COLM paper: LLMs claim multilingual support but fail on low-resource languages
anas_ant · x · 2026-08-27
A new position-backed-by-experiments COLM paper coins "incidental multilingualism": LLMs pick up many languages incidentally from web-scale pretraining and claim broad support, yet the lower-resource the language, the more likely they reply in the wrong one.
Key findings:
- The number of languages frontier models claim to support exceeds what they can actually handle on simple tasks like translation and open-ended generation;
- When LLM-powered agents interact in multilingual settings — as they certainly will outside controlled environments — coordination and downstream performance suffer, dubbed the "Tower of Babel" problem.
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