Papers with generate-then-ground

1 papers
Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering (2024.acl-long)

Copied to clipboard

Challenge: Existing approaches to solve multi-hop question are constrained by the retriever and the noise in the retrieved documents.
Approach: They propose a framework that integrates parametric knowledge of large language models with external documents to solve a multi-hop question.
Outcome: The proposed framework is based on the parametric knowledge of LLMs and external documents to solve a multi-hop question.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations