collaborators

5 papers

cs.DC2026

Why Smaller Is Slower? Dimensional Misalignment in Compressed LLMs

Jihao Xin, Tian Lyu, Qilong Pan +2

Post-training compression reduces LLM parameter counts but often produces irregular tensor dimensions that degrade GPU performance -- a phenomenon we call \emph{dimensional misalig…

cs.CL2025

Cross-Lingual SynthDocs: A Large-Scale Synthetic Corpus for Any to Arabic OCR and Document Understanding

Haneen Al-Homoud, Asma Ibrahim, Murtadha Al-Jubran +5

Cross-Lingual SynthDocs is a large-scale synthetic corpus designed to address the scarcity of Arabic resources for Optical Character Recognition (OCR) and Document Understanding (D…

cs.CL2025

A-SEA3L-QA: A Fully Automated Self-Evolving, Adversarial Workflow for Arabic Long-Context Question-Answer Generation

Kesen Wang, Daulet Toibazar, Pedro J. Moreno

We present an end-to-end, self-evolving adversarial workflow for long-context Question-Answer (QA) Generation in Arabic. By orchestrating multiple specialized LVLMs: a question gen…

cs.CV2025

Trust the Model: Compact VLMs as In-Context Judges for Image-Text Data Quality

Daulet Toibazar, Kesen Wang, Sherif Mohamed +3

Vision-language models (VLMs) extend the conventional large language models by integrating visual data, enabling richer multimodal reasoning and significantly broadens the practica…

cs.CL2025

Multi-Agent Interactive Question Generation Framework for Long Document Understanding

Kesen Wang, Daulet Toibazar, Abdulrahman Alfulayt +6

Document Understanding (DU) in long-contextual scenarios with complex layouts remains a significant challenge in vision-language research. Although Large Vision-Language Models (LV…