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until we find ways to evaluate improvement that’s not just next token prediction, we would keep on coming up with methods without knowing on which axes are we improving and trading FLOPs.merging pretrain and post-train already started may 2025 in avataRL and OPD existed much earlier than that as well.
1:20
until we find ways to evaluate improvement that’s not just next token prediction, we would keep on coming up with methods without knowing on which axes are we improving and trading FLOPs.merging pretrain and post-train already started may 2025 in avataRL and OPD existed much earlier than that as well.
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x.comtokenbender
Next Token Prediction is a Fundamental Function of the World
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Your Next-Token Prediction and Transformers Are Biased for Long-Context Modeling - Yifei Wang｜ASAP20
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A simple overview of the Transformer Architecture Transformers process inputs step by step first, text (or tokens) is converted into embeddings and enriched with positional encodings to preserve the order of words In the encoder, layers of self-attention (multi-headed) and linear/feed-forward networks transform these embeddings into contextual representations, where each token "looks at" or attends to others to capture meaning The decoder then takes these encoder outputs along with its own self-
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