most citedChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summaries

13 citations · 22 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20231 cited

Building Real-World Meeting Summarization Systems using Large Language Models: A Practical Perspective

Md Tahmid Rahman Laskar, Xue-Yong Fu, Cheng Chen +1

This paper studies how to effectively build meeting summarization systems for real-world usage using large language models (LLMs). For this purpose, we conduct an extensive evaluat…

cs.CL20232 cited

Are Large Language Models Reliable Judges? A Study on the Factuality Evaluation Capabilities of LLMs

Xue-Yong Fu, Md Tahmid Rahman Laskar, Cheng Chen +1

In recent years, Large Language Models (LLMs) have gained immense attention due to their notable emergent capabilities, surpassing those seen in earlier language models. A particul…

cs.CL2023

AI Coach Assist: An Automated Approach for Call Recommendation in Contact Centers for Agent Coaching

Md Tahmid Rahman Laskar, Cheng Chen, Xue-Yong Fu +3

In recent years, the utilization of Artificial Intelligence (AI) in the contact center industry is on the rise. One area where AI can have a significant impact is in the coaching o…

cs.CL202313 cited

ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summaries

Raian Rahman, Rizvi Hasan, Abdullah Al Farhad +3

Automatic chart to text summarization is an effective tool for the visually impaired people along with providing precise insights of tabular data in natural language to the user. A…

cs.CL20235 cited

CQSumDP: A ChatGPT-Annotated Resource for Query-Focused Abstractive Summarization Based on Debatepedia

Md Tahmid Rahman Laskar, Mizanur Rahman, Israt Jahan +2

Debatepedia is a publicly available dataset consisting of arguments and counter-arguments on controversial topics that has been widely used for the single-document query-focused ab…

cs.CL20211 cited

Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text Summarization

Md Tahmid Rahman Laskar, Enamul Hoque, Jimmy Xiangji Huang

The Query Focused Text Summarization (QFTS) task aims at building systems that generate the summary of the text document(s) based on the given query. A key challenge in addressing…