SOURCE-LINKED INTELLIGENCE
SA-Bench: Evaluating Semantic Alignment in LLM-Based Paper Reproduction
LLM agents can generate paper reproduction code, yet often produce scientifically unfaithful implementations. We define this failure mode as semantic drift, where generated code silently diverges from the paper's specifications. We introduce SemanticAlign-Bench(SA-Bench), a diagnostic benchmark covering 30 papers from ICLR, ICML and NeurIPS 2025. For each paper, we decompose its specifications into atomic and verifiable implementation claims, which we call Semantic Alignment Units (SAUs) and evaluate repositories along four diagnostic dimensions spanning numerical, methodological, protocol and
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T08:48:48.000Z
First collected: 2026-09-21T10:02:02.728Z. This is not the publication date.