Papers with RPG

2 papers
Rethinking Repetition Problems of LLMs in Code Generation (2025.acl-long)

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Challenge: Recent studies have focused on content repetition, but structural repetition is a more prevalent problem in code generation.
Approach: They propose a decoding approach that eliminates repetition problems in code generation by identifying grammar rules and strategically decaying the likelihood of critical tokens that contribute to repetitions.
Outcome: The proposed approach outperforms baselines and humanEval benchmarks on CodeRepetEval dataset and MBPP benchmarks, effectively reducing repetitions and enhancing the quality of generated code.
Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation (2024.emnlp-main)

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Challenge: Large language models (LLMs) often produce factual errors due to limited internal knowledge.
Approach: They propose a retrieval-augmented generation framework that generates plan tokens to guide subsequent generation.
Outcome: The proposed framework improves the accuracy of large language models with external knowledge sources.

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