Formalizes nonlinear M2M regression and introduces transformer architectures as static maps and dynamic velocity fields between probability measures, tested on synthetic, particle, and organoid datasets.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A learned translator converts soft prompts to hard natural-language prompts, outperforming training-free baselines like InSPEcT and enabling portable prompts that exceed original soft-prompt performance on larger models.
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Learning to Translate from Soft to Hard LLM Prompts
A learned translator converts soft prompts to hard natural-language prompts, outperforming training-free baselines like InSPEcT and enabling portable prompts that exceed original soft-prompt performance on larger models.