--- title: "James Henderson — papers and cards" description: "James Henderson: 2 paper cards in the Research library (2020–2021), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/james-henderson/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/james-henderson/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / James Henderson # James Henderson 2 paper cards in the Research library · 2020–2021 James Henderson wrote 2 of the papers Mova reads, in 2020–2021, most of them on [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/), [Treebanks](https://md.research.elamur.ai/free/en/topics/treebanks/); often with [Alireza Mohammadshahi](https://md.research.elamur.ai/free/en/authors/alireza-mohammadshahi/). Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=James+Henderson) · [Semantic Scholar](https://www.semanticscholar.org/search?q=James+Henderson) · [dblp](https://dblp.org/search?q=James+Henderson) · [ACL Anthology](https://aclanthology.org/search/?q=James+Henderson) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=James+Henderson) Topics: [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) 2 · [Treebanks](https://md.research.elamur.ai/free/en/topics/treebanks/) 1 ## Papers 1. **[Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement](https://md.research.elamur.ai/free/en/papers/ud-2021-mohammadshahi-recursive-non-autoregressive-graph-graph/)** *(2021)* The parser predicts all edges of a graph in parallel, then refines the whole graph in recursive passes. Each pass is conditioned on the graph from the previous pass. An initial parser supplies the first graph, and the paper refines both UDify output and its own graph parser (SynTr). Refinement reduces LAS error… 2. **[Graph-to-Graph Transformer for Transition-based Dependency Parsing](https://md.research.elamur.ai/free/en/papers/ud-2020-mohammadshahi-graph-graph-transformer-transition-based/)** *(2020)* The paper proposes the Graph2Graph Transformer (G2GTr), an architecture that conditions on an arbitrary graph and predicts one. ## Co-authors (1) - [Alireza Mohammadshahi](https://md.research.elamur.ai/free/en/authors/alireza-mohammadshahi/) ×2 ## More papers in the library (2) Pages of the Research library: our summary, the ideas, references and who cites each. - [The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task](https://md.research.elamur.ai/free/en/papers/barry-2021-dcu-epfl-enhanced-dependency-parser/) — James Barry, Alireza Mohammadshahi, Joachim Wagner, et al. · 2021 - [Document-Level Neural Machine Translation with Hierarchical Attention Networks](https://md.research.elamur.ai/free/en/papers/miculicich-2018-document-level-neural-machine-translation/) — Lesly Miculicich, Dhananjay Ram, Nikolaos Pappas, et al. · 2018