Papers by Zhengran Zeng

2 papers
RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation (2024.emnlp-demo)

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Challenge: Existing research on Retrieval Augmented Generation (RAG) does not address the problem of hallucinations and real-time updating of knowledge.
Approach: They propose a modular open-source library to equip LLMs with external knowledge.
Outcome: The proposed approach reduces the need for expensive open-source tools and lacks fair comparisons between novel RAG algorithms.
FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models (2024.emnlp-demo)

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Challenge: Large language models (LLMs) have revolutionized natural language processing with impressive performance across various tasks.
Approach: They propose a framework for automated evaluations of large language models . they open-source their code at https://github.com/WisdomShell/FreeEval .
Outcome: The framework is open-source and can be used to develop and validate new evaluation methods.

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