language models (LLMs),increasingly embedded in search, recommendati…
From Passive to Persuasive: Localized Activation Injection for Empathy and Negotiation
Niranjan Chebrolu, Kokil Jaidka, Gerard Christopher Yeo
Complex social behaviors, such as empathy and strategic politeness, are widely assumed to resist the directional decomposition that makes activation steering effective for coarse a…
Labels or Input? Rethinking Augmentation in Multimodal Hate Detection
Sahajpreet Singh, Kokil Jaidka, Subhayan Mukerjee
Online hate remains a significant societal challenge, especially as multimodal content enables subtle, culturally grounded, and implicit forms of harm. Hateful memes embed hostilit…
Disentangling Codemixing in Chats: The NUS ABC Codemixed Corpus
Svetlana Churina, Akshat Gupta, Insyirah Mujtahid +1
Code-mixing involves the seamless integration of linguistic elements from multiple languages within a single discourse, reflecting natural multilingual communication patterns. Desp…
Beyond Context to Cognitive Appraisal: Emotion Reasoning as a Theory of Mind Benchmark for Large Language Models
Gerard Christopher Yeo, Kokil Jaidka
Datasets used for emotion recognition tasks typically contain overt cues that can be used in predicting the emotions expressed in a text. However, one challenge is that texts somet…
On the Limitations of Steering in Language Model Alignment
Chebrolu Niranjan, Kokil Jaidka, Gerard Christopher Yeo
Steering vectors are a promising approach to aligning language model behavior at inference time. In this paper, we propose a framework to assess the limitations of steering vectors…
Conversations: Love Them, Hate Them, Steer Them
Niranjan Chebrolu, Gerard Christopher Yeo, Kokil Jaidka
Large Language Models (LLMs) demonstrate increasing conversational fluency, yet instilling them with nuanced, human-like emotional expression remains a significant challenge. Curre…
Hateful Meme Detection through Context-Sensitive Prompting and Fine-Grained Labeling
Rongxin Ouyang, Kokil Jaidka, Subhayan Mukerjee +1
The prevalence of multi-modal content on social media complicates automated moderation strategies. This calls for an enhancement in multi-modal classification and a deeper understa…
LLMs and Finetuning: Benchmarking cross-domain performance for hate speech detection
Ahmad Nasir, Aadish Sharma, Kokil Jaidka +1
In the evolving landscape of online communication, hate speech detection remains a formidable challenge, further compounded by the diversity of digital platforms. This study invest…
Predicting Sentence-Level Factuality of News and Bias of Media Outlets
Francielle Vargas, Kokil Jaidka, Thiago A. S. Pardo +1
Automated news credibility and fact-checking at scale require accurately predicting news factuality and media bias. This paper introduces a large sentence-level dataset, titled "Fa…
Just Another Day on Twitter: A Complete 24 Hours of Twitter Data
Juergen Pfeffer, Daniel Matter, Kokil Jaidka +13
At the end of October 2022, Elon Musk concluded his acquisition of Twitter. In the weeks and months before that, several questions were publicly discussed that were not only of int…