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Ethan Yu

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#artificial intelligence Apr 2026

Beyond Output Correctness: Benchmarking and Evaluating Large Language Model Reasoning in Coding Tasks

This work introduces CodeRQ-Bench, the first benchmark for evaluating LLM reasoning quality across three coding task categories: generation, summarization, and classification, and proposes VERA, a two-stage evaluator that combines evidence-grounded verification with ambiguity-aware score correction.

Yuangang Li, Justin Tian Jin Chen, Ethan Yu et al. · 1 citation