---
title: "Who cites Peter Shaw — 463 papers of our library"
description: "463 papers of the Elamur Research library cite the works of Peter Shaw, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/peter-shaw/cited-by/"
---
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# Who cites Peter Shaw

467 citations of their works from 463 papers of our library (of the 141,840 whose bibliographies we read) · 44 with a page here, the most cited first · [← Peter Shaw](https://md.research.elamur.ai/free/en/authors/peter-shaw/)

1. [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683**Colin Raffel, Noam Shazeer, Adam Roberts, et al.*2019 · 11,088 citations*](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/)
2. **[fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://md.research.elamur.ai/free/en/papers/ott-2019-fairseq-fast-extensible-toolkit-sequence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Myle Ott, Sergey Edunov, Alexei Baevski, et al.*2019 · 3,951 citations*
3. [**RoFormer: Enhanced Transformer with Rotary Position Embedding arXiv:2104.09864**Jianlin Su, Yu Lu, Shengfeng Pan, et al.*2021 · 2,963 citations*](https://md.research.elamur.ai/free/en/papers/su-2021-roformer-enhanced-transformer-rotary-position/)
4. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*
5. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,287 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
6. **[Multimodal Transformer for Unaligned Multimodal Language Sequences](https://md.research.elamur.ai/free/en/papers/tsai-2019-multimodal-transformer-unaligned-multimodal-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, et al.*2019 · 2,174 citations*
7. [**DeBERTa: Decoding-enhanced BERT with Disentangled Attention arXiv:2006.03654**Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 1,808 citations*](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/)
8. [**DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing arXiv:2111.09543**Pengcheng He, Jianfeng Gao, Weizhu Chen*2021 · 1,316 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-debertav3-improving-deberta-using-electra/)
9. **[Big Bird: Transformers for Longer Sequences](https://md.research.elamur.ai/free/en/papers/zaheer-2020-big-bird-transformers-longer-sequences/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Manzil Zaheer, Guru Guruganesh, Avinava Dubey, et al.*2020 · 1,002 citations*
10. [**MPNet: Masked and Permuted Pre-training for Language Understanding arXiv:2004.09297**Kaitao Song, Xu Tan, Tao Qin, et al.*2020 · 948 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-mpnet-masked-permuted-pre-training/)
11. **[Scaling Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/ott-2018-scaling-neural-machine-translation/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Myle Ott, Sergey Edunov, David Grangier, et al.*2018 · 819 citations*
12. **[Learning Deep Transformer Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2019-learning-deep-transformer-models-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiang Wang, Bei Li, Tong Xiao, et al.*2019 · 802 citations*
13. **[RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers](https://md.research.elamur.ai/free/en/papers/wang-2020-rat-sql-relation-aware-schema/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bailin Wang, Richard Shin, Xiaodong Liu, et al.*2020 · 752 citations*
14. **[Efficient Content-Based Sparse Attention with Routing Transformers](https://md.research.elamur.ai/free/en/papers/roy-2020-efficient-content-based-sparse-attention/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aurko Roy, Mohammad Saffar, Ashish Vaswani, et al.*2020 · 664 citations*
15. **[LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Xu, Yiheng Xu, Tengchao Lv, et al.*2021 · 623 citations*
16. **[Leveraging Pre-trained Checkpoints for Sequence Generation Tasks](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Sascha Rothe, Shashi Narayan, Aliaksei Severyn*2019 · 563 citations*
17. [**Large Language Models: A Survey arXiv:2402.06196**Shervin Minaee, Tomas Mikolov, Narjes Nikzad, et al.*2024 · 468 citations*](https://md.research.elamur.ai/free/en/papers/minaee-2024-large-language-models-survey/)
18. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
19. [**Pay Less Attention with Lightweight and Dynamic Convolutions arXiv:1901.10430**Felix Wu, Angela Fan, Alexei Baevski, et al.*2019 · 424 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-pay-less-attention-lightweight-dynamic/)
20. **[ETC: Encoding Long and Structured Inputs in Transformers](https://md.research.elamur.ai/free/en/papers/ainslie-2020-etc-encoding-long-structured-inputs/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ainslie, Santiago Ontañón, Chris Alberti, et al.*2020 · 380 citations*
21. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
22. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
23. **[RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/li-2023-resdsql-decoupling-schema-linking-skeleton/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Haoyang Li, Jing Zhang, Cuiping Li, et al.*2023 · 277 citations*
