Papers with instruction-based learning

1 papers
David helps Goliath: Inference-Time Collaboration Between Small Specialized and Large General Diffusion LMs (2024.naacl-long)

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Challenge: Existing studies of diffusion-based language models have been conducted on a smaller scale.
Approach: They propose to scale an autoregressive diffusion model from 0.4B to 13B parameters and propose techniques to improve its training and inference efficiency.
Outcome: The proposed model is able to combine a large general-purpose diffusion model with smaller, but specialized and contextualized diffusion models at inference time.

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