--- title: "Who cites Language Models Learn Rare — 38 citing papers" description: "38 papers of the Elamur Research library cite «Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the…" canonical: "https://research.elamur.ai/free/en/papers/misra-2024-language-models-learn-rare-phenomena/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/misra-2024-language-models-learn-rare-phenomena/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Language Models Learn Rare Phenomena from Less…](https://md.research.elamur.ai/free/en/papers/misra-2024-language-models-learn-rare-phenomena/) / cited by # Who cites «Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNs» 38 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNs»](https://md.research.elamur.ai/free/en/papers/misra-2024-language-models-learn-rare-phenomena/) 1. **[Filtered Corpus Training (FiCT) Shows that Language Models Can Generalize from Indirect Evidence](https://md.research.elamur.ai/free/en/papers/patil-2024-filtered-corpus-training-fict-shows/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Abhinav Patil, Jaap Jumelet, Yu Ying Chiu, et al.*2024 · 23 citations* 2. [**Language Models as Models of Language arXiv:2408.07144**Raphael Milliere*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/milliere-2024-language-models-models-language/) 3. **[Is Child-Directed Speech Effective Training Data for Language Models?](https://md.research.elamur.ai/free/en/papers/feng-2024-is-child-directed-speech-effective/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Steven Y. Feng, Noah D. Goodman, Michael C. Frank*2024 · 18 citations* 4. **[Do Construction Distributions Shape Formal Language Learning In German BabyLMs?](https://md.research.elamur.ai/free/en/papers/bunzeck-2025-do-construction-distributions-shape-formal/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Daniel Duran, Sina Zarrieß*2025 · 13 citations* 5. **[What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Length](https://md.research.elamur.ai/free/en/papers/tjuatja-2025-what-goes-into-lm-acceptability/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Lindia Tjuatja, Graham Neubig, Tal Linzen, et al.*2025 · 12 citations* 6. **[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* 7. **[Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race](https://md.research.elamur.ai/free/en/papers/sun-2025-aligned-but-blind-alignment-increases/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lihao Sun, Chengzhi Mao, Valentin Hofmann, et al.*2025 · 10 citations* 8. **[Constructions are Revealed in Word Distributions](https://md.research.elamur.ai/free/en/papers/rozner-2025-constructions-are-revealed-word-distributions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Rozner, Leonie Weissweiler, Kyle Mahowald, et al.*2025 · 9 citations* 9. **[Function Words as Statistical Cues for Language Learning](https://md.research.elamur.ai/free/en/papers/yang-2026-function-words-as-statistical-cues/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiulin Yang, Heidi R. Getz, Ethan Gotlieb Wilcox*2026 · 1 citation* 10. **[Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.*2026 · 1 citation* 11. **[What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies](https://md.research.elamur.ai/free/en/papers/zhou-2026-what-exactly-do-children-receive/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Zhenghao Zhou, William Dai, Maya Viswanathan, et al.*2026 · 1 citation* 12. [**Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networks**Claire Hobbs, R. Thomas McCoy*2026*](https://md.research.elamur.ai/free/en/papers/hobbs-2026-collocational-bootstrapping-hypothesis-about-learning/) 13. **[Cross-Modal Taxonomic Generalization in (Vision-) Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-cross-modal-taxonomic-generalization-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyang Xu, Marcelo Sandoval-Castañeda, Karen Livescu, et al.*2026* 14. **[CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models](https://md.research.elamur.ai/free/en/papers/oba-2026-cxmp-linguistic-minimal-pair-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Miyu Oba, Saku Sugawara*2026* 15. **[Heterogeneity in Formal Linguistic Competence of Language Models: Is Data the Real Bottleneck?](https://md.research.elamur.ai/free/en/papers/renduchintala-2026-heterogeneity-formal-linguistic-competence-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**H S V N S Kowndinya Renduchintala, Sumit Bhatia*2026* 16. **[Metric Grammars: A usage-based grammatical formalism that supports generation, parsing and morphological innovation](https://md.research.elamur.ai/free/en/papers/tabor-2026-metric-grammars-usage-based-grammatical/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Whitney Tabor, Hyosun Lee*2026* 17. **[On the Effect of Hyperparameters in Language Modeling for Computational Linguistics](https://md.research.elamur.ai/free/en/papers/ning-2026-effect-hyperparameters-language-modeling-computational/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruoxi Ning, Yongpeng Zhu, Qingcheng Zeng, et al.*2026* 18. **[Studying Expert-ese: Profiling and Classification of Domain-Specific Language Variation in Architecture with Traditional Machine Learning and LLMs](https://md.research.elamur.ai/free/en/papers/schacht-2026-studying-expert-ese-profiling-classification/) [Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL)](https://md.research.elamur.ai/free/en/venues/latechclfl/)**Carmen Schacht, Renate Delucchi Danhier*2026* 20 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/misra-2024-language-models-learn-rare-phenomena/) — Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNs