22 citations · 26 across the 7 of their papers we have counts for
8 papers
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…
How Well Do Large Language Models Understand Syntax? An Evaluation by Asking Natural Language Questions
Houquan Zhou, Yang Hou, Zhenghua Li +4
While recent advancements in large language models (LLMs) bring us closer to achieving artificial general intelligence, the question persists: Do LLMs truly understand language, or…
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…
Learning node embeddings via summary graphs: a brief theoretical analysis
Houquan Zhou, Shenghua Liu, Danai Koutra +2
Graph representation learning plays an important role in many graph mining applications, but learning embeddings of large-scale graphs remains a problem. Recent works try to improv…
Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging
Houquan Zhou, Yang Li, Zhenghua Li +1
In recent years, large-scale pre-trained language models (PLMs) have made extraordinary progress in most NLP tasks. But, in the unsupervised POS tagging task, works utilizing PLMs…
An In-depth Study on Internal Structure of Chinese Words
Chen Gong, Saihao Huang, Houquan Zhou +5
Unlike English letters, Chinese characters have rich and specific meanings. Usually, the meaning of a word can be derived from its constituent characters in some way. Several previ…