---
title: "Who cites Proficiency assessment of L2 — 11 citing papers"
description: "11 papers of the Elamur Research library cite «Proficiency assessment of L2 spoken English using wav2vec 2.0», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/banno-2022-proficiency-assessment-l2-spoken-english/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Proficiency assessment of L2 spoken English using…](https://md.research.elamur.ai/free/en/papers/banno-2022-proficiency-assessment-l2-spoken-english/) / cited by

# Who cites «Proficiency assessment of L2 spoken English using wav2vec 2.0»

11 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «Proficiency assessment of L2 spoken English using wav2vec 2.0»](https://md.research.elamur.ai/free/en/papers/banno-2022-proficiency-assessment-l2-spoken-english/)

1. **[A Benchmark Corpus for the Diagnostic Assessment of Content in L2 English Speech](https://md.research.elamur.ai/free/en/papers/doi-2026-benchmark-corpus-diagnostic-assessment-content/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Doi, Justin Vasselli, Taro Watanabe*2026*
2. [**Controlling Implicit Shortcut Reliance in L2 Spoken English Auto-markers arXiv:2607.16085**Shilin Gao, Mark J. F. Gales, Kate M. Knill*2026*](https://md.research.elamur.ai/free/en/papers/gao-2026-controlling-implicit-shortcut-reliance-l2/)
3. **[MASA: A Novel Multimodal Foundation Model for L2 Speaking Assessment in Picture-description Scenarios](https://md.research.elamur.ai/free/en/papers/yan-2026-masa-novel-multimodal-foundation-model/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Bi-Cheng Yan, Fu-An Chao, Hong-Yun H.Y. Lin, et al.*2026*
4. **[RABIT: Rationale-Based Distillation Towards Interpretable Automatic Speaking Assessment via a Small Language Model](https://md.research.elamur.ai/free/en/papers/yan-2026-rabit-rationale-based-distillation-interpretable/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Bi-Cheng Yan, Hong-Yun Lin, Fu-An Chao, et al.*2026*
5. [**Automatic Proficiency Assessment in L2 English Learners arXiv:2505.02615**Armita Mohammadi, Alessandro Lameiras Koerich, Laureano Moro-Velazquez, et al.*2025*](https://md.research.elamur.ai/free/en/papers/mohammadi-2025-automatic-proficiency-assessment-l2-english/)
6. **[Enhancing Automated English Speaking Assessment for L2 Speakers with BERT and Wav2vec2.0 Fusion](https://md.research.elamur.ai/free/en/papers/peng-2023-enhancing-automated-english-speaking-assessment/) [Conference on Computational Linguistics and Speech Processing (ROCLING)](https://md.research.elamur.ai/free/en/venues/rocling/)**Wen-Hsuan Peng, Hsin-Wei Wang, Sally Chen, et al.*2023*

5 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/banno-2022-proficiency-assessment-l2-spoken-english/) — Proficiency assessment of L2 spoken English using wav2vec 2.0