10 citations · 18 across the 14 of their papers we have counts for
4 papers · 1 filter
DocVLM: Make Your VLM an Efficient Reader
Mor Shpigel Nacson, Aviad Aberdam, Roy Ganz +5
Vision-Language Models (VLMs) excel in diverse visual tasks but face challenges in document understanding, which requires fine-grained text processing. While typical visual tasks p…
TAP-VL: Text Layout-Aware Pre-training for Enriched Vision-Language Models
Jonathan Fhima, Elad Ben Avraham, Oren Nuriel +4
Vision-Language (VL) models have garnered considerable research interest; however, they still face challenges in effectively handling text within images. To address this limitation…
Question Aware Vision Transformer for Multimodal Reasoning
Roy Ganz, Yair Kittenplon, Aviad Aberdam +4
Vision-Language (VL) models have gained significant research focus, enabling remarkable advances in multimodal reasoning. These architectures typically comprise a vision encoder, a…
GRAM: Global Reasoning for Multi-Page VQA
Tsachi Blau, Sharon Fogel, Roi Ronen +6
The increasing use of transformer-based large language models brings forward the challenge of processing long sequences. In document visual question answering (DocVQA), leading met…