--- title: "Who cites Compositionality decomposed: — 146 citing papers" description: "146 papers of the Elamur Research library cite «Compositionality decomposed: how do neural networks generalise?», found in their…" canonical: "https://research.elamur.ai/free/en/papers/hupkes-2019-compositionality-decomposed-neural-networks-generalise/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/hupkes-2019-compositionality-decomposed-neural-networks-generalise/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Compositionality decomposed: how do neural…](https://md.research.elamur.ai/free/en/papers/hupkes-2019-compositionality-decomposed-neural-networks-generalise/) / cited by # Who cites «Compositionality decomposed: how do neural networks generalise?» 146 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 «Compositionality decomposed: how do neural networks generalise?»](https://md.research.elamur.ai/free/en/papers/hupkes-2019-compositionality-decomposed-neural-networks-generalise/) 1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/) 2. [**Scaling Laws for Autoregressive Generative Modeling arXiv:2010.14701**Tom Henighan, Jared Kaplan, Mor Katz, et al.*2020 · 277 citations*](https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/) 3. **[The Impact of Positional Encoding on Length Generalization in Transformers](https://md.research.elamur.ai/free/en/papers/kazemnejad-2023-impact-positional-encoding-length-generalization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, et al.*2023 · 134 citations* 4. [**Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation**Atticus Geiger, Kyle Richardson, Christopher Potts*2020 · 123 citations*](https://md.research.elamur.ai/free/en/papers/geiger-2020-neural-natural-language-inference-models/) 5. **[How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN](https://md.research.elamur.ai/free/en/papers/mccoy-2023-how-much-do-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**R. Thomas McCoy, Paul Smolensky, Tal Linzen, et al.*2023 · 117 citations* 6. [**Large Language Models as General Pattern Machines arXiv:2307.04721**Suvir Mirchandani, Fei Xia, Pete Florence, et al.*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/mirchandani-2023-large-language-models-general-pattern/) 7. **[Are Pretrained Language Models Symbolic Reasoners over Knowledge?](https://md.research.elamur.ai/free/en/papers/kassner-2020-are-pretrained-language-models-symbolic/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Nora Kassner, Benno Krojer, Hinrich Schütze*2020 · 81 citations* 8. **[Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus](https://md.research.elamur.ai/free/en/papers/lee-2024-reasoning-abilities-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Seungpil Lee, Woochang Sim, Donghyeon Shin, et al.*2024 · 38 citations* 9. **[Compositionality and Sentence Meaning: Comparing Semantic Parsing and Transformers on a Challenging Sentence Similarity Dataset](https://md.research.elamur.ai/free/en/papers/fodor-2025-compositionality-sentence-meaning-comparing-semantic/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**James Fodor, Simon De Deyne, Shinsuke Suzuki*2025 · 22 citations* 10. **[Circuit Compositions: Exploring Modular Structures in Transformer-Based Language Models](https://md.research.elamur.ai/free/en/papers/mondorf-2025-circuit-compositions-exploring-modular-structures/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Philipp Mondorf, Sondre Wold, Barbara Plank*2025 · 8 citations* 11. **[Exploring Continual Learning of Compositional Generalization in NLI](https://md.research.elamur.ai/free/en/papers/fu-2024-exploring-continual-learning-compositional-generalization/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xiyan Fu, Anette Frank*2024 · 5 citations* 12. **[Compositional Syntactico-SemBanking for English as a Second or Foreign Language](https://md.research.elamur.ai/free/en/papers/li-2025-compositional-syntactico-sembanking-english-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxi Li, Xihao Wang, Weiwei Sun*2025 · 2 citations* 13. **[From Atomic to Complex tasks: Cross-Tasking Improves Zero-Shot Argument Generation and Retrieval](https://md.research.elamur.ai/free/en/papers/tamine-2026-atomic-complex-tasks-cross-tasking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lynda Tamine, Ahmed Rayane Kebir, Merveille Dona Codjo, et al.*2026* 14. **[Investigating More Explainable and Partition-Free Compositionality Estimation for LLMs: A Rule-Generation Perspective](https://md.research.elamur.ai/free/en/papers/xu-2026-investigating-more-explainable-partition-free/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyao Xu, Cong Wang, Houfeng Wang*2026* 132 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/hupkes-2019-compositionality-decomposed-neural-networks-generalise/) — Compositionality decomposed: how do neural networks generalise?