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A practical decoding algorithm for code generation is designed and evaluated it alongside CTD on benchmarks including HumanEval and MBPP, showing improvements over standard and adaptive decoding baselines.
This paper develops a rigorous information-theoretic framework for non-repetitive sequence generation and uses it to provide theoretical underpinnings for temperature-based sampling, and extends it to the practically relevant and novel online setting, where the model’s token distributions evolve and are revealed sequen...
This work proposes a novel and practical framework for dependence testing in labeled graphs via mutual information over a structure-weighted joint label distribution and demonstrates that the proposed test is a statistically sound and an effective tool for uncovering nontrivial dependencies in graph data.
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