TextReg mitigates prompt distributional overfitting via regularized text-space optimization, reporting up to +16.5% OOD accuracy gains over prior methods on reasoning benchmarks.
A simple weight decay can improve generalization.Advances in neural information processing systems, 4
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
LoRA applied to critics in SAC and FastTD3 reduces critic loss and yields best or competitive policy performance on most evaluated tasks.
citing papers explorer
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TextReg: Mitigating Prompt Distributional Overfitting via Regularized Text-Space Optimization
TextReg mitigates prompt distributional overfitting via regularized text-space optimization, reporting up to +16.5% OOD accuracy gains over prior methods on reasoning benchmarks.
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Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning
LoRA applied to critics in SAC and FastTD3 reduces critic loss and yields best or competitive policy performance on most evaluated tasks.