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Found 4 papers, 3 papers with code
RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation
Leveraging RAGLAB, we conduct a fair comparison of 6 RAG algorithms across 10 benchmarks.
FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models
The rapid development of large language model (LLM) evaluation methodologies and datasets has led to a profound challenge: integrating state-of-the-art evaluation techniques cost-effectively while ensuring reliability, reproducibility, and efficiency.
CodeShell Technical Report
Through this process, We have curated 100 billion high-quality pre-training data from GitHub.
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
To ensure the reliability of PandaLM, we collect a diverse human-annotated test dataset, where all contexts are generated by humans and labels are aligned with human preferences.
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