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Mir Tafseer Nayeem

8 accepted papers

2025

From Charts to Fair Narratives: Uncovering and Mitigating Geo-Economic Biases in Chart-to-Text

Ridwan Mahbub, Mohammed Saidul Islam, Mir Tafseer Nayeem, Md Tahmid Rahman Laskar, Mizanur Rahman, Shafiq Joty +1
EMNLP 2025

Charts are very common for exploring dataand communicating insights, but extracting key takeaways from charts and articulating them in natural language can be challenging. The chart-to-text task aims to automate this process by generating textual summaries of charts. While with the rapid advancement

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2025

SurveyGen: Quality-Aware Scientific Survey Generation with Large Language Models

Tong Bao, Mir Tafseer Nayeem, Davood Rafiei, Chengzhi Zhang
EMNLP 2025

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 of standardized evaluation datasets critically hampers rigorous assessment of their performance against human-written su

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2025

eC-Tab2Text: Aspect-Based Text Generation from e-Commerce Product Tables

Luis Antonio Gutierrez Guanilo, Mir Tafseer Nayeem, Cristian Jose Lopez Del Alamo, Davood Rafiei
NAACL 2025industry

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-specific datasets. To address this gap, we introduce eC-Tab2Text, a novel dataset designed to capture the intricacies of e-…

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2024

Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning

Mohammed Saidul Islam, Raian Rahman, Ahmed Masry, Md Tahmid Rahman Laskar, Mir Tafseer Nayeem, Enamul Hoque
EMNLP 2024finding

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 language, various downstream tasks have been introduced recently such as chart question answering, chart summarization, and f…

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2024

BenLLM-Eval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP

Mohsinul Kabir, Mohammed Saidul Islam, Md Tahmid Rahman Laskar, Mir Tafseer Nayeem, M Saiful Bari, Enamul Hoque
COLING 2024main

Large Language Models (LLMs) have emerged as one of the most important breakthroughs in natural language processing (NLP) for their impressive skills in language generation and other language-specific tasks. Though LLMs have been evaluated in various tasks, mostly in English, they have not yet under…

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2024

KidLM: Advancing Language Models for Children – Early Insights and Future Directions

Mir Tafseer Nayeem, Davood Rafiei
EMNLP 2024main

Recent studies highlight the potential of large language models in creating educational tools for children, yet significant challenges remain in maintaining key child-specific properties such as linguistic nuances, cognitive needs, and safety standards. In this paper, we explore foundational steps t…

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2024

XL-HeadTags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tags

Faisal Tareque Shohan, Mir Tafseer Nayeem, Samsul Islam, Abu Ubaida Akash, Shafiq Joty
ACL 2024findings

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 time. While headline generation has been extensively studied, tag generation remains largely unexplored, yet it offers r…

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2021

Simple or Complex? Learning to Predict Readability of Bengali Texts

Susmoy Chakraborty, Mir Tafseer Nayeem, Wasi Uddin Ahmad
AAAI 2021technical

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 Bengali language to provide in-depth information on its readability and complexity. Despite being the 7th most spoken language…

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