Papers with Capability Salience Vector

1 papers
Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law (2025.acl-long)

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Challenge: Large language models have demonstrated impressive performance across a wide range of tasks, but this achievement comes with the trade-off of significant computational demands.
Approach: They propose a scaling law that decomposes the overall validation loss and assigns different importance weights to tokens to assess a specific meta-capability.
Outcome: The proposed model can predict the loss trending of models across different levels of computation without a gap between validation loss and model's downstream capabilities.

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