---
title: "Who cites Generate, Annotate, and Learn: — 31 citing papers"
description: "31 papers of the Elamur Research library cite «Generate, Annotate, and Learn: NLP with Synthetic Text», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/he-2022-generate-annotate-learn-nlp-synthetic/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Generate, Annotate, and Learn: NLP with Synthetic…](https://md.research.elamur.ai/free/en/papers/he-2022-generate-annotate-learn-nlp-synthetic/) / cited by

# Who cites «Generate, Annotate, and Learn: NLP with Synthetic Text»

31 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 «Generate, Annotate, and Learn: NLP with Synthetic Text»](https://md.research.elamur.ai/free/en/papers/he-2022-generate-annotate-learn-nlp-synthetic/)

1. [**Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMs arXiv:2402.12030 · Transactions on Machine Learning Research, January 2025**Nicolas Boizard, Kevin El Haddad, Celine Hudelot, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2024-towards-cross-tokenizer-distillation-universal/)
2. [**Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges arXiv:2309.12426**Vinay Samuel, Houda Aynaou, Arijit Ghosh Chowdhury, et al.*2023 · 16 citations*](https://md.research.elamur.ai/free/en/papers/samuel-2023-llms-augment-low-resource-reading/)
3. **[AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment](https://md.research.elamur.ai/free/en/papers/lai-2025-adacqr-enhancing-query-reformulation-conversational/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yilong Lai, Jialong Wu, Congzhi Zhang, et al.*2025 · 9 citations*
4. **[A Novel Synthetic Dataset for Few-Shot Legal Relation Extraction in German](https://md.research.elamur.ai/free/en/papers/nouri-2026-novel-synthetic-dataset-few-shot/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Shiva Banasaz Nouri, Elena Leitner, Julian Moreno-Schneider, et al.*2026*
5. **[LingVarBench: Benchmarking LLMs on Entity Recognitions and Linguistic Verbalization Patterns in Phone-Call Transcripts](https://md.research.elamur.ai/free/en/papers/mohammadi-2026-lingvarbench-benchmarking-llms-entity-recognitions/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Seyedali Mohammadi, Manas Paldhe, Amit Chhabra, et al.*2026*
6. **[When Efficiency Meets Safety: A Benchmark Security Analysis of KV Cache Compression in Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-when-efficiency-meets-safety-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoxiao Ma, Kuofeng Gao, Zeyi Lu, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/he-2022-generate-annotate-learn-nlp-synthetic/) — Generate, Annotate, and Learn: NLP with Synthetic Text