Feiyu Gao
12 papers · 2019–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Cross-Pollinator (15) π§ Keyword Pioneer π£ Hot Topic Early Bird π Conference Polyglot (7) π Academic Marathon (6)
π
Renaissance Researcher
(5)
π
Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(19)
π
Century Club
(12)
β
The Questioner
Conferences
EMNLP (4)
ECCV (3)
AAAI (1)
COLING (1)
CVPR (1)
ICCV (1)
NAACL (1)
Top co-authors
Keywords
document understanding
(5)
visual information
(2)
multimodal learning
(2)
document parsing
(2)
cell detection
(2)
information extraction
(2)
multi-modal large language model
(1)
multimodal large language model
(1)
positional encoding
(1)
graph convolution
(1)
table structure recognition
(1)
cross-modality learning
(1)
entity extraction
(1)
graph convolutional network
(1)
visual document understanding
(1)
knowledge conflict
(1)
visually rich document
(1)
layout analysis
(1)
large language model
(1)
cognition perception
(1)
Papers
Intelligent Document Parsing: Towards End-to-end Document Parsing via Decoupled Content Parsing and Layout Grounding
EMNLP 2025
A Simple yet Effective Layout Token in Large Language Models for Document Understanding
CVPR 2025
Is Cognition Consistent with Perception? Assessing and Mitigating Multimodal Knowledge Conflicts in Document Understanding
EMNLP 2025
DocHieNet: A Large and Diverse Dataset for Document Hierarchy Parsing
EMNLP 2024
WebRPG: Automatic Web Rendering Parameters Generation for Visual Presentation
ECCV 2024
Visual Text Generation in the Wild
ECCV 2024
LORE: Logical Location Regression Network for Table Structure Recognition
AAAI 2023
GEM: Gestalt Enhanced Markup Language Model for Web Understanding via Render Tree
EMNLP 2023
Parsing Table Structures in the Wild
ICCV 2021
An End-to-End OCR Text Re-organization Sequence Learning for Rich-text Detail Image Comprehension
ECCV 2020
Merge and Recognize: A Geometry and 2D Context Aware Graph Model for Named Entity Recognition from Visual Documents
COLING 2020
Graph Convolution for Multimodal Information Extraction from Visually Rich Documents
NAACL 2019