---
title: "Who cites David Belanger — 501 papers of our library"
description: "501 papers of the Elamur Research library cite the works of David Belanger, found in their bibliographies; the most cited first."
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---
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# Who cites David Belanger

503 citations of their works from 501 papers of our library (of the 149,439 whose bibliographies we read) · 78 with a page here, the most cited first · [← David Belanger](https://md.research.elamur.ai/free/en/authors/david-belanger/)

1. **[Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://md.research.elamur.ai/free/en/papers/liu-2021-swin-transformer-hierarchical-vision-transformer/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Ze Liu, Yutong Lin, Yue Cao, et al.*2021 · 33,968 citations*
2. [**PaLM: Scaling Language Modeling with Pathways arXiv:2204.02311**Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.*2022 · 4,753 citations*](https://md.research.elamur.ai/free/en/papers/chowdhery-2022-palm-scaling-language-modeling-pathways/)
3. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
4. [**RoFormer: Enhanced Transformer with Rotary Position Embedding arXiv:2104.09864**Jianlin Su, Yu Lu, Shengfeng Pan, et al.*2021 · 3,028 citations*](https://md.research.elamur.ai/free/en/papers/su-2021-roformer-enhanced-transformer-rotary-position/)
5. **[Efficient Transformers: A Survey](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Yi Tay, Mostafa Dehghani, Dara Bahri, et al.*2020 · 1,539 citations*
6. [**FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning arXiv:2307.08691**Tri Dao*2023 · 1,240 citations*](https://md.research.elamur.ai/free/en/papers/dao-2023-flashattention-2-faster-attention-better/)
7. **[A Unified MRC Framework for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/li-2020-unified-mrc-framework-named-entity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoya Li, Jingrong Feng, Yuxian Meng, et al.*2020 · 840 citations*
8. **[FNet: Mixing Tokens with Fourier Transforms](https://md.research.elamur.ai/free/en/papers/thorp-2022-fnet-mixing-tokens-fourier-transforms/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**James Lee-Thorp, Joshua Ainslie, Ilya Eckstein, et al.*2022 · 597 citations*
9. **[Named Entity Recognition as Dependency Parsing](https://md.research.elamur.ai/free/en/papers/yu-2020-named-entity-recognition-as-dependency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Juntao Yu, Bernd Bohnet, Massimo Poesio*2020 · 596 citations*
10. **[AudioLM: a Language Modeling Approach to Audio Generation](https://md.research.elamur.ai/free/en/papers/borsos-2022-audiolm-language-modeling-approach-audio/) [IEEE/ACM Transactions on Audio Speech and Language Processing](https://md.research.elamur.ai/free/en/venues/ieee-acm-transactions-on-audio-speech-and-language-processing/)**Zalan Borsos, Raphael Marinier, Damien Vincent, et al.*2022 · 581 citations*
11. [**Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model arXiv:2401.09417**Lianghui Zhu, Bencheng Liao, Qian Zhang, et al.*2024 · 500 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-vision-mamba-efficient-visual-representation/)
12. **[Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction](https://md.research.elamur.ai/free/en/papers/xu-2018-double-embeddings-cnn-based-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hu Xu, Bing Liu, Lei Shu, et al.*2018 · 499 citations*
13. **[Template-Based Named Entity Recognition Using BART](https://md.research.elamur.ai/free/en/papers/cui-2021-template-based-named-entity-recognition/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leyang Cui, Yu Wu, Jian Liu, et al.*2021 · 421 citations*
14. [**Long Range Arena: A Benchmark for Efficient Transformers arXiv:2011.04006**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2020 · 414 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-long-range-arena-benchmark-efficient/)
15. **[FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision](https://md.research.elamur.ai/free/en/papers/shah-2024-flashattention-3-fast-accurate-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jay Shah, Ganesh Bikshandi, Ying Zhang, et al.*2024 · 400 citations*
16. **[LongT5: Efficient Text-To-Text Transformer for Long Sequences](https://md.research.elamur.ai/free/en/papers/guo-2022-longt5-efficient-text-text-transformer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mandy Guo, Joshua Ainslie, David Uthus, et al.*2022 · 399 citations*
