Papers with MBPP datasets

2 papers
Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking (2025.emnlp-main)

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Challenge: Existing methods to watermark low-entropy content are expensive and risky . IE reduces parameter size by 99% while achieving performance on par with state-of-the-art methods .
Approach: They propose a logit-based watermarking paradigm that uses entropy-based features to predict whether the next token is high or low.
Outcome: The proposed method reduces parameter size by 99% while achieving performance on par with state-of-the-art methods.
Learning to Insert [PAUSE] Tokens for Better Reasoning (2025.findings-acl)

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Challenge: Existing studies have explored incorporating special-purpose tokens into the training process to enhance reasoning capabilities.
Approach: They propose a method for inserting dummy tokens consecutively just before reasoning steps to increase model effectiveness.
Outcome: The proposed method outperforms fine-tuning and previous token insertion methods on multiple datasets and models.

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