2 citations · 5 across the 9 of their papers we have counts for
9 papers
VisEditBench: Can Vision-Language Models Edit Visualization Code from Multimodal Feedback?
Mizanur Rahman, Arshia Azimlu, Shadikur Rahman +4
Vision-language models (VLMs) have shown strong capabilities in generating visualization code from textual or visual specifications. However, real-world visualization authoring is…
Learning to Fast Unrank in Collaborative Filtering Recommendation
Junpeng Zhao, Lin Li, Ming Li +2
Modern data-driven recommendation systems risk memorizing sensitive user behavioral patterns, raising privacy concerns. Existing recommendation unlearning methods, while capable of…
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…
LLM-Based Data Science Agents: A Survey of Capabilities, Challenges, and Future Directions
Mizanur Rahman, Amran Bhuiyan, Mohammed Saidul Islam +5
Recent advances in large language models (LLMs) have enabled a new class of AI agents that automate multiple stages of the data science workflow by integrating planning, tool use,…
Evolution of ReID: From Early Methods to LLM Integration
Amran Bhuiyan, Mizanur Rahman, Md Tahmid Rahman Laskar +2
Person re-identification (ReID) has evolved from handcrafted feature-based methods to deep learning approaches and, more recently, to models incorporating large language models (LL…
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…
A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations
Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari +10
Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough…
Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges
Jiajia Wang, Jimmy X. Huang, Xinhui Tu +4
Recent years have witnessed a substantial increase in the use of deep learning to solve various natural language processing (NLP) problems. Early deep learning models were constrai…
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…