Distilling Examples into Task Instructions: Enhanced In-Context Learning for Real-World B2B Conversations
A novel approach for B2B conversation classification that reduces token usage by 99% while improving performance and maintaining robustness as context length increases.
Hugging Face · Daily Papers
·Guy Rotman, Adi Kopilov
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·▲ 2 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Guy Rotman, Adi Kopilov, Danit Berger Zalmanson, Omri Allouche
- 2 upvotes da comunidade
- Temas: in-context learning, few-shot examples, token compression, classification logic, semantic complexity, multi-party conversations
Resumo
Resumo original (em inglês), extraído do paper:
A novel approach for B2B conversation classification that reduces token usage by 99% while improving performance and maintaining robustness as context length increases.
