Arab cultural entities that double as everyday Arabic words are harder for language models to recognize, especially when tokenized as single tokens.
Source codes in human communication
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Although information theoretic characterizations of human communication have become increasingly popular in linguistics, to date they have largely involved grafting probabilistic constructs onto older ideas about grammar. Similarities between human and digital communication have been strongly emphasized, and differences largely ignored. However, some of these differences matter: communication systems are based on predefined codes shared by every sender-receiver, whereas the distributions of words in natural languages guarantee that no speaker-hearer ever has access to an entire linguistic code, which seemingly undermines the idea that natural languages are probabilistic systems in any meaningful sense. This paper describes how the distributional properties of languages meet the various challenges arising from the differences between information systems and natural languages, along with the very different view of human communication these properties suggest.
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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On The Origin of Cultural Biases in Language Models: From Pre-training Data to Linguistic Phenomena
Arab cultural entities that double as everyday Arabic words are harder for language models to recognize, especially when tokenized as single tokens.