Author

Mahjabin Nahar

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#natural language process... Sep 2026

One Model Is Not a Crowd: Multi-LLM and Aspect-Conditioned Diverse Comment Generation

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 inhabit these spaces, a key question arises: whether synthetic comment threads can capture the diversity inherent in human discourse. This concern...

N. Tripto, Delvin Ce Zhang, Mahjabin Nahar et al. · arXiv.org · 0 citations

#human-computer interacti... Preprint Sep 2026

When AI Says"I Am Unable to Answer": Understanding User Responses to AI Refusals

A tension between hallucination avoidance and user satisfaction is revealed and the importance of designing balanced refusal strategies is highlighted, to highlight the importance of designing balanced refusal strategies.

Mahjabin Nahar, Eun-Ju Lee, Yujin Heo et al. · 0 citations

#natural language process... Preprint Sep 2026

TRILOGUE: A Trilingual Spoken Dialogue Fact-Checking Benchmark with Evidence and Paired Audio

TRILOGUE (TRIlingual spoken diaLOGUE fact-checking) is introduced, a large-scale trilingual benchmark of source-grounded spoken dialogues in English, Russian, and Kazakh that supports claim check-worthiness detection, source-article evidence retrieval, and claim verification with claim-only, gold-evidence, and retrieve...

Chaewan Chun, Meruyert Aristombayeva, Jiyoung Choi et al. · 0 citations