3 citations · 8 across the 9 of their papers we have counts for
9 papers
A Training-free LLM-based Approach to General Chinese Character Error Correction
Houquan Zhou, Bo Zhang, Zhenghua Li +2
Chinese spelling correction (CSC) is a crucial task that aims to correct character errors in Chinese text. While conventional CSC focuses on character substitution errors caused by…
DISC: Plug-and-Play Decoding Intervention with Similarity of Characters for Chinese Spelling Check
Ziheng Qiao, Houquan Zhou, Yumeng Liu +6
One key characteristic of the Chinese spelling check (CSC) task is that incorrect characters are usually similar to the correct ones in either phonetics or glyph. To accommodate th…
A Simple yet Effective Training-free Prompt-free Approach to Chinese Spelling Correction Based on Large Language Models
Houquan Zhou, Zhenghua Li, Bo Zhang +5
This work proposes a simple training-free prompt-free approach to leverage large language models (LLMs) for the Chinese spelling correction (CSC) task, which is totally different f…
mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding
Anwen Hu, Haiyang Xu, Jiabo Ye +8
Structure information is critical for understanding the semantics of text-rich images, such as documents, tables, and charts. Existing Multimodal Large Language Models (MLLMs) for…
Improving Seq2Seq Grammatical Error Correction via Decoding Interventions
Houquan Zhou, Yumeng Liu, Zhenghua Li +5
The sequence-to-sequence (Seq2Seq) approach has recently been widely used in grammatical error correction (GEC) and shows promising performance. However, the Seq2Seq GEC approach s…
NaSGEC: a Multi-Domain Chinese Grammatical Error Correction Dataset from Native Speaker Texts
Yue Zhang, Bo Zhang, Haochen Jiang +4
We introduce NaSGEC, a new dataset to facilitate research on Chinese grammatical error correction (CGEC) for native speaker texts from multiple domains. Previous CGEC research prim…
Mining Error Templates for Grammatical Error Correction
Yue Zhang, Haochen Jiang, Zuyi Bao +3
Some grammatical error correction (GEC) systems incorporate hand-crafted rules and achieve positive results. However, manually defining rules is time-consuming and laborious. In vi…
MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction
Yue Zhang, Zhenghua Li, Zuyi Bao +5
This paper presents MuCGEC, a multi-reference multi-source evaluation dataset for Chinese Grammatical Error Correction (CGEC), consisting of 7,063 sentences collected from three Ch…
Entity Relation Extraction as Dependency Parsing in Visually Rich Documents
Yue Zhang, Bo Zhang, Rui Wang +3
Previous works on key information extraction from visually rich documents (VRDs) mainly focus on labeling the text within each bounding box (i.e., semantic entity), while the relat…