11 citations · 11 across the 6 of their papers we have counts for
8 papers
One Model Is Not a Crowd: Multi-LLM and Aspect-Conditioned Diverse Comment Generation
Nafis Irtiza Tripto, Delvin Ce Zhang, Mahjabin Nahar +1
Human communication on the internet is shaped by diverse perspectives, most visibly expressed in online comment spaces. As large language model (LLM)based AI agents begin to inhabi…
When AI Says "I Am Unable to Answer": Understanding User Responses to AI Refusals
Mahjabin Nahar, Eun-Ju Lee, Yujin Heo +1
While refusal-based safeguards to mitigate hallucinations in large language models (LLMs) are becoming increasingly common, they may conflict with users' preferences for definitive…
TRILOGUE: A Trilingual Spoken Dialogue Fact-Checking Benchmark with Evidence and Paired Audio
Chaewan Chun, Meruyert Aristombayeva, Jiyoung Choi +3
Modern misinformation is often heard before it is read, yet fact-checking systems are still evaluated mainly on clean written claims. Spoken dialogue remains different even when sy…
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…
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…
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…
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.…
Fakes of Varying Shades: How Warning Affects Human Perception and Engagement Regarding LLM Hallucinations
Mahjabin Nahar, Haeseung Seo, Eun-Ju Lee +2
The widespread adoption and transformative effects of large language models (LLMs) have sparked concerns regarding their capacity to produce inaccurate and fictitious content, refe…