12 citations · 12 across the 5 of their papers we have counts for
5 papers
HSD: Training-Free Acceleration for Document Parsing Vision-Language Models with Hierarchical Speculative Decoding
Wenhui Liao, Hongliang Li, Pengyu Xie +15
Document parsing is a fundamental task in multimodal understanding, supporting a wide range of downstream applications such as information extraction and intelligent document analy…
RedundancyLens: Revealing and Exploiting Visual Token Processing Redundancy for Efficient Decoder-Only MLLMs
Hongliang Li, Jiaxin Zhang, Wenhui Liao +3
Current Multimodal Large Language Model (MLLM) architectures face a critical tradeoff between performance and efficiency: decoder-only architectures achieve higher performance but…
DocLayLLM: An Efficient Multi-modal Extension of Large Language Models for Text-rich Document Understanding
Wenhui Liao, Jiapeng Wang, Hongliang Li +3
Text-rich document understanding (TDU) requires comprehensive analysis of documents containing substantial textual content and complex layouts. While Multimodal Large Language Mode…
PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair Extraction
Zening Lin, Jiapeng Wang, Teng Li +4
Document pair extraction aims to identify key and value entities as well as their relationships from visually-rich documents. Most existing methods divide it into two separate task…
Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation
Yongxin Shi, Dezhi Peng, Wenhui Liao +5
This paper presents a comprehensive evaluation of the Optical Character Recognition (OCR) capabilities of the recently released GPT-4V(ision), a Large Multimodal Model (LMM). We as…