Self-Adapting Language Models: Paper Authors Discuss Implications
Deep Papers
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Exploring Self-Adapting Language Models and the Future of Pre-Training
This chapter delves into the difficulties of scaling language models, emphasizing the issue of hallucination in generated outputs. It also discusses adaptive rewriting of information and novel pre-training methods that enable models to forge their own learning paths while building on existing knowledge.
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