--- title: "Wanxiang Che — papers and cards" description: "Wanxiang Che: 3 paper cards in the Research library (2015–2021), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/wanxiang-che/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/wanxiang-che/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Wanxiang Che # Wanxiang Che 3 paper cards in the Research library · 2015–2021 Wanxiang Che wrote 3 of the papers Mova reads, in 2015–2021, most of them on [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/), [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/), [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/), [Yijia Liu](https://md.research.elamur.ai/free/en/authors/yijia-liu/), [Ivan Titov](https://md.research.elamur.ai/free/en/authors/ivan-titov/). [OpenAlex](https://openalex.org/A5019108029) · [ORCID](https://orcid.org/0000-0002-3907-0335) · [**h-index 49**](https://openalex.org/authors/A5019108029) · [8874 citations](https://openalex.org/authors/A5019108029) · [359 works](https://openalex.org/works?filter=author.id:A5019108029) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Wanxiang+Che) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Wanxiang+Che) · [dblp](https://dblp.org/search?q=Wanxiang+Che) · [ACL Anthology](https://aclanthology.org/search/?q=Wanxiang+Che) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Wanxiang+Che) Topics: [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) 2 · [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) 1 · [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 1 ## Papers 1. **[A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples](https://md.research.elamur.ai/free/en/papers/findings-2021-wang-closer-look-into-robustness-neural/)** *(2021)* The paper attacks two English dependency parsers, a biaffine graph parser and a stack-pointer parser, by substituting words. 2. **[Parsing Tweets into Universal Dependencies](https://md.research.elamur.ai/free/en/papers/ud-2018-liu-parsing-tweets-into-universal-dependencies/)** *(2018)* The authors extend the UD guidelines to tweets: emoticons and retweet markers become non-syntactic or discourse tokens, abbreviations such as "idc" stay unnormalized as single words, multiword expressions can be merged, and tweets can have several roots. 3. **[Transition-Based Syntactic Linearization](https://md.research.elamur.ai/free/en/papers/liu-2015-transition-based-syntactic-linearization/)** *(2015)* Syntactic linearization takes a bag of words and optional syntactic constraints and builds the sentence and its tree together. ## Co-authors (11) - [Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/) ×2 - [Yijia Liu](https://md.research.elamur.ai/free/en/authors/yijia-liu/) ×2 - [Ivan Titov](https://md.research.elamur.ai/free/en/authors/ivan-titov/) - [Nathan Schneider](https://md.research.elamur.ai/free/en/authors/nathan-schneider/) - [Noah A. Smith](https://md.research.elamur.ai/free/en/authors/noah-a-smith/) - [Shay B. Cohen](https://md.research.elamur.ai/free/en/authors/shay-b-cohen/) - Ting Liu - Yi Zhu - [Yue Zhang](https://md.research.elamur.ai/free/en/authors/yue-zhang/) - Yuxuan Wang - Zhilin Lei ## More papers in the library (6) Pages of the Research library: our summary, the ideas, references and who cites each. - [Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) — Qiguang Chen, Libo Qin, Jinhao Liu, et al. · 2025 - [MMSD2.0: Towards a Reliable Multi-modal Sarcasm Detection System](https://md.research.elamur.ai/free/en/papers/qin-2023-mmsd2-0-reliable-multi-modal/) — Libo Qin, Shijue Huang, Qiguang Chen, et al. · 2023 - [LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/) — Yang Xu, Yiheng Xu, Tengchao Lv, et al. · 2021 - [Revisiting Pre-Trained Models for Chinese Natural Language Processing](https://md.research.elamur.ai/free/en/papers/cui-2020-revisiting-pre-trained-models-chinese/) — Yiming Cui, Wanxiang Che, Ting Liu, et al. · 2020 - [Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency](https://md.research.elamur.ai/free/en/papers/ren-2019-generating-natural-language-adversarial-examples/) — Shuhuai Ren, Yihe Deng, Kun He, et al. · 2019 - [Pre-Training with Whole Word Masking for Chinese BERT](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/) — Yiming Cui, Wanxiang Che, Ting Liu, et al. · 2019