EvoEmbedding: Evolvable Representations for Long-Context Retrieval and Agentic Memory
EvoEmbedding is a dynamic embedding model that generates adaptive representations by maintaining a continuously updated latent memory, enabling improved retrieval performance in lo…
Hugging Face · Daily Papers
·Chang Nie, Chaoyou Fu
·
·▲ 22 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Chang Nie, Chaoyou Fu, Junlan Feng, Caifeng Shan
- 22 upvotes da comunidade
- Temas: evolvable representations, latent memory, sequential processing, joint generation, representation collapse, segment-batching
Resumo
Resumo original (em inglês), extraído do paper:
EvoEmbedding is a dynamic embedding model that generates adaptive representations by maintaining a continuously updated latent memory, enabling improved retrieval performance in long-context scenarios.
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