--- title: "Who cites Studying the Inductive Biases of — 47 citing papers" description: "47 papers of the Elamur Research library cite «Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages», found…" canonical: "https://research.elamur.ai/free/en/papers/ravfogel-2019-studying-inductive-biases-rnns-synthetic/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ravfogel-2019-studying-inductive-biases-rnns-synthetic/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Studying the Inductive Biases of RNNs with…](https://md.research.elamur.ai/free/en/papers/ravfogel-2019-studying-inductive-biases-rnns-synthetic/) / cited by # Who cites «Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages» 47 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages»](https://md.research.elamur.ai/free/en/papers/ravfogel-2019-studying-inductive-biases-rnns-synthetic/) 1. [**Calibrate Before Use: Improving Few-Shot Performance of Language Models arXiv:2102.09690**Tony Z. Zhao, Eric Wallace, Shi Feng, et al.*2021 · 825 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2021-calibrate-before-use-improving-few/) 2. [**What Artificial Neural Networks Can Tell Us About Human Language Acquisition arXiv:2208.07998**Alex Warstadt, Samuel R. Bowman*2022 · 177 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2022-artificial-neural-networks-tell-us/) 3. **[UnNatural Language Inference](https://md.research.elamur.ai/free/en/papers/sinha-2021-unnatural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, et al.*2021 · 135 citations* 4. **[Does Syntax Need to Grow on Trees? Sources of Hierarchical Inductive Bias in Sequence-to-Sequence Networks](https://md.research.elamur.ai/free/en/papers/mccoy-2020-does-syntax-need-grow-trees/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**R. Thomas McCoy, Robert Frank, Tal Linzen*2020 · 123 citations* 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. **[Cross-Linguistic Syntactic Evaluation of Word Prediction Models](https://md.research.elamur.ai/free/en/papers/mueller-2020-cross-linguistic-syntactic-evaluation-word/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou, et al.*2020 · 98 citations* 7. [**Zoology: Measuring and Improving Recall in Efficient Language Models arXiv:2312.04927**Simran Arora; Sabri Eyuboglu; Aman Timalsina; Isys Johnson; Michael Poli; James Zou; Atri Rudra;, Christopher Re*2023 · 55 citations*](https://md.research.elamur.ai/free/en/papers/arora-2023-zoology-measuring-improving-recall-efficient/) 8. **[Compositional Evaluation on Japanese Textual Entailment and Similarity](https://md.research.elamur.ai/free/en/papers/yanaka-2022-compositional-evaluation-japanese-textual-entailment/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Hitomi Yanaka, Koji Mineshima*2022 · 33 citations* 9. **[A Cross-Linguistic Pressure for Uniform Information Density in Word Order](https://md.research.elamur.ai/free/en/papers/clark-2023-cross-linguistic-pressure-uniform-information/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Thomas Hikaru Clark, Clara Meister, Tiago Pimentel, et al.*2023 · 24 citations* 10. **[On the Difficulty of Translating Free-Order Case-Marking Languages](https://md.research.elamur.ai/free/en/papers/bisazza-2021-difficulty-translating-free-order-case/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Arianna Bisazza, Ahmet Üstün, Stephan Sportel*2021 · 19 citations* 11. **[Can Language Models Learn Typologically Implausible Languages?](https://md.research.elamur.ai/free/en/papers/xu-2026-can-language-models-learn-typologically/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tianyang Xu, Tatsuki Kuribayashi, Yohei Oseki, et al.*2026 · 10 citations* 36 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/ravfogel-2019-studying-inductive-biases-rnns-synthetic/) — Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages