4 papers
Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs
Mahjabin Nahar, Nafis Irtiza Tripto, Aiping Xiong +2
As AI-generated and AI-assisted content floods online spaces, source labels attached to such content can distort human reasoning judgments, with downstream consequences for moderat…
Beyond checkmate: exploring the creative chokepoints in AI text
Nafis Irtiza Tripto, Saranya Venkatraman, Mahjabin Nahar +1
The rapid advancement of Large Language Models (LLMs) has revolutionized text generation but also raised concerns about potential misuse, making detecting LLM-generated text (AI te…
Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations
Mahjabin Nahar, Eun-Ju Lee, Jin Won Park +1
While we increasingly rely on large language models (LLMs) for various tasks, these models are known to produce inaccurate content or 'hallucinations' with potentially disastrous c…
Generative AI Policies under the Microscope: How CS Conferences Are Navigating the New Frontier in Scholarly Writing
Mahjabin Nahar, Sian Lee, Rebekah Guillen +1
As the use of Generative AI (Gen-AI) in scholarly writing and peer reviews continues to rise, it is essential for the computing field to establish and adopt clear Gen-AI policies.…