elvis(@omarsar0):New research from Google DeepMind. (bookmark it) SkillSmith treats model weights as an additional modality the LLM reads natively. The augmented model ingests existing prefix weights alongside rich text describing how a capability relates to a target, then directly outputs new prefix weights that manifest that skill. Skill composition becomes an inference-time operation instead of a training run. The team calls this instruction-steered parametric synthesis. The gains exceed what text-only and weight-only adaptation reach on their own. Paper: https://t.co/FXmBF0Uu6M Track more trending AI papers in our academy:

2026.08.02 16:21

New research from Google DeepMind. (bookmark it) SkillSmith treats model weights as an additional modality the LLM reads natively. The augmented model ingests existing prefix weights alongside rich text describing how a capability relates to a target, then directly outputs new prefix weights that manifest that skill. Skill composition becomes an inference-time operation instead of a training run. The team calls this instruction-steered parametric synthesis. The gains exceed what text-only and weight-only adaptation reach on their own. Paper: Track more trending AI papers in our academy:

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