---
title: "Who cites Restoration of Fragmentary Babylonian Texts…"
description: "The papers of the Elamur Research library that cite «Restoration of Fragmentary Babylonian Texts Using Recurrent Neural Networks», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/langstream-2020-fetaya-restoration-fragmentary-babylonian-texts-using/cited-by/"
---
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# Who cites «Restoration of Fragmentary Babylonian Texts Using Recurrent Neural Networks»

13 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/langstream-2020-fetaya-restoration-fragmentary-babylonian-texts-using/)

1. [Building a Corpus and Database for Rare and Undeciphered Scripts](https://aclanthology.org/2026.lt4hala-1.17/) *— 2026 · Proceedings of the Fourth Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA 2026) @ LREC 2026*
2. [Draft, Verify, Restore: Self-Refining Historical Inscription Restoration with a Unified MLLM](https://aclanthology.org/2026.acl-long.1254/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [Validator-Guided Hard Negative Mining for Masked Language Modeling in Low-Resource Ancient Languages](https://aclanthology.org/2026.acl-srw.69/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
4. [EvaCun 2025 Shared Task: Lemmatization and Token Prediction in Akkadian and Sumerian using LLMs](https://md.research.elamur.ai/free/en/papers/aclbulk-2025-gordin-evacun-2025-shared-task-lemmatization/) *— our card · 2025 · Proceedings of the Second Workshop on Ancient Language Processing*
5. [Reviving Cultural Heritage: A Novel Approach for Comprehensive Historical Document Restoration](https://aclanthology.org/2025.acl-long.1402/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
6. [Embible: Reconstruction of Ancient Hebrew and Aramaic Texts Using Transformers](https://md.research.elamur.ai/free/en/papers/aclbulk-2024-fono-embible-reconstruction-ancient-hebrew-aramaic/) *— our card · 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
7. [MsBERT: A New Model for the Reconstruction of Lacunae in Hebrew Manuscripts](https://md.research.elamur.ai/free/en/papers/aclbulk-2024-shmidman-msbert-new-model-reconstruction-lacunae/) *— our card · 2024 · Proceedings of the 1st Workshop on Machine Learning for Ancient Languages (ML4AL 2024)*
8. [PhiloGPT: A Philology-Oriented Large Language Model for Ancient Chinese Manuscripts with Dunhuang as Case Study](https://aclanthology.org/2024.emnlp-main.163/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
9. [Reconstruction of Cuneiform Literary Texts as Text Matching](https://aclanthology.org/2024.lrec-main.1197/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
10. [Restoring Ancient Ideograph: A Multimodal Multitask Neural Network Approach](https://aclanthology.org/2024.lrec-main.1221/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
11. [Restoring Mycenaean Linear B `A&B' series tablets using supervised and transfer learning](https://aclanthology.org/2024.ml4al-1.13/) *— 2024 · Proceedings of the 1st Workshop on Machine Learning for Ancient Languages (ML4AL 2024)*
12. [Contextual Unsupervised Clustering of Signs for Ancient Writing Systems](https://aclanthology.org/2022.lt4hala-1.12/) *— 2022 · Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages*
13. [Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach](https://md.research.elamur.ai/free/en/papers/emnlp-2021-lazar-filling-gaps-ancient-akkadian-texts/) *— our card · 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*