mlsanityData to 14 Oct 2026

Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings

arXiv 2107.02416 ↗First posted 6 Jul 2021cs.CL cs.LGcited by 2

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Abstract (arXiv)

This paper describes the system used in submission from SHANGHAITECH team to the IWPT 2021 Shared Task. Our system is a graph-based parser with the technique of Automated Concatenation of Embeddings (ACE). Because recent work found that better word representations can be obtained by concatenating different types of embeddings, we use ACE to automatically find the better concatenation of embeddings for the task of enhanced universal dependencies. According to official results averaged on 17 languages, our system ranks 2nd over 9 teams.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 23 of its 37 references that are in the map. First posted on arXiv 6 Jul 2021.

Builds on

23 of 37 references.

References · 23

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11 more
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Citing papers per year: 2023: 1; 2024: 0; 2025: 1.

2 papers.

  1. 2025From Text to Graph: Leveraging Graph Neural Networks for Enhanced Explainability in NLPcited by 1
  2. 2023A Semi-Autoregressive Graph Generative Model for Dependency Graph Parsingcited by 0