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Fact knowledge memorization is crucial for Large Language Models (LLM) to generate factual and reliable responses.
Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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Scaling laws for neural machine translation
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Unified scaling laws for routed language models
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Scaling laws for reward model overoptimization
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Physics of language models: Part 3.2, knowledge manipulation
Zeyuan Allen-Zhu and Yuanzhi Li. 2023 · 2023
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Hybrid hierarchical retrieval for open-domain question answering
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Self-rag: Learning to retrieve, generate, and critique through self-reflection
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Gpt-4 technical report
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Llama 2: Open foundation and fine-tuned chat models
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Siren’s song in the AI ocean: A survey on hallucination in large language models
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The reversal curse: Llms trained on "a is b" fail to learn "b is a"
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Scaling laws for downstream task performance of large language models
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Llatrieval: Llm-verified retrieval for verifiable generation
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