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Chao-Zeng Ma

2 accepted papers

2026

ARBench: Algorithmic Reasoner or API Alchemist? Evaluating LLMs Beyond API Calls

AAAI 2026technical

Large Language Models (LLMs) have demonstrated impressive capabilities in code generation. Like human programmers, LLMs tend to call high-level APIs and libraries to program efficiently. However, this shortcut may hinder LLMs from learning the essential algorithm reasoning, leading instead to rote m

Cited by 0SourcePDFScholar
2026

Dynamic-Static Synergistic Selection Method for Candidate Code Solutions with Generated Test Cases

AAAI 2026technical

Large language models (LLMs) show significant improvement in code generation. A common practice is sampling multiple candidate codes to increase the likelihood of producing an accurate solution. However, effectively identifying the best candidate from the pool is a significant challenge. Although ex

Cited by 0SourcePDFScholar