How does the code generation accuracy of 13B and 34B parameter-efficient fine-tuned models compare on the Huma

Abstract

Abstract: Abstract The rapid evolution of large language models (LLMs) has driven a transformative shift in artificial intelligence (AI), reshaping both research paradigms and practical applications. Distinguished from their predecessors by unprecedented scale and advanced capabilities, LLMs necessitate new frameworks for understanding their development, behavior, and societal impact. This survey systematically reviews recent advancements in LLM techniques across four key dimensions: (1) pre-training methodologies, which establish core model capabilities through large-scale self-supervised training, arc

Research Question

How does the code generation accuracy of 13B and 34B parameter-efficient fine-tuned models compare on the HumanEval benchmark, and what are the per-token inference latency differences?

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Quality Tier

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Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

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Provenance