17. **[A Neural Layered Model for Nested Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/ju-2018-neural-layered-model-nested-named/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Meizhi Ju, Makoto Miwa, Sophia Ananiadou*2018 · 379 citations*
18. **[Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction](https://md.research.elamur.ai/free/en/papers/verga-2018-simultaneously-self-attending-all-mentions/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Patrick Verga, Emma Strubell, Andrew McCallum*2018 · 353 citations*
19. **[Efficient Attentions for Long Document Summarization](https://md.research.elamur.ai/free/en/papers/huang-2021-efficient-attentions-long-document-summarization/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Luyang Huang, Shuyang Cao, Nikolaus Parulian, et al.*2021 · 336 citations*
20. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language arXiv:2204.00598**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
21. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
22. **[Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation](https://md.research.elamur.ai/free/en/papers/clark-2022-canine-pre-training-efficient-tokenization/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jonathan H. Clark, Dan Garrette, Iulia Turc, et al.*2022 · 301 citations*
23. **[Deep Exhaustive Model for Nested Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/sohrab-2018-deep-exhaustive-model-nested-named/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mohammad Golam Sohrab, Makoto Miwa*2018 · 300 citations*
24. **[Entity Linking via Joint Encoding of Types, Descriptions, and Context](https://md.research.elamur.ai/free/en/papers/gupta-2017-entity-linking-joint-encoding-types/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nitish Gupta, Sameer Singh, Dan Roth*2017 · 299 citations*
25. **[xLSTM: Extended Long Short-Term Memory](https://md.research.elamur.ai/free/en/papers/beck-2024-xlstm-extended-long-short-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.*2024 · 296 citations*
26. [**Perceiver: General Perception with Iterative Attention arXiv:2103.03206**Andrew Jaegle, Felix Gimeno, Andrew Brock, et al.*2021 · 269 citations*](https://md.research.elamur.ai/free/en/papers/jaegle-2021-perceiver-general-perception-iterative-attention/)
27. [**Transformers learn in-context by gradient descent arXiv:2212.07677**Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.*2022 · 247 citations*](https://md.research.elamur.ai/free/en/papers/oswald-2022-transformers-learn-context-gradient-descent/)
28. **[NCRF++: An Open-source Neural Sequence Labeling Toolkit](https://md.research.elamur.ai/free/en/papers/yang-2018-ncrf-open-source-neural-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jie Yang, Yue Zhang*2018 · 245 citations*
29. **[Design Challenges and Misconceptions in Neural Sequence Labeling](https://md.research.elamur.ai/free/en/papers/yang-2018-design-challenges-misconceptions-neural-sequence/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jie Yang, Shuailong Liang, Yue Zhang*2018 · 197 citations*
30. [**Charformer: Fast Character Transformers via Gradient-based Subword Tokenization arXiv:2106.12672**Yi Tay, Vinh Q. Tran, Sebastian Ruder, et al.*2021 · 186 citations*](https://md.research.elamur.ai/free/en/papers/tay-2021-charformer-fast-character-transformers-gradient/)
31. **[Adapting Language Models to Compress Contexts](https://md.research.elamur.ai/free/en/papers/chevalier-2023-adapting-language-models-compress-contexts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.*2023 · 182 citations*
32. **[Zero-Shot Cross-Lingual Transfer with Meta Learning](https://md.research.elamur.ai/free/en/papers/nooralahzadeh-2020-zero-shot-cross-lingual-transfer/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, et al.*2020 · 171 citations*
33. **[SCROLLS: Standardized CompaRison Over Long Language Sequences](https://md.research.elamur.ai/free/en/papers/shaham-2022-scrolls-standardized-comparison-over-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Uri Shaham, Elad Segal, Maor Ivgi, et al.*2022 · 165 citations*
34. **[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*
35. **[Learning Distributed Representations of Texts and Entities from Knowledge Base](https://md.research.elamur.ai/free/en/papers/yamada-2017-learning-distributed-representations-texts-entities/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2017 · 125 citations*
36. [**H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models arXiv:2306.14048**Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-h-2-o-heavy-hitter/)
