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Linfeng Song

2 paper cards in the Research library · 2017–2019

Linfeng Song wrote 2 of the papers Mova reads, in 2017–2019, most of them on Machine translation; often with Daniel Gildea, Yue Zhang, Zhiguo Wang.

OpenAlex · ORCID · h-index 23 · 2357 citations · 132 works — 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 · Semantic Scholar · dblp · ACL Anthology · ORCID

Topics: Machine translation 2

Papers

  1. Semantic Neural Machine Translation Using 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 (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)

More papers in the library (2)

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