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cs.CL2024
Reranking Laws for Language Generation: A Communication-Theoretic Perspective
António Farinhas, Haau-Sing Li, André F. T. Martins
To ensure large language models (LLMs) are used safely, one must reduce their propensity to hallucinate or to generate unacceptable answers. A simple and often used strategy is to…
cs.CL2024
DOCE: Finding the Sweet Spot for Execution-Based Code Generation
Haau-Sing Li, Patrick Fernandes, Iryna Gurevych +1
Recently, a diverse set of decoding and reranking procedures have been shown effective for LLM-based code generation. However, a comprehensive framework that links and experimental…