37. [**LongNet: Scaling Transformers to 1,000,000,000 Tokens arXiv:2307.02486**Jiayu Ding, Shuming Ma, Li Dong, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/ding-2023-longnet-scaling-transformers-1-000/)
38. **[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 · 118 citations*
39. [**In-context Autoencoder for Context Compression in a Large Language Model arXiv:2307.06945**Tao Ge, Jing Hu, Lei Wang, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-context-autoencoder-context-compression-large/)
40. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
41. **[Unlimiformer: Long-Range Transformers with Unlimited Length Input](https://md.research.elamur.ai/free/en/papers/bertsch-2023-unlimiformer-long-range-transformers-unlimited/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Amanda Bertsch, Uri Alon, Graham Neubig, et al.*2023 · 111 citations*
42. [**Linear Transformers Are Secretly Fast Weight Programmers arXiv:2102.11174**Imanol Schlag, Kazuki Irie, Jurgen Schmidhuber*2021 · 111 citations*](https://md.research.elamur.ai/free/en/papers/schlag-2021-linear-transformers-secretly-fast-weight/)
43. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
44. **[Do Long-Range Language Models Actually Use Long-Range Context?](https://md.research.elamur.ai/free/en/papers/sun-2021-do-long-range-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke, et al.*2021 · 101 citations*
45. [**Transformer Quality in Linear Time arXiv:2202.10447**Weizhe Hua, Zihang Dai, Hanxiao Liu, et al.*2022 · 99 citations*](https://md.research.elamur.ai/free/en/papers/hua-2022-transformer-quality-linear-time/)
46. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
47. [**Landmark Attention: Random-Access Infinite Context Length for Transformers arXiv:2305.16300**Amirkeivan Mohtashami, Martin Jaggi*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/mohtashami-2023-landmark-attention-random-access-infinite/)
48. **[Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?](https://md.research.elamur.ai/free/en/papers/tay-2023-scaling-laws-vs-model-architectures/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2023 · 86 citations*
49. **[MoBA: Mixture of Block Attention for Long-Context LLMs](https://md.research.elamur.ai/free/en/papers/lu-2025-moba-mixture-block-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.*2025 · 80 citations*
50. **[Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/laskar-2022-domain-adaptation-pre-trained-transformers/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Md Tahmid Rahman Laskar, Enamul Hoque, Jimmy Xiangji Huang*2022 · 76 citations*
51. **[SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration](https://md.research.elamur.ai/free/en/papers/zhang-2024-sageattention-accurate-8-bit-attention/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jintao Zhang, Jia Wei, Haofeng Huang, et al.*2024 · 74 citations*
52. **[The Devil in Linear Transformer](https://md.research.elamur.ai/free/en/papers/qin-2022-devil-linear-transformer/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Qin, Xiaodong Han, Weixuan Sun, et al.*2022 · 67 citations*
53. [**MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention arXiv:2506.13585**MiniMax, Aili Chen, Aonian Li, et al.*2025 · 66 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-m1-scaling-test/)
54. [**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/)
55. [**Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models arXiv:2402.02244**Xindi Wang, Mahsa Salmani, Parsa Omidi, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-limits-survey-techniques-extend-context/)
56. [**Simple linear attention language models balance the recall-throughput tradeoff arXiv:2402.18668**Simran Arora, Sabri Eyuboglu, Michael Zhang, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/arora-2024-simple-linear-attention-language-models/)
57. [**Scaling Laws of RoPE-based Extrapolation arXiv:2310.05209**Xiaoran Liu, Hang Yan, Shuo Zhang, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-scaling-laws-rope-based/)
58. **[Long-Context Language Modeling with Parallel Context Encoding](https://md.research.elamur.ai/free/en/papers/yen-2024-long-context-language-modeling-parallel/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Howard Yen, Tianyu Gao, Danqi Chen*2024 · 44 citations*
59. [**TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer arXiv:2307.14995**Zhen Qin, Dong Li, Weigao Sun, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-transnormerllm-faster-better-large/)
