Tokensometimes

Tokensometimes is a term used in computational linguistics and natural language processing to describe a token that appears irregularly within a corpus or across time. Unlike stable high-frequency tokens, tokensometimes shows sporadic presence, often tied to domain shifts, topic drift, or data collection artifacts.

Origin and usage: The coinage blends token, referring to basic units of text such as words or subword units, with sometimes, highlighting intermittent occurrence. It is used descriptively to discuss the challenges posed by tokens that are not consistently represented in training data or vocabularies.

In practice: Tokensometimes affects tokenization, vocabulary maintenance, and embedding learned representations. Frequency analysis, drift detection, and time-series modeling can reveal tokensometimes behavior. It is a particular concern in domain adaptation and cross-domain transfer.

Handling: Approaches include subword models (such as BPE or SentencePiece), byte-level tokenization, dynamic or adaptive vocabularies, data augmentation, and continual learning strategies to maintain robust representations across shifts.

Examples: Terms that arise briefly in a topic-specific corpus, brand names that appear only in certain contexts, or technical terms introduced by new standards. Tokensometimes can also reflect coding artifacts such as inconsistent casing or punctuation attaching to tokens.

See also: tokenization, vocabulary drift, concept drift, domain adaptation, subword modeling.