Disentangling Language Modeling and Boundaries | Paper Citation Record

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This paper cites 2021 , eprint=.

Disentangling Language Modeling and Boundaries 2021 , eprint=

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Disentangling Language Modeling and Boundaries 2024 , eprint=

Reference 2

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This paper cites 2024 , eprint=.

Disentangling Language Modeling and Boundaries 2024 , eprint=

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Observation 80b7f3c9-e6a8-47c5-b771-8ce0895209c2 · outbound

This paper cites Tokenizer Choice For LLM Training: Negligible or Crucial?.

Disentangling Language Modeling and Boundaries Tokenizer Choice For LLM Training: Negligible or Crucial?

Reference 4

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This paper cites Unsupervised Cross-lingual Representation Learning at Scale.

Disentangling Language Modeling and Boundaries Unsupervised Cross-lingual Representation Learning at Scale

Reference 5

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This paper cites WECHSEL : Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.

Disentangling Language Modeling and Boundaries WECHSEL : Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models

Reference 6

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This paper cites LLaMA: Open and Efficient Foundation Language Models.

Disentangling Language Modeling and Boundaries LLaMA: Open and Efficient Foundation Language Models

Reference 7

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Disentangling Language Modeling and Boundaries Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 8

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Disentangling Language Modeling and Boundaries The Llama 3 Herd of Models

Reference 9

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This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Disentangling Language Modeling and Boundaries Gemma: Open Models Based on Gemini Research and Technology

Reference 10

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This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Disentangling Language Modeling and Boundaries Gemma 2: Improving Open Language Models at a Practical Size

Reference 11

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Disentangling Language Modeling and Boundaries Gemma 3 Technical Report

Reference 12

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This paper cites Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=.

Disentangling Language Modeling and Boundaries Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=

Reference 13

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This paper cites Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference.

Disentangling Language Modeling and Boundaries Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Reference 14

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Disentangling Language Modeling and Boundaries Transactions of the association for computational linguistics , volume=

Reference 15

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This paper cites An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT).

Disentangling Language Modeling and Boundaries An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)

Reference 16

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This paper cites FOCUS : Effective Embedding Initialization for Monolingual Specialization of Multilingual Models.

Disentangling Language Modeling and Boundaries FOCUS : Effective Embedding Initialization for Monolingual Specialization of Multilingual Models

Reference 17

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This paper cites Proceedings of the 2013 conference of the North American chapter of the association for computational linguistics: human language technologies , pages=.

Disentangling Language Modeling and Boundaries Proceedings of the 2013 conference of the North American chapter of the association for computational linguistics: human language technologies , pages=

Reference 18

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This paper cites Trans-Tokenization and Cross-lingual Vocabulary Transfers: Language Adaptation of LLMs for Low-Resource NLP.

Disentangling Language Modeling and Boundaries Trans-Tokenization and Cross-lingual Vocabulary Transfers: Language Adaptation of LLMs for Low-Resource NLP

Reference 19

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Disentangling Language Modeling and Boundaries Unresolved cited work

Reference 20

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Disentangling Language Modeling and Boundaries FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 21

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Disentangling Language Modeling and Boundaries O pen S ubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles

Reference 22

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Disentangling Language Modeling and Boundaries Decoupled Weight Decay Regularization

Reference 24

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Disentangling Language Modeling and Boundaries 2023 , eprint=

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Disentangling Language Modeling and Boundaries Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier

Reference 26

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Disentangling Language Modeling and Boundaries MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation

Reference 27

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Disentangling Language Modeling and Boundaries MAUPQA: Massive Automatically-created Polish Question Answering Dataset

Reference 28

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Disentangling Language Modeling and Boundaries 1: A Polish Language Model--Development, Insights, and Evaluation , author=

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Disentangling Language Modeling and Boundaries Byte Latent Transformer: Patches Scale Better Than Tokens

Reference 30

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Disentangling Language Modeling and Boundaries Dynamic Chunking for End-to-End Hierarchical Sequence Modeling

Reference 31

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Disentangling Language Modeling and Boundaries As Good as New. How to Successfully Recycle English GPT-2 to Make Models for Other Languages

Reference 32

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Disentangling Language Modeling and Boundaries Language Contamination Helps Explains the Cross-lingual Capabilities of E nglish Pretrained Models

Reference 33

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Disentangling Language Modeling and Boundaries Knowledge Neurons in Pretrained Transformers

