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Weize Kong

2 accepted papers

2024

Bridging the Preference Gap between Retrievers and LLMs

ACL 2024long

Large Language Models (LLMs) have demonstrated superior results across a wide range of tasks, and Retrieval-augmented Generation (RAG) is an effective way to enhance the performance by locating relevant information and placing it into the context window of the LLM. However, the relationship between…

Cited by 30SourcePDFScholar
2024

PRewrite: Prompt Rewriting with Reinforcement Learning

ACL 2024short

Prompt engineering is critical for the development of LLM-based applications. However, it is usually done manually in a “trial and error” fashion that can be time consuming, ineffective, and sub-optimal. Even for the prompts which seemingly work well, there is always a lingering question: can the pr…

Cited by 10SourcePDFScholar