---
title: "Who cites Subject-verb agreement with Seq2Seq…"
description: "The papers of the Elamur Research library that cite «Subject-verb agreement with Seq2Seq transformers: Bigger is better, but still not best», found in…"
canonical: "https://research.elamur.ai/free/en/papers/wilson-2023-subject-verb-agreement-seq2seq-transformers/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Subject-verb agreement with Seq2Seq transformers…](https://md.research.elamur.ai/free/en/papers/wilson-2023-subject-verb-agreement-seq2seq-transformers/) / cited by

# Who cites «Subject-verb agreement with Seq2Seq transformers: Bigger is better, but still not best»

2 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/wilson-2023-subject-verb-agreement-seq2seq-transformers/)

1. [Investigating Syntactic Biases in Multilingual Transformers with RC Attachment Ambiguities in Italian and English](https://aclanthology.org/2026.scil-main.19/) *— 2026 · Proceedings of the Society for Computation in Linguistics 2026*
2. [Modeling morphosyntactic agreement as neural search: a case study of Hindi-Urdu](https://aclanthology.org/2024.scil-1.21/) *— 2024 · Proceedings of the Society for Computation in Linguistics 2024*