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Balancing knowledge and correctness in language models
There is a contrast between the concrete data structures in relational databases and the more vague knowledge in language models. The challenge lies in bridging these two worlds to ensure correctness. To address the issue of hallucinations in language models, it is essential to reduce the tendency to please the user by lying and train models with more reasoning and less knowledge. This approach may lead to a more grounded output with proper references and citations.