--- title: "Zhiguo Wang — papers and cards" description: "Zhiguo Wang: 2 paper cards in the Research library (2017–2019), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/zhiguo-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhiguo-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhiguo Wang # Zhiguo Wang 2 paper cards in the Research library · 2017–2019 Zhiguo Wang wrote 2 of the papers Mova reads, in 2017–2019, most of them on [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Daniel Gildea](https://md.research.elamur.ai/free/en/authors/daniel-gildea/), [Linfeng Song](https://md.research.elamur.ai/free/en/authors/linfeng-song/), [Yue Zhang](https://md.research.elamur.ai/free/en/authors/yue-zhang/). [OpenAlex](https://openalex.org/A5006895046) · [ORCID](https://orcid.org/0000-0003-0343-7278) · [**h-index 21**](https://openalex.org/authors/A5006895046) · [1576 citations](https://openalex.org/authors/A5006895046) · [148 works](https://openalex.org/works?filter=author.id:A5006895046) — 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=Zhiguo+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhiguo+Wang) · [dblp](https://dblp.org/search?q=Zhiguo+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Zhiguo+Wang) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Zhiguo+Wang) Topics: [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 2 ## Papers 1. **[Semantic Neural Machine Translation Using AMR](https://md.research.elamur.ai/free/en/papers/song-2019-semantic-neural-machine-translation-amr/)** *(2019)* The paper asks whether an AMR graph of the source sentence helps neural machine translation. The model keeps a BiLSTM encoder over the words and adds a graph recurrent network that encodes the AMR graph without linearising it. A doubly attentive LSTM decoder reads both encodings. On WMT16 English-German (4.17M… 2. **[AMR-to-text Generation with Synchronous Node Replacement Grammar](https://md.research.elamur.ai/free/en/papers/song-2017-amr-text-generation-synchronous-node/)** *(2017)* The paper generates sentences directly from the AMR graph, without first making a spanning tree, so that no information is lost in the graph-to-tree step. ## Co-authors (5) - [Daniel Gildea](https://md.research.elamur.ai/free/en/authors/daniel-gildea/) ×2 - [Linfeng Song](https://md.research.elamur.ai/free/en/authors/linfeng-song/) ×2 - [Yue Zhang](https://md.research.elamur.ai/free/en/authors/yue-zhang/) ×2 - Jinsong Su - Xiaochang Peng ## More papers in the library (2) Pages of the Research library: our summary, the ideas, references and who cites each. - [A Graph-to-Sequence Model for AMR-to-Text Generation](https://md.research.elamur.ai/free/en/papers/song-2018-graph-sequence-model-amr-text/) — Linfeng Song, Yue Zhang, Zhiguo Wang, et al. · 2018 - [Bilateral Multi-Perspective Matching for Natural Language Sentences](https://md.research.elamur.ai/free/en/papers/wang-2017-bilateral-multi-perspective-matching-natural/) — Zhiguo Wang, Wael Hamza, Radu Florian · 2017