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[PDF][PDF] A systematic survey of prompt engineering in large language models: Techniques and applications
Smaller, weaker, yet better: Training llm reasoners via compute-optimal sampling
Training on high-quality synthetic data from strong language models (LMs) is a common
strategy to improve the reasoning performance of LMs. In this work, we revisit whether this …
strategy to improve the reasoning performance of LMs. In this work, we revisit whether this …
Rear: A relevance-aware retrieval-augmented framework for open-domain question answering
Considering the limited internal parametric knowledge, retrieval-augmented generation
(RAG) has been widely used to extend the knowledge scope of large language models …
(RAG) has been widely used to extend the knowledge scope of large language models …