Equation 33 · Part 1 · Shrink It, Train It Small, or Search for It: The Main Strategies for Small Models, Compared
Symbol C_lifetime
What this part means
ifetime is part of the quantity the equation computes from the expression on the right.
Its job in the formula
ifetime is part of the quantity the equation computes from the expression on the right.
Full expression→Symbol C_lifetime→Article meaning
The passage around this formula
Set side by side, the four strategies do not compete on a single scale, and a comparison that reduces them to one leaderboard number is not describing what any of them actually trades off. Each holds a different quantity fixed as “already spent” and treats a different quantity as the one still to be paid: . Compression pays mostly , a documented small fraction of a from-scratch training cost [ 3 ] , but only if a suitable large model is available to reuse in the first place. Training small on purpose pays and in full, with no discount, in exchange for a model that inherits nothing it was not deliberately given.…
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Sources cited in the surrounding passage
- [3] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning ↗
- [7] Neural Architecture Search with Reinforcement Learning ↗
- [10] Once for All: Train One Network and Specialize it for Efficient Deployment ↗
These citations provide research context; check each source for the exact claim it supports.