24. **[ConveRT: Efficient and Accurate Conversational Representations from Transformers](https://md.research.elamur.ai/free/en/papers/henderson-2020-convert-efficient-accurate-conversational-representations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Matthew Henderson, Iñigo Casanueva, Nikola Mrkšić, et al.*2020 · 268 citations*
25. **[Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Victoria Lin, Richard Socher, Caiming Xiong*2020 · 261 citations*
26. **[Modeling Localness for Self-Attention Networks](https://md.research.elamur.ai/free/en/papers/yang-2018-modeling-localness-self-attention-networks/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Baosong Yang, Zhaopeng Tu, Derek F. Wong, et al.*2018 · 255 citations*
27. [**Multimodal Few-Shot Learning with Frozen Language Models arXiv:2106.13884**Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, et al.*2021 · 243 citations*](https://md.research.elamur.ai/free/en/papers/tsimpoukelli-2021-multimodal-few-shot-learning-frozen/)
28. **[MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems](https://md.research.elamur.ai/free/en/papers/lin-2020-mintl-minimalist-transfer-learning-task/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaojiang Lin, Andrea Madotto, Genta Indra Winata, et al.*2020 · 240 citations*
29. **[Reasoning Over Semantic-Level Graph for Fact Checking](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wanjun Zhong, Jingjing Xu, Duyu Tang, et al.*2020 · 221 citations*
30. **[SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing](https://md.research.elamur.ai/free/en/papers/ao-2022-speecht5-unified-modal-encoder-decoder/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyi Ao, Rui Wang, Long Zhou, et al.*2022 · 217 citations*
31. **[LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations](https://md.research.elamur.ai/free/en/papers/cao-2021-lgesql-line-graph-enhanced-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruisheng Cao, Lu Chen, Zhi Chen, et al.*2021 · 191 citations*
32. **[Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/artetxe-2019-margin-based-parallel-corpus-mining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mikel Artetxe, Holger Schwenk*2019 · 165 citations*
33. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.*2023 · 145 citations*
34. **[Diverse Demonstrations Improve In-context Compositional Generalization](https://md.research.elamur.ai/free/en/papers/levy-2023-diverse-demonstrations-improve-context-compositional/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Itay Levy, Ben Bogin, Jonathan Berant*2023 · 139 citations*
35. [**Efficient Training of Language Models to Fill in the Middle arXiv:2207.14255**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 138 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
36. **[A Length-Extrapolatable Transformer](https://md.research.elamur.ai/free/en/papers/sun-2023-length-extrapolatable-transformer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yutao Sun, Li Dong, Barun Patra, et al.*2023 · 117 citations*
37. **[APE at Scale and Its Implications on MT Evaluation Biases](https://md.research.elamur.ai/free/en/papers/freitag-2019-ape-scale-its-implications-mt/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Markus Freitag, Isaac Caswell, Scott Roy*2019 · 107 citations*
38. **[The NiuTrans Machine Translation Systems for WMT19](https://md.research.elamur.ai/free/en/papers/li-2019-niutrans-machine-translation-systems-wmt19/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Bei Li, Yinqiao Li, Chen Xu, et al.*2019 · 92 citations*
39. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
40. [**Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement**Alireza Mohammadshahi, James Henderson*2021 · 26 citations*](https://md.research.elamur.ai/free/en/papers/mohammadshahi-2021-recursive-non-autoregressive-graph-graph/)
41. [**Graph-to-Graph Transformer for Transition-based Dependency Parsing**Alireza Mohammadshahi, James Henderson*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/mohammadshahi-2020-graph-graph-transformer-transition-based/)
42. [**Local Contextual Attention with Hierarchical Structure for Dialogue Act Recognition arXiv:2003.06044**Zhigang Dai, Jinhua Fu, Qile Zhu, et al.*2020 · 15 citations*](https://md.research.elamur.ai/free/en/papers/dai-2020-local-contextual-attention-hierarchical-structure/)
43. **[Character-aware Transformers Learn an Irregular Morphological Pattern Yet None Generalize Like Humans](https://md.research.elamur.ai/free/en/papers/ramarao-2026-character-aware-transformers-learn-irregular/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Akhilesh Kakolu Ramarao, Kevin Tang, Dinah Baer-Henney*2026*
44. **[Examining Algebraic Recombination for Compositional Generalisation](https://md.research.elamur.ai/free/en/papers/ruiz-2026-examining-algebraic-recombination-compositional-generalisation/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Joaquin Cardona Ruiz, Antske Fokkens, Lucia Donatelli*2026*

419 more citing papers of our library have no page here yet.

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