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--- nlp:tokenization [2024/06/28 03:46] – jmflanig
+++ nlp:tokenization [2024/07/12 03:28] (current) – [Miscellaneous Papers about Tokenization] jmflanig
@@ Line 34: / Line 34: @@
   * Gradient-based Subword Tokenization: **[[https://arxiv.org/pdf/2106.12672.pdf|Tay et al 2021 - Charformer: Fast Character Transformers via Gradient-based Subword Tokenization]]**
-===== Effects and Choice of Tokenization =====
+==== Effects and Choice of Tokenization ====
   * [[https://arxiv.org/pdf/2310.08754|Ali et al 2024 - Tokenizer Choice For LLM Training: Negligible or Crucial?]] HuggingFace implementation of BPE seems to be suboptimal, see table 3.
 ===== Miscellaneous Papers about Tokenization =====
   * [[https://aclanthology.org/2024.eacl-long.72.pdf|Christopoulou et al 2024 - Text-to-Code Generation with Modality-relative Pre-training]] Adds domain-specific tokens to a pretrained LM for text-to-code
+  * [[https://arxiv.org/pdf/2406.20086|Feucht et al 2024 - Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs]] Finds the implicit vocabulary in a Transformer decoder model
 ===== Stopwords =====
@@ Line 51: / Line 52: @@
   * SentencePiece (does BPE and subword regularization): [[https://github.com/google/sentencepiece]] You don't need to run the Moses tokenizer first (see the [[https://aclanthology.org/D18-2012.pdf|paper]])
   * [[https://github.com/glample/fastBPE|fastBPE]]: A fast C++ implementation of BPE
+===== Related Pages =====
+  * [[Data Preparation]]