---
title: "Who cites What Context Features Can — 42 citing papers"
description: "42 papers of the Elamur Research library cite «What Context Features Can Transformer Language Models Use?», found in their…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [What Context Features Can Transformer Language…](https://md.research.elamur.ai/free/en/papers/connor-2021-what-context-features-can-transformer/) / cited by

# Who cites «What Context Features Can Transformer Language Models Use?»

42 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «What Context Features Can Transformer Language Models Use?»](https://md.research.elamur.ai/free/en/papers/connor-2021-what-context-features-can-transformer/)

1. **[Lost in the Middle: How Language Models Use Long Contexts](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,584 citations*
2. [**In-context Learning and Induction Heads arXiv:2209.11895**Catherine Olsson, Nelson Elhage, Neel Nanda, et al.*2022 · 475 citations*](https://md.research.elamur.ai/free/en/papers/olsson-2022-context-learning-induction-heads/)
3. **[Do Prompt-Based Models Really Understand the Meaning of Their Prompts?](https://md.research.elamur.ai/free/en/papers/webson-2022-do-prompt-based-models-really/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Albert Webson, Ellie Pavlick*2022 · 407 citations*
4. **[Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little](https://md.research.elamur.ai/free/en/papers/sinha-2021-masked-language-modeling-distributional-hypothesis/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.*2021 · 297 citations*
5. **[Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 295 citations*
6. **[LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context Scenarios](https://md.research.elamur.ai/free/en/papers/wu-2025-lifbench-evaluating-instruction-following-performance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaodong Wu, Minhao Wang, Yichen Liu, et al.*2025 · 11 citations*
7. **[No Context Needed: Contextual Quandary In Idiomatic Reasoning With Pre-Trained Language Models](https://md.research.elamur.ai/free/en/papers/cheng-2024-no-context-needed-contextual-quandary/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kellen Tan Cheng, Suma Bhat*2024 · 3 citations*
8. **[Investigating the Effect of Pre-finetuning BERT Models on NLI Involving Presuppositions](https://md.research.elamur.ai/free/en/papers/kabbara-2023-investigating-effect-pre-finetuning-bert/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jad Kabbara, Jackie Cheung*2023 · 2 citations*

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

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