Co-occurring keywords · papers mentioning both
Papers
MoVoC: Morphology-Aware Subword Construction for Ge’ez Script Languages
EMNLP 2025
Multidimensional Byte Pair Encoding: Shortened Sequences for Improved Visual Data Generation
ICCV 2025
R-BPE: Improving BPE-Tokenizers with Token Reuse
EMNLP 2025
Rethinking Tokenization for Rich Morphology: The Dominance of Unigram over BPE and Morphological Alignment
IJCNLP 2025
Scaffold-BPE: Enhancing Byte Pair Encoding for Large Language Models with Simple and Effective Scaffold Token Removal
AAAI 2025
Segmentation Beyond Defaults: Asymmetrical Byte Pair Encoding for Optimal Machine Translation Performance
AACL 2025
Self-Vocabularizing Training for Neural Machine Translation
NAACL 2025
Semitic Root Encoding: Tokenization Based on the Templatic Morphology of Semitic Languages in NMT
EMNLP 2025
Tokenization is Sensitive to Language Variation
ACL 2025
Train It and Forget It: Merge Lists are Unnecessary for BPE Inference in Language Models
EMNLP 2025
Transformers: Leveraging OpenNMT and Transfer Learning for Low-Resource Indian Language Translation
EMNLP 2025
Unified Multimodal Understanding via Byte-Pair Visual Encoding
ICCV 2025
Unlike “Likely”, “Unlike” is Unlikely: BPE-based Segmentation hurts Morphological Derivations in LLMs
COLING 2025
When Every Token Counts: Optimal Segmentation for Low-Resource Language Models
COLING 2025
An Analysis of BPE Vocabulary Trimming in Neural Machine Translation
NAACL 2024
A Systematic Analysis of Subwords and Cross-Lingual Transfer in Multilingual Translation
NAACL 2024
BPE Gets Picky: Efficient Vocabulary Refinement During Tokenizer Training
EMNLP 2024
BPE-knockout: Pruning Pre-existing BPE Tokenisers with Backwards-compatible Morphological Semi-supervision
NAACL 2024
Distributional Properties of Subword Regularization
EMNLP 2024
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes
ICLR 2024
Finding the Optimal Byte-Pair Encoding Merge Operations for Neural Machine Translation in a Low-Resource Setting
EMNLP 2024
Getting the most out of your tokenizer for pre-training and domain adaptation
ICML 2024
Greed is All You Need: An Evaluation of Tokenizer Inference Methods
ACL 2024
How Important Is Tokenization in French Medical Masked Language Models?
COLING 2024
Length-aware Byte Pair Encoding for Mitigating Over-segmentation in Korean Machine Translation
ACL 2024