activity
20242026
most citedAlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding

1 citations · 1 across the 6 of their papers we have counts for

collaborators
Showing cs.CLShow all

18 papers · 1 filter

cs.CL2026

Training Therapeutic Judges and Multi-Agent Systems for Human-Aligned Mental Health Support

Mizanur Rahman, Abeer Badawi, Elahe Rahimi +4

Large language models show promise for mental health support, yet therapeutic quality improves only when evaluation functions as an actionable control signal rather than a passive…

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

ColMate: Contrastive Late Interaction and Masked Text for Multimodal Document Retrieval

Ahmed Masry, Megh Thakkar, Patrice Bechard +9

Retrieval-augmented generation has proven practical when models require specialized knowledge or access to the latest data. However, existing methods for multimodal document retrie…

cs.CL2025

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding

Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang +19

Aligning visual features with language embeddings is a key challenge in vision-language models (VLMs). The performance of such models hinges on having a good connector that maps vi…

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…

cs.CL2025

DashboardQA: Benchmarking Multimodal Agents for Question Answering on Interactive Dashboards

Aaryaman Kartha, Ahmed Masry, Mohammed Saidul Islam +8

Dashboards are powerful visualization tools for data-driven decision-making, integrating multiple interactive views that allow users to explore, filter, and navigate data. Unlike s…