[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/cited-by/ud-2016-schuster-enhanced-english-universal-dependencies-improved-2/)

[home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [cited-by](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/) / Who cites «Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks» · page 2

# Who cites «Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks» · page 2

111 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/ud-2016-schuster-enhanced-english-universal-dependencies-improved/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2016-schuster-enhanced-english-universal-dependencies-improved/) · **2**

1. birtic-2025-dative-alternations-less-researched-syntactic
2. gao-2021-learning-clause-representation-dependency-anchor
3. han-2019-micron-multigranular-interaction-contextualizing-representation
4. handler-2019-query-focused-sentence-compression-linear
5. judea-2017-event-argument-identification-dependency-graphs
6. kuznetsov-2018-corpus-driven-thematic-hierarchy-induction
7. osenova-2017-recent-developments-within-bultreebank
8. przepiorkowski-2025-coordination-theoretical-computational-linguistics
9. wang-2022-simple-effective-graph-graph-annotation
10. yellin-2021-paths-relation-extraction-through-semantic
11. yih-2022-how-syntactic-analysis-influences-calculation

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2016-schuster-enhanced-english-universal-dependencies-improved/) · **2**

- [← previous Who cites «Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2016-schuster-enhanced-english-universal-dependencies-improved/)
- [next → Who cites «UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2016-straka-udpipe-trainable-pipeline-processing-conll/)
- [↑ back to papers/cited-by/](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/)
