10 citations · 26 across the 18 of their papers we have counts for
18 papers
PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models
Jiyuan An, Jiachen Zhao, Fan Chen +6
The construction of CAD models has traditionally relied on labor-intensive manual operations and specialized expertise. Recent advances in large language models (LLMs) have inspire…
From Human Cognition to Neural Activations: Probing the Computational Primitives of Spatial Reasoning in LLMs
Jiyuan An, Liner Yang, Mengyan Wang +3
As spatial intelligence becomes an increasingly important capability for foundation models, it remains unclear whether large language models' (LLMs) performance on spatial reasonin…
From Text to CQL: Bridging Natural Language and Corpus Search Engine
Luming Lu, Jiyuan An, Yujie Wang +8
Natural Language Processing (NLP) technologies have revolutionized the way we interact with information systems, with a significant focus on converting natural language queries int…
Cross-domain Chinese Sentence Pattern Parsing
Jingsi Yu, Cunliang Kong, Liner Yang +6
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,…
OMGEval: An Open Multilingual Generative Evaluation Benchmark for Large Language Models
Yang Liu, Meng Xu, Shuo Wang +7
Modern large language models (LLMs) should generally benefit individuals from various cultural backgrounds around the world. However, most recent advanced generative evaluation ben…
MCTS: A Multi-Reference Chinese Text Simplification Dataset
Ruining Chong, Luming Lu, Liner Yang +6
Text simplification aims to make the text easier to understand by applying rewriting transformations. There has been very little research on Chinese text simplification for a long…
Cost-efficient Crowdsourcing for Span-based Sequence Labeling: Worker Selection and Data Augmentation
Yujie Wang, Chao Huang, Liner Yang +5
This paper introduces a novel crowdsourcing worker selection algorithm, enhancing annotation quality and reducing costs. Unlike previous studies targeting simpler tasks, this study…
Lexical Complexity Controlled Sentence Generation
Jinran Nie, Liner Yang, Yun Chen +3
Text generation rarely considers the control of lexical complexity, which limits its more comprehensive practical application. We introduce a novel task of lexical complexity contr…
COMPILING: A Benchmark Dataset for Chinese Complexity Controllable Definition Generation
Jiaxin Yuan, Cunliang Kong, Chenhui Xie +2
The definition generation task aims to generate a word's definition within a specific context automatically. However, owing to the lack of datasets for different complexities, the…
LitMind Dictionary: An Open-Source Online Dictionary
Cunliang Kong, Xuezhi Fang, Liner Yang +2
Dictionaries can help language learners to learn vocabulary by providing definitions of words. Since traditional dictionaries present word senses as discrete items in predefined in…
BLCU-ICALL at SemEval-2022 Task 1: Cross-Attention Multitasking Framework for Definition Modeling
Cunliang Kong, Yujie Wang, Ruining Chong +4
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, 2…
Multitasking Framework for Unsupervised Simple Definition Generation
Cunliang Kong, Yun Chen, Hengyuan Zhang +2
The definition generation task can help language learners by providing explanations for unfamiliar words. This task has attracted much attention in recent years. We propose a novel…
YACLC: A Chinese Learner Corpus with Multidimensional Annotation
Yingying Wang, Cunliang Kong, Liner Yang +8
Learner corpus collects language data produced by L2 learners, that is second or foreign-language learners. This resource is of great relevance for second language acquisition rese…
CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark
Yuan Yao, Qingxiu Dong, Jian Guan +32
Realizing general-purpose language intelligence has been a longstanding goal for natural language processing, where standard evaluation benchmarks play a fundamental and guiding ro…
Few-Shot Domain Adaptation for Grammatical Error Correction via Meta-Learning
Shengsheng Zhang, Yaping Huang, Yun Chen +3
Most existing Grammatical Error Correction (GEC) methods based on sequence-to-sequence mainly focus on how to generate more pseudo data to obtain better performance. Few work addre…
Toward Cross-Lingual Definition Generation for Language Learners
Cunliang Kong, Liner Yang, Tianzuo Zhang +4
Generating dictionary definitions automatically can prove useful for language learners. However, it's still a challenging task of cross-lingual definition generation. In this work,…
Controllable Data Synthesis Method for Grammatical Error Correction
Liner Yang, Chencheng Wang, Yun Chen +2
Due to the lack of parallel data in current Grammatical Error Correction (GEC) task, models based on Sequence to Sequence framework cannot be adequately trained to obtain higher pe…
Incorporating Sememes into Chinese Definition Modeling
Liner Yang, Cunliang Kong, Yun Chen +3
Chinese definition modeling is a challenging task that generates a dictionary definition in Chinese for a given Chinese word. To accomplish this task, we construct the Chinese Defi…