4 citations · 11 across the 19 of their papers we have counts for
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Whose Data, Whose Benchmark? A User-Centric Framework for Auditing Evaluation Resources
Mir Tafseer Nayeem, Davood Rafiei
Benchmarks shape how model capabilities are measured and interpreted, yet their scores can obscure whose conventions, contexts, and judgments define successful performance. We intr…
CineSubBench: Evaluating LLMs on Long-Form Narrative and Cultural Understanding from Multilingual Movie Subtitles
Mir Tafseer Nayeem, Susmoy Chakraborty, Davood Rafiei
Large language models are increasingly evaluated in specialized domains such as law, medicine, software engineering, and cybersecurity, yet film remains comparatively underexplored…
Who Gets a Token, and What Does It Carry? Unequal Name Support and Concept Access in Large Language Models
Mir Tafseer Nayeem, Davood Rafiei
Names are personal identifiers, but they also carry social meaning and are widely used to evaluate how language models treat different people. Such evaluations typically assume tha…
SurveyAgent-HKA: A multi-agent framework for scientific survey generation with LLMs and human knowledge augmentation
Tong Bao, Mir Tafseer Nayeem, Yi Zhao +2
Automatic scientific survey generation has become an important task in scientific document processing. The common approach of retrieving literature from a single source (e.g., arXi…
Chart Deception in Vision-Language Models: From Vulnerability to Mitigation
Ridwan Mahbub, Mohammed Saidul Islam, Md Tahmid Rahman Laskar +3
Information visualizations are widely used to communicate patterns, trends, and outliers, yet deceptive design choices-such as truncated or inverted axes, distorted aspect ratios,…
How Does "English (US)" Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline
Mir Tafseer Nayeem, Davood Rafiei
Large language models (LLMs) are increasingly embedded in educational, professional, and public infrastructure, yet widely used platforms expose "English (US)" as a primary English…
Stop Taking Tokenizers for Granted: They Are Core Design Decisions in Large Language Models
Sawsan Alqahtani, Mir Tafseer Nayeem, Md Tahmid Rahman Laskar +2
Tokenization underlies every large language model, yet it remains an under-theorized and inconsistently designed component. Common subword approaches such as Byte Pair Encoding (BP…