73 citations · 89 across the 10 of their papers we have counts for
10 papers
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models
Geewook Kim, Hodong Lee, Daehee Kim +7
Recent advances in Large Language Models (LLMs) have stimulated a surge of research aimed at extending their applications to the visual domain. While these models exhibit promise i…
Semi-Structured Query Grounding for Document-Oriented Databases with Deep Retrieval and Its Application to Receipt and POI Matching
Geewook Kim, Wonseok Hwang, Minjoon Seo +1
Semi-structured query systems for document-oriented databases have many real applications. One particular application that we are interested in is matching each financial receipt i…
OCR-free Document Understanding Transformer
Geewook Kim, Teakgyu Hong, Moonbin Yim +7
Understanding document images (e.g., invoices) is a core but challenging task since it requires complex functions such as reading text and a holistic understanding of the document.…
Revisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings
Masahiro Naito, Sho Yokoi, Geewook Kim +1
It is well-known that typical word embedding methods such as Word2Vec and GloVe have the property that the meaning can be composed by adding up the embeddings (additive composition…
Cost-effective End-to-end Information Extraction for Semi-structured Document Images
Wonseok Hwang, Hyunji Lee, Jinyeong Yim +2
A real-world information extraction (IE) system for semi-structured document images often involves a long pipeline of multiple modules, whose complexity dramatically increases its…
Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization
Morihiro Mizutani, Akifumi Okuno, Geewook Kim +1
Multimodal relational data analysis has become of increasing importance in recent years, for exploring across different domains of data, such as images and their text tags obtained…
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
Jeonghun Baek, Geewook Kim, Junyeop Lee +5
Many new proposals for scene text recognition (STR) models have been introduced in recent years. While each claim to have pushed the boundary of the technology, a holistic and fair…
Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities
Geewook Kim, Akifumi Okuno, Kazuki Fukui +1
We propose (WIPS) for neural network-based graph embedding. In addition to the parameters of neural networks, we optimize the weights o…
Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability
Akifumi Okuno, Geewook Kim, Hidetoshi Shimodaira
We propose shifted inner-product similarity (SIPS), which is a novel yet very simple extension of the ordinary inner-product similarity (IPS) for neural-network based graph embeddi…
Segmentation-free Compositional -gram Embedding
Geewook Kim, Kazuki Fukui, Hidetoshi Shimodaira
We propose a new type of representation learning method that models words, phrases and sentences seamlessly. Our method does not depend on word segmentation and any human-annotated…