6 citations · 6 across the 6 of their papers we have counts for
6 papers
HIVE: Query, Hypothesize, Verify An LLM Framework for Multimodal Reasoning-Intensive Retrieval
Mahmoud Abdalla, Mahmoud SalahEldin Kasem, Mohamed Mahmoud +3
Multimodal retrieval models fail on reasoning-intensive queries where images (diagrams, charts, screenshots) must be deeply integrated with text to identify relevant documents -- t…
BRIDGE: Multimodal-to-Text Retrieval via Reinforcement-Learned Query Alignment
Mohamed Darwish Mounis, Mohamed Mahmoud, Shaimaa Sedek +4
Multimodal retrieval systems struggle to resolve image-text queries against text-only corpora: the best vision-language encoder achieves only 27.6 nDCG@10 on MM-BRIGHT, underperfor…
MARVEL: Multimodal Adaptive Reasoning-intensiVe Expand-rerank and retrievaL
Mahmoud SalahEldin Kasem, Mohamed Mahmoud, Mostafa Farouk Senussi +3
Multimodal retrieval over text corpora remains a fundamental challenge: the best vision-language encoder achieves only 27.6 nDCG@10 on MM-BRIGHT, a reasoning-intensive multimodal r…
MM-BRIGHT: A Multi-Task Multimodal Benchmark for Reasoning-Intensive Retrieval
Abdelrahman Abdallah, Mohamed Darwish Mounis, Mahmoud Abdalla +6
Existing retrieval benchmarks primarily consist of text-based queries where keyword or semantic matching is usually sufficient. Many real-world queries contain multimodal elements,…
RetoVLA: Reusing Register Tokens for Spatial Reasoning in Vision-Language-Action Models
Jiyeon Koo, Taewan Cho, Hyunjoon Kang +4
Vision-Language-Action (VLA) models have demonstrated robust performance across diverse robotic tasks. However, their high memory and computational demands often limit real-time de…
Advancements and Challenges in Arabic Optical Character Recognition: A Comprehensive Survey
Mahmoud SalahEldin Kasem, Mohamed Mahmoud, Hyun-Soo Kang
Optical character recognition (OCR) is a vital process that involves the extraction of handwritten or printed text from scanned or printed images, converting it into a format that…