60. **[TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text](https://md.research.elamur.ai/free/en/papers/lu-2025-turborag-accelerating-retrieval-augmented-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songshuo Lu, Hua Wang, Yutian Rong, et al.*2025 · 32 citations*
61. [**Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models arXiv:2401.04658**Zhen Qin, Weigao Sun, Dong Li, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-lightning-attention-2-free/)
62. **[Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 27 citations*
63. [**Block-State Transformers arXiv:2306.09539**Mahan Fathi, Jonathan Pilault, Orhan Firat, et al.*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/fathi-2023-block-state-transformers/)
64. [**Modeling Speech Acts in Asynchronous Conversations: A Neural-CRF Approach**Shafiq Joty, Tasnim Mohiuddin*2018 · 20 citations*](https://md.research.elamur.ai/free/en/papers/joty-2018-modeling-speech-acts-asynchronous-conversations/)
65. [**Linearizing Large Language Models arXiv:2405.06640**Jean Mercat, Igor Vasiljevic, Sedrick Keh, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/mercat-2024-linearizing-large-language-models/)
66. **[Rewarding Coreference Resolvers for Being Consistent with World Knowledge](https://md.research.elamur.ai/free/en/papers/aralikatte-2019-rewarding-coreference-resolvers-being-consistent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rahul Aralikatte, Heather Lent, Ana Valeria Gonzalez, et al.*2019 · 16 citations*
67. **[Attention Entropy is a Key Factor: An Analysis of Parallel Context Encoding with Full-attention-based Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-attention-entropy-is-key-factor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhisong Zhang, Yan Wang, Xinting Huang, et al.*2025 · 14 citations*
68. **[New Insights into Cross-Document Event Coreference: Systematic Comparison and a Simplified Approach](https://md.research.elamur.ai/free/en/papers/cremisini-2020-new-insights-into-cross-document/) [Workshop on Narrative Understanding](https://md.research.elamur.ai/free/en/venues/nuse/)**Andres Cremisini, Mark Finlayson*2020 · 13 citations*
69. [**PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation arXiv:2312.17276**Yunhe Wang, Hanting Chen, Yehui Tang, et al.*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pangu-pi-enhancing-language/)
70. [**Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks**Gor Arakelyan, Karen Hambardzumyan, Hrant Khachatrian*2018 · 10 citations*](https://md.research.elamur.ai/free/en/papers/arakelyan-2018-jointud-part-speech-tagging-lemmatization/)
71. [**Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding arXiv:2205.10687**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models-their/)
72. [**Just read twice: closing the recall gap for recurrent language models arXiv:2407.05483**Simran Arora; Aman Timalsina; Aaryan Singhal; Benjamin Spector; Sabri Eyuboglu; Xinyi Zhao; Ashish Rao; Atri Rudra;, Christopher Re*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/arora-2024-just-read-twice-closing-recall/)
73. [**An End-to-End OCR Framework for Robust Arabic-Handwriting Recognition using a Novel Transformers-based Model and an Innovative 270 Million-Words Multi-Font Corpus of Classical Arabic with Diacritics arXiv:2208.11484**Aly Mostafa, Omar Mohamed, Ali Ashraf, et al.*2022 · 3 citations*](https://md.research.elamur.ai/free/en/papers/mostafa-2022-end-end-ocr-framework-robust/)
74. **[Cross-layer Attention Sharing for Pre-trained Large Language Models](https://md.research.elamur.ai/free/en/papers/mu-2026-cross-layer-attention-sharing-pre/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yongyu Mu, Yuzhang Wu, Yuchun Fan, et al.*2026 · 2 citations*
75. [**MiniMax Sparse Attention arXiv:2606.13392**Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lai-2026-minimax-sparse-attention/)
76. **[A Survey of Retentive Network](https://md.research.elamur.ai/free/en/papers/yang-2026-survey-retentive-network/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiqi Yang, Zhiyuan Li, Yi Chang, et al.*2026*
77. **[From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code Completion](https://md.research.elamur.ai/free/en/papers/wang-2026-logical-computational-sparsity-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanli Wang, Yanlin Wang, Bowen Zhang, et al.*2026*
78. **[SemToken: Semantic-Aware Tokenization for Efficient Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/liu-2026-semtoken-semantic-aware-tokenization-efficient/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Dong Liu, Yanxuan Yu*2026*

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