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# Who cites «Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words»

61 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/lex-2021-hofmann-superbizarre-derivational/)

1. [Do Diacritics Matter? Evaluating the Impact of Arabic Diacritics on Tokenization and LLM Benchmarks](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2026-inoue-do-diacritics-matter-evaluating-impact/) *— our card · 2026 · Findings of the Association for Computational Linguistics: EACL 2026*
2. [Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://aclanthology.org/2026.findings-acl.1618/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
3. [AdaptiVocab: Enhancing LLM Efficiency in Focused Domains through Lightweight Vocabulary Adaptation](https://arxiv.org/abs/2503.19693) *— 2025 · arXiv:2503.19693*
4. [Evaluating Morphological Compositional Generalization in Large Language Models](https://aclanthology.org/2025.naacl-long.59/) *— 2025 · NAACL 2025 (Albuquerque)*
5. [From Sm{\o}r-re-br{\o}d to Subwords: Training LLMs on Danish, One Morpheme at a Time](https://arxiv.org/abs/2504.01540) *— 2025 · arXiv:2504.01540*
6. [Towards the Machine Translation of Scientific Neologisms](https://aclanthology.org/2025.coling-main.63/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
7. [Unlike ``Likely'''', ``Unlike'''' is Unlikely: BPE-based Segmentation hurts Morphological Derivations in LLMs](https://aclanthology.org/2025.coling-main.348/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
8. [Why do language models perform worse for morphologically complex languages?](https://aclanthology.org/2025.coling-main.441/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
9. [Analyzing the Understanding of Morphologically Complex Words in Large Language Models](https://aclanthology.org/2024.lrec-main.90/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
10. [BPE Gets Picky: Efficient Vocabulary Refinement During Tokenizer Training](https://aclanthology.org/2024.emnlp-main.925/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
11. [BPE-knockout: Pruning Pre-existing BPE Tokenisers with Backwards-compatible Morphological Semi-supervision](https://aclanthology.org/2024.naacl-long.324/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
12. [Derivational Morphology Reveals Analogical Generalization in Large Language Models](https://arxiv.org/abs/2411.07990) *— 2024 · arXiv:2411.07990*
13. [DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain](https://aclanthology.org/2024.lrec-main.478/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
14. [Greed is All You Need: An Evaluation of Tokenizer Inference Methods](https://aclanthology.org/2024.acl-short.73/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
15. [HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/findings-2024-argaman-hesum-novel-dataset-abstractive-text/) *— our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
16. [LLMSegm: Surface-level Morphological Segmentation Using Large Language Model](https://aclanthology.org/2024.lrec-main.933/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
17. [Subword Segmentation in LLMs: Looking at Inflection and Consistency](https://aclanthology.org/2024.emnlp-main.672/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
18. [The Impact of Word Splitting on the Semantic Content of Contextualized Word Representations](https://aclanthology.org/2024.tacl-1.17/) *— 2024 · Transactions of the Association for Computational Linguistics*
19. [Time Machine GPT](https://aclanthology.org/2024.findings-naacl.208/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
20. [Tokenization Is More Than Compression](https://aclanthology.org/2024.emnlp-main.40/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
21. [Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance](https://aclanthology.org/2024.findings-acl.134/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
22. [Analyzing Cognitive Plausibility of Subword Tokenization](https://aclanthology.org/2023.emnlp-main.272/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
23. [Biomedical Language Models are Robust to Sub-optimal Tokenization](https://aclanthology.org/2023.bionlp-1.32/) *— 2023 · Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks*
24. [CompoundPiece: Evaluating and Improving Decompounding Performance of Language Models](https://aclanthology.org/2023.emnlp-main.24/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
25. [Counting the Bugs in ChatGPT''s Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model](https://md.mova.elamur.ai/free/en/docs/papers/lex-2023-weissweiler-chatgpt-wugs-morphology/) *— our card · 2023 · EMNLP 2023 (Singapore)*
26. [Effects of sub-word segmentation on performance of transformer language models](https://aclanthology.org/2023.emnlp-main.459/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
27. [Entropy-guided Vocabulary Augmentation of Multilingual Language Models for Low-resource Tasks](https://aclanthology.org/2023.findings-acl.548/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
28. [Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2023-gueta-explicit-morphological-knowledge-improves-pre/) *— our card · 2023 · arXiv:2311.00658*
29. [Incorporating Context into Subword Vocabularies](https://aclanthology.org/2023.eacl-main.45/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
30. [Language Model Tokenizers Introduce Unfairness Between Languages](https://arxiv.org/abs/2305.15425) *— 2023 · arXiv:2305.15425*
31. [Paloma: A Benchmark for Evaluating Language Model Fit](https://arxiv.org/abs/2312.10523) *— 2023 · arXiv:2312.10523*
32. [Sentence Embedding Models for Ancient Greek Using Multilingual Knowledge Distillation](https://aclanthology.org/2023.alp-1.2/) *— 2023 · Proceedings of the Ancient Language Processing Workshop*
33. [BECEL: Benchmark for Consistency Evaluation of Language Models](https://aclanthology.org/2022.coling-1.324/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
34. [Improving Tokenisation by Alternative Treatment of Spaces](https://aclanthology.org/2022.emnlp-main.786/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
35. [Morphological Processing of Low-Resource Languages: Where We Are and What''s Next](https://aclanthology.org/2022.findings-acl.80/) *— 2022 · Findings of ACL 2022 (Dublin)*
36. [Morphology Without Borders: Clause-Level Morphology](https://aclanthology.org/2022.tacl-1.83/) *— 2022 · Transactions of the Association for Computational Linguistics*
37. [Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment](https://aclanthology.org/2022.coling-1.359/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
38. [Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP](https://arxiv.org/abs/2112.10508) *— 2021 · arXiv:2112.10508*
39. bauwens-2025-grampa-subword-regularisation-skewing-uniform
40. bauwens-2026-rebpe-iteratively-improving-internal-structure
41. chowdhury-2026-benchmarking-byte-pair-encoding-tokenizers
42. chu-2022-signal-noise-exploring-meaning-encoded
43. church-2022-training-lexical-resources
44. dakota-2024-bits-pieces-investigating-effects-subwords
45. garcia-2024-sierra-morphological-evaluation-subwords-vocabulary-used
46. haslett-2025-how-much-semantic-information-is
47. haslett-2025-tokenization-changes-meaning-large-language
48. hudspeth-2024-latin-treebanks-review-evaluation-morphological
49. kazantseva-2024-fitting-square-peg-into-round
50. kiegeland-2026-proper-treatment-units-surprisal-theory
51. knigawka-2022-constructing-derivational-morphology-resource-transformer
52. lee-2026-morpheme-matters-morpheme-based-subword
53. li-2023-can-pretrained-language-models-derive
54. lin-2025-rethinking-vocabulary-augmentation-addressing-challenges
55. madasu-2022-what-do-large-language-models
56. nikolaev-2025-case-number-dissociation-finnish-noun
57. nzeyimana-2025-kinyacolbert-lexically-grounded-retrieval-model
58. oh-2025-incorporating-domain-knowledge-into-materials
59. smith-2024-word-boundary-information-isn-t
60. srivastava-2023-bertwich-extending-bert-s-capabilities
61. xu-2026-tokenization-morphological-fidelity-uralic-nlp
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