3 citations · 5 across the 8 of their papers we have counts for
8 papers
MPDocBench-Parse: Benchmarking Practical Multi-page Document Parsing
Bangbang Zhou, Hangdi Xing, Yifan Chen +8
Document parsing converts visually rich documents into machine-readable structured representations, forming a crucial foundation for information systems. Although many benchmarks h…
Test-Time Scaling with Reflective Generative Model
Zixiao Wang, Yuxin Wang, Xiaorui Wang +8
We introduce our first reflective generative model MetaStone-S1, which obtains OpenAI o3-mini's performance via the new Reflective Generative Form. The new form focuses on high-qua…
GRIP: A Graph-Based Reasoning Instruction Producer
Jiankang Wang, Jianjun Xu, Xiaorui Wang +4
Large-scale, high-quality data is essential for advancing the reasoning capabilities of large language models (LLMs). As publicly available Internet data becomes increasingly scarc…
Self-Supervised Pre-training with Symmetric Superimposition Modeling for Scene Text Recognition
Zuan Gao, Yuxin Wang, Yadong Qu +4
In text recognition, self-supervised pre-training emerges as a good solution to reduce dependence on expansive annotated real data. Previous studies primarily focus on local visual…
Symmetrical Linguistic Feature Distillation with CLIP for Scene Text Recognition
Zixiao Wang, Hongtao Xie, Yuxin Wang +3
In this paper, we explore the potential of the Contrastive Language-Image Pretraining (CLIP) model in scene text recognition (STR), and establish a novel Symmetrical Linguistic Fea…
VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering
Zijun Yao, Yuanyong Chen, Xin Lv +8
We present Visual Knowledge oriented Programming platform (VisKoP), a knowledge base question answering (KBQA) system that integrates human into the loop to edit and debug the know…
Linguistic More: Taking a Further Step toward Efficient and Accurate Scene Text Recognition
Boqiang Zhang, Hongtao Xie, Yuxin Wang +2
Vision model have gained increasing attention due to their simplicity and efficiency in Scene Text Recognition (STR) task. However, due to lacking the perception of linguistic know…
Exploring Stroke-Level Modifications for Scene Text Editing
Yadong Qu, Qingfeng Tan, Hongtao Xie +3
Scene text editing (STE) aims to replace text with the desired one while preserving background and styles of the original text. However, due to the complicated background textures…