LLM-SLM Collaborative Framework of Idiomatic Expression Generation (2026.acl-long)
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| Challenge: | Existing methods for idiomatic expression generation lack parallel data and manual annotations. |
| Approach: | They propose an iterative LLM-SLM collaborative framework that replaces human supervision for idiomatic expression data generation. |
| Outcome: | The proposed framework outperforms DeepSeek-R1 in Chinese Idiom Polishing with a 25.2% improvement in accuracy. |
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