Unverified50% confidenceFactExact time
大多数主流分词器（BPE、WordPiece）将数字按字符级别分割，导致数字的位值结构在输入阶段就已被破坏
1
Sources
50%
Confidence
Long-term
Relevance
7/6/2026
First Seen
Sources
Fixing the Three Big Weaknesses of LLMs: Knowledge, Computation, and Tool Use
bilibili晴天AI实战7/4/2026
Related Claims
UnverifiedLLM的分词器（如BPE）为自然语言设计，会将数值拆解为多个不相关的token，破坏数字的连续性和大小语义75% similarVerifiedBPE的核心思路是从字符级别出发，反复合并出现频率最高的相邻字符对，直到词汇表达到预设大小72% similarUnverifiedTokenization algorithms like BPE (Byte Pair Encoding) split words into sub-word segments; for example, 'understanding' might be split into 'under', 'stand', and 'ing'68% similarVerifiedThe byte pair encoding (BPE) or WordPiece algorithms widely used in modern large models are essentially data-driven morphological segmentation methods.66% similarUnverifiedMainstream large models generally use Byte Pair Encoding (BPE) or its variants (such as SentencePiece and tiktoken) for tokenization.66% similar
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