David Hong

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.