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Adaptive Frequency Threshold Byte Pair Encoding for Mixed Natural Language and Structured Symbolic Corpora

Paper recorded by Signals 4 on 2026-10-23 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-23 on arXiv · recorded by Signals 4 on 2026-10-26

Category: cs.LG · 机器学习 · first seen 2026-10-26

Abstract

Modern language models rely on subwording tokenization to define the discrete units of input processing, typically using methods like Byte Pair Encoding (BPE) that treat whitespace as a fixed semantic boundary. This design is inherently limited, as many meaningful concepts---including multiword expressions and the structured environments of formal languages like LaTeX---frequently span across whit

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#183 most recent of 749 cs.LG papers we have recorded · ↑ newer: ZENO: Nonlinear filtering with Zakai Equation Neural Operators · ↓ older: A Tutorial on Physics Constrained Machine Learning for Hybrid Modeling
Cite this page: Adaptive Frequency Threshold Byte Pair Encoding for Mixed Natural Language and Structured Symbolic Corpora: the #183 most recent of 749 cs.LG papers we have recorded (as of 2026-10-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/adaptive-frequency-threshold-byte-pair-encoding-for-mixed-natural-language-and-s.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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