4 citations · 11 across the 19 of their papers we have counts for
25 papers
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…
OpinioRAG: Towards Generating User-Centric Opinion Highlights from Large-scale Online Reviews
Mir Tafseer Nayeem, Davood Rafiei
We study the problem of opinion highlights generation from large volumes of user reviews, often exceeding thousands per entity, where existing methods either fail to scale or produ…
Beyond Fertility: Analyzing STRR as a Metric for Multilingual Tokenization Evaluation
Mir Tafseer Nayeem, Sawsan Alqahtani, Md Tahmid Rahman Laskar +2
Tokenization is a crucial but under-evaluated step in large language models (LLMs). The standard metric, fertility (the average number of tokens per word), captures compression eff…
Deploying Tiny LVLM Judges for Real-World Evaluation of Chart Models: Lessons Learned and Best Practices
Md Tahmid Rahman Laskar, Mohammed Saidul Islam, Ridwan Mahbub +7
Large Vision-Language Models (LVLMs) with only 7B parameters have shown promise as automated judges in chart comprehension tasks. However, tiny models (<=2B parameters) still perfo…
SurveyGen: Quality-Aware Scientific Survey Generation with Large Language Models
Tong Bao, Mir Tafseer Nayeem, Davood Rafiei +1
Automatic survey generation has emerged as a key task in scientific document processing. While large language models (LLMs) have shown promise in generating survey texts, the lack…
The Perils of Chart Deception: How Misleading Visualizations Affect Vision-Language Models
Ridwan Mahbub, Mohammed Saidul Islam, Md Tahmid Rahman Laskar +3
Information visualizations are powerful tools that help users quickly identify patterns, trends, and outliers, facilitating informed decision-making. However, when visualizations i…
From Charts to Fair Narratives: Uncovering and Mitigating Geo-Economic Biases in Chart-to-Text
Ridwan Mahbub, Mohammed Saidul Islam, Mir Tafseer Nayeem +4
Charts are very common for exploring data and communicating insights, but extracting key takeaways from charts and articulating them in natural language can be challenging. The cha…
Judging the Judges: Can Large Vision-Language Models Fairly Evaluate Chart Comprehension and Reasoning?
Md Tahmid Rahman Laskar, Mohammed Saidul Islam, Ridwan Mahbub +7
Charts are ubiquitous as they help people understand and reason with data. Recently, various downstream tasks, such as chart question answering, chart2text, and fact-checking, have…
eC-Tab2Text: Aspect-Based Text Generation from e-Commerce Product Tables
Luis Antonio Gutiérrez Guanilo, Mir Tafseer Nayeem, Cristian López +1
Large Language Models (LLMs) have demonstrated exceptional versatility across diverse domains, yet their application in e-commerce remains underexplored due to a lack of domain-spe…
LFOSum: Summarizing Long-form Opinions with Large Language Models
Mir Tafseer Nayeem, Davood Rafiei
Online reviews play a pivotal role in influencing consumer decisions across various domains, from purchasing products to selecting hotels or restaurants. However, the sheer volume…
KidLM: Advancing Language Models for Children -- Early Insights and Future Directions
Mir Tafseer Nayeem, Davood Rafiei
Recent studies highlight the potential of large language models in creating educational tools for children, yet significant challenges remain in maintaining key child-specific prop…
XL-HeadTags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tags
Faisal Tareque Shohan, Mir Tafseer Nayeem, Samsul Islam +2
Millions of news articles published online daily can overwhelm readers. Headlines and entity (topic) tags are essential for guiding readers to decide if the content is worth their…
Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs
Mohammed Saidul Islam, Raian Rahman, Ahmed Masry +3
Natural language is a powerful complementary modality of communication for data visualizations, such as bar and line charts. To facilitate chart-based reasoning using natural langu…
BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP
Mohsinul Kabir, Mohammed Saidul Islam, Md Tahmid Rahman Laskar +3
Large Language Models (LLMs) have emerged as one of the most important breakthroughs in NLP for their impressive skills in language generation and other language-specific tasks. Th…
On the Role of Reviewer Expertise in Temporal Review Helpfulness Prediction
Mir Tafseer Nayeem, Davood Rafiei
Helpful reviews have been essential for the success of e-commerce services, as they help customers make quick purchase decisions and benefit the merchants in their sales. While man…
Unsupervised Abstractive Summarization of Bengali Text Documents
Radia Rayan Chowdhury, Mir Tafseer Nayeem, Tahsin Tasnim Mim +2
Abstractive summarization systems generally rely on large collections of document-summary pairs. However, the performance of abstractive systems remains a challenge due to the unav…
Simple or Complex? Learning to Predict Readability of Bengali Texts
Susmoy Chakraborty, Mir Tafseer Nayeem, Wasi Uddin Ahmad
Determining the readability of a text is the first step to its simplification. In this paper, we present a readability analysis tool capable of analyzing text written in the Bengal…
Extract with Order for Coherent Multi-Document Summarization
Mir Tafseer Nayeem, Yllias Chali
In this work, we aim at developing an extractive summarizer in the multi-document setting. We implement a rank based sentence selection using continuous vector representations alon…