4 citations · 11 across the 19 of their papers we have counts for
8 papers · 1 filter
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…