🔗 Who cites «Transformer Language Models without Positional Encodings Still Learn Positional Information»

55 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · ← back to «Transformer Language Models without Positional Encodings Still Learn Positional Information»

1. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
2. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
3. The Falcon Series of Open Language ModelsarXiv:2311.16867Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 443 citations
4. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
5. Jamba: A Hybrid Transformer-Mamba Language ModelarXiv:2403.19887Opher Lieber, Barak Lenz, Hofit Bata, et al.2024 · 159 citations
6. The Impact of Positional Encoding on Length Generalization in TransformersConference on Neural Information Processing Systems (NeurIPS)Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, et al.2023 · 134 citations
7. Landmark Attention: Random-Access Infinite Context Length for TransformersarXiv:2305.16300Amirkeivan Mohtashami, Martin Jaggi2023 · 88 citations
8. Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at ScaleTransactions of the Association for Computational Linguistics (TACL)Laurent Sartran, Samuel Barrett, Adhiguna Kuncoro, et al.2022 · 72 citations
9. PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise TrainingarXiv:2309.10400Dawei Zhu, Nan Yang, Liang Wang, et al.2023 · 52 citations
10. Chinese Idiom ParaphrasingTransactions of the Association for Computational Linguistics (TACL)Jipeng Qiang, Yang Li, Chaowei Zhang, et al.2023 · 31 citations
11. POSITION BIAS MITIGATES POSITION BIAS: Mitigate Position Bias Through Inter-Position Knowledge DistillationConference on Empirical Methods in Natural Language Processing (EMNLP)Yifei Wang, Feng Xiong, Yong Wang, et al.2025 · 13 citations
12. Character-aware Transformers Learn an Irregular Morphological Pattern Yet None Generalize Like HumansWorkshop on Cognitive Modeling and Computational Linguistics (CMCL)Akhilesh Kakolu Ramarao, Kevin Tang, Dinah Baer-Henney2026
13. Position Encoding with Random Float Sampling Enhances Length Generalization of TransformersFindings of the Association for Computational LinguisticsAtsushi Shimizu, Shohei Taniguchi, Yutaka Matsuo2026
14. SCOPE: Boosting LLM Efficiency with Scoped Position EncodingAnnual Meeting of the Association for Computational Linguistics (ACL)Qingguo Qi, Hongyang Chen, Zhao Li2026

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

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