Understanding the Behaviors of Environment-aware Information Retrieval
Large language models can be trained via reinforcement learning to adapt query formulation strategies for different retrievers, with distinct optimal query styles and improved perf…
Hugging Face · Daily Papers
·Ruifeng Yuan, Chaohao Yuan
·
·▲ 6 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Ruifeng Yuan, Chaohao Yuan, David Dai, Yu Rong, Hong Cheng, Hou Pong Chan
- 6 upvotes da comunidade
- Temas: retrieval-augmented generation, LLMs, reinforcement learning, query formulation strategies, retriever-specific guidance, multi-retrieval-step trajectories
Resumo
Resumo original (em inglês), extraído do paper:
Large language models can be trained via reinforcement learning to adapt query formulation strategies for different retrievers, with distinct optimal query styles and improved performance through retriever-specific guidance and model scaling.
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