Search Results for author: Cunliang Kong

Found 14 papers, 5 papers with code

基于BERT与柱搜索的中文释义生成(Chinese Definition Modeling Based on BERT and Beam Seach)

no code implementations CCL 2020 Qinan Fan, Cunliang Kong, Liner Yang, Erhong Yang

释义生成任务是指为一个目标词生成相应的释义。前人研究中文释义生成任务时未考虑目标词的上下文, 本文首次在中文释义生成任务中使用了目标词的上下文信息, 并提出了一个基于BERT与柱搜索的释义生成模型。本文构建了包含上下文的CWN中文数据集用于开展实验, 除了BLEU指标之外, 还使用语义相似度作为额外的自动评价指标, 实验结果显示本文模型在中文CWN数据集和英文Oxford数据集上均有显著提升, 人工评价结果也与自动评价结果一致。最后, 本文对生成实例进行了深入分析。

Cross-domain Chinese Sentence Pattern Parsing

no code implementations26 Feb 2024 Jingsi Yu, Cunliang Kong, Liner Yang, Meishan Zhang, Lin Zhu, Yujie Wang, Haozhe Lin, Maosong Sun, Erhong Yang

Sentence Pattern Structure (SPS) parsing is a syntactic analysis method primarily employed in language teaching. Existing SPS parsers rely heavily on textbook corpora for training, lacking cross-domain capability. To overcome this constraint, this paper proposes an innovative approach leveraging large language models (LLMs) within a self-training framework.

Sentence

OMGEval: An Open Multilingual Generative Evaluation Benchmark for Large Language Models

no code implementations21 Feb 2024 Meng Xu, Shuo Wang, Liner Yang, Haoyu Wang, Zhenghao Liu, Cunliang Kong, Yun Chen, Yang Liu, Maosong Sun, Erhong Yang

We evaluate several representative multilingual LLMs on the proposed OMGEval, which we believe will provide a valuable reference for the community to further understand and improve the multilingual capability of LLMs.

General Knowledge Logical Reasoning

Lexical Complexity Controlled Sentence Generation

no code implementations26 Nov 2022 Jinran Nie, Liner Yang, Yun Chen, Cunliang Kong, Junhui Zhu, Erhong Yang

Compared with potential solutions, our approach fuses the representations of the word complexity levels into the model to get better control of lexical complexity.

Sentence Text Generation

LitMind Dictionary: An Open-Source Online Dictionary

1 code implementation23 Apr 2022 Cunliang Kong, Xuezhi Fang, Liner Yang, Yun Chen, Erhong Yang

Since traditional dictionaries present word senses as discrete items in predefined inventories, they fall short of flexibility, which is required in providing specific meanings of words in particular contexts.

BLCU-ICALL at SemEval-2022 Task 1: Cross-Attention Multitasking Framework for Definition Modeling

1 code implementation SemEval (NAACL) 2022 Cunliang Kong, Yujie Wang, Ruining Chong, Liner Yang, Hengyuan Zhang, Erhong Yang, Yaping Huang

This paper describes the BLCU-ICALL system used in the SemEval-2022 Task 1 Comparing Dictionaries and Word Embeddings, the Definition Modeling subtrack, achieving 1st on Italian, 2nd on Spanish and Russian, and 3rd on English and French.

Language Modelling Word Embeddings

Multitasking Framework for Unsupervised Simple Definition Generation

2 code implementations ACL 2022 Cunliang Kong, Yun Chen, Hengyuan Zhang, Liner Yang, Erhong Yang

We demonstrate that the framework can generate relevant, simple definitions for the target words through automatic and manual evaluations on English and Chinese datasets.

YACLC: A Chinese Learner Corpus with Multidimensional Annotation

1 code implementation30 Dec 2021 Yingying Wang, Cunliang Kong, Liner Yang, Yijun Wang, Xiaorong Lu, Renfen Hu, Shan He, Zhenghao Liu, Yun Chen, Erhong Yang, Maosong Sun

This resource is of great relevance for second language acquisition research, foreign-language teaching, and automatic grammatical error correction.

Grammatical Error Correction Language Acquisition +1

Incorporating Sememes into Chinese Definition Modeling

1 code implementation16 May 2019 Liner Yang, Cunliang Kong, Yun Chen, Yang Liu, Qinan Fan, Erhong Yang

To accomplish this task, we construct the Chinese Definition Modeling Corpus (CDM), which contains triples of word, sememes and the corresponding definition.

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