activity
20242026
collaborators

15 papers

cs.AI2026

DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments?

Mizanur Rahman, Mohammed Saidul Islam, Ridwan Mahbub +3

Real-world data science involves long-horizon workflows that span data wrangling, exploration, modeling, visualization, and validation, and require coordinated use of tools such as…

cs.AI2026

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,…

cs.LG2026

Fine-Grained Benchmark Generation for Comprehensive Evaluation of Foundation Models

Mohammed Saidul Islam, Negin Baghbanzadeh, Farnaz Kohankhaki +5

Evaluation of foundation models often rely on aggregate scores from benchmarks that lack comprehensive coverage and metadata for a fine-grained evaluation. We introduce a framework…

cs.CL2026

BanglaSummEval: Reference-Free Factual Consistency Evaluation for Bangla Summarization

Ahmed Rafid, Rumman Adib, Fariya Ahmed +2

Evaluating factual consistency is essential for reliable text summarization, particularly in high-stakes domains such as healthcare and news. However, most existing evaluation metr…

cs.CL2026

Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization

Mizanur Rahman, Mohammed Saidul Islam, Md Tahmid Rahman Laskar +2

Text-to-Visualization (Text2Vis) systems translate natural language queries over tabular data into concise answers and executable visualizations. While closed-source LLMs generate…

cs.CL2025

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…