🔗 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?»

1. Lost in the Middle: How Language Models Use Long ContextsTransactions of the Association for Computational Linguistics (TACL)Nelson F. Liu, Kevin Lin, John Hewitt, et al.2023 · 2,584 citations
2. In-context Learning and Induction HeadsarXiv:2209.11895Catherine Olsson, Nelson Elhage, Neel Nanda, et al.2022 · 475 citations
3. Do Prompt-Based Models Really Understand the Meaning of Their Prompts?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Albert Webson, Ellie Pavlick2022 · 407 citations
4. Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for LittleConference on Empirical Methods in Natural Language Processing (EMNLP)Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.2021 · 297 citations
5. Can language models learn from explanations in context?Findings of the Association for Computational LinguisticsAndrew 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 ScenariosAnnual Meeting of the Association for Computational Linguistics (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 ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kellen Tan Cheng, Suma Bhat2024 · 3 citations
8. Investigating the Effect of Pre-finetuning BERT Models on NLI Involving PresuppositionsFindings of the Association for Computational LinguisticsJad Kabbara, Jackie Cheung2023 · 2 citations

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

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