Grammar as Control: Modular Language Generation for the Long Tail (2026.acl-long)
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| Challenge: | Large language models (LLMs) can bootstrap language technologies for long-tail languages . however, without structured guidance, they produce narrow, unrepresentative samples . |
| Approach: | They propose a framework that transforms descriptive grammars into explicit control mechanisms that guide LLMs to generate typologically balanced synthetic data for downstream training. |
| Outcome: | The proposed framework improves typological entropy and yields a "student-beats-teacher" effect across three low-resource languages. |
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