Reference 34

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Disentangling Language Modeling and Boundaries T ok A lign: Efficient Vocabulary Adaptation via Token Alignment

Reference 35

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Disentangling Language Modeling and Boundaries and Vuli\'

Reference 36

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Disentangling Language Modeling and Boundaries The Falcon Series of Open Language Models

Reference 37

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Disentangling Language Modeling and Boundaries Large Vocabulary Size Improves Large Language Models

Reference 38

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Disentangling Language Modeling and Boundaries XLM - V : Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models

Reference 39

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Disentangling Language Modeling and Boundaries On the Cross-lingual Transferability of Monolingual Representations

Reference 40

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Disentangling Language Modeling and Boundaries Cross-lingual Transfer of Monolingual Models

Reference 41

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Disentangling Language Modeling and Boundaries OFA : A Framework of Initializing Unseen Subword Embeddings for Efficient Large-scale Multilingual Continued Pretraining

Reference 42

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Disentangling Language Modeling and Boundaries Tik-to-Tok: Translating Language Models One Token at a Time: An Embedding Initialization Strategy for Efficient Language Adaptation

Reference 43

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Disentangling Language Modeling and Boundaries Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)

Reference 44

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Disentangling Language Modeling and Boundaries G lo V e: Global Vectors for Word Representation

Reference 45

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Disentangling Language Modeling and Boundaries Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning

Reference 46

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Disentangling Language Modeling and Boundaries Mini-Model Adaptation: Efficiently Extending Pretrained Models to New Languages via Aligned Shallow Training

Reference 47

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Disentangling Language Modeling and Boundaries Advances in Neural Information Processing Systems , volume=

Reference 48

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Disentangling Language Modeling and Boundaries Proceedings of the 40th International Conference on Machine Learning , pages =

Reference 49

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Disentangling Language Modeling and Boundaries Post \#9194 on Telegram Channel Zaduha

Reference 50

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Disentangling Language Modeling and Boundaries doi:10.5281/zenodo.12608602 , url =

Reference 51

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Disentangling Language Modeling and Boundaries The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

Reference 52

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Disentangling Language Modeling and Boundaries Global MMLU : Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation

Reference 53

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Disentangling Language Modeling and Boundaries Measuring Massive Multitask Language Understanding

Reference 54

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Disentangling Language Modeling and Boundaries No Language Left Behind: Scaling Human-Centered Machine Translation

Reference 55

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Disentangling Language Modeling and Boundaries Unresolved cited work

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This paper cites The FLoRes Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English.

Disentangling Language Modeling and Boundaries The FLoRes Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English

Reference 57

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Disentangling Language Modeling and Boundaries On the Path to Make U krainian a High-Resource Language

Reference 58

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Disentangling Language Modeling and Boundaries Qwen Technical Report

Reference 59

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Disentangling Language Modeling and Boundaries 2025 , eprint=

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Disentangling Language Modeling and Boundaries Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI era , month =

Reference 61

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Disentangling Language Modeling and Boundaries From Tokens to Words: On the Inner Lexicon of LLMs

Reference 62

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Disentangling Language Modeling and Boundaries The Fourteenth International Conference on Learning Representations , year=

Reference 63

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Reference 64

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Reference 65

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Disentangling Language Modeling and Boundaries Saiful and Mubasshir, Kazi and Li, Yuan-Fang and Kang, Yong-Bin and Rahman, M

Reference 66

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Disentangling Language Modeling and Boundaries WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects

Reference 67

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Disentangling Language Modeling and Boundaries 2018 , editor =

Reference 68

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Reference 69

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Disentangling Language Modeling and Boundaries Distilling the Knowledge in a Neural Network

Reference 70

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Reference 71

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Disentangling Language Modeling and Boundaries Recovered in Translation: Efficient Pipeline for Automated Translation of Benchmarks and Datasets

Reference 72

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Disentangling Language Modeling and Boundaries arXiv preprint arXiv:2512.15586 , year=

Reference 73

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This paper cites B y T 5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models.

Disentangling Language Modeling and Boundaries B y T 5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models

Reference 74

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Disentangling Language Modeling and Boundaries Model-Aware Tokenizer Transfer

Reference 75

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Disentangling Language Modeling and Boundaries Universal

Reference 76

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Disentangling Language Modeling and Boundaries Unresolved cited work

Reference 77

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Disentangling Language Modeling and Boundaries Cross-Tokenizer

Reference 78

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