A weighted in-context influence metric selects effective instruction-tuning data, outperforming baselines while showing that harder samples have lower influence.
Fine-tuning is performed with DeepSpeed ZeRO-3 for memory optimization and bf16 mixed precision, using input sequences truncated to 2,048 tokens
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What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective
A weighted in-context influence metric selects effective instruction-tuning data, outperforming baselines while showing that harder samples have lower influence.