Papers by Omri Allouche
Distilling Examples into Task Instructions: Enhanced In-Context Learning for Real-World B2B Conversations (2026.findings-acl)
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| Challenge: | In-context learning (ICL) is the standard method for low-resource classification, yet its efficacy in specialized domains remains largely unexplored. |
| Approach: | They propose a framework that distills verbose examples into compact, interpretable representations of structured classification criteria and precise task descriptions. |
| Outcome: | The proposed method achieves 99% reduction in token usage and improves macro-averaged AUC by up to 7% over traditional ICL. |