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Same idea here? Larger models do a better job forgetting their training data and dropping their semantic priors. Perhaps another way of thinking through this is
by tartakovsky 3y ago
Same idea here? Larger models do a better job forgetting their training data and dropping their semantic priors. Perhaps another way of thinking through this is that larger models learn new information and drop old information faster. https://arxiv.org/abs/2303.03846 https://arxiv.org/abs/2303.03846
Isn't that interesting? The idea of "mental liquidity", or "strong opinions weakly held"? https://news.ycombinator.com/item?id=36280772 https://news.ycombinator.com/item?id=36280772
- indus 3y agoWouldn’t this be the equivalent of ranking? I thought LLM are not supposed to get influenced by freshness.
- marcosdumay 3y agoBy the freshness of training with some data? Well, aren't they? I believe any kind of reinforcement learning is supposed to be biased into the last training set.