Answer Validation

Answer validation focuses on verifying the correctness and reliability of answers generated by automated systems, particularly large language models and face recognition systems. Current research emphasizes improving verification accuracy by considering not only the final answer but also the underlying reasoning or rationale, employing techniques like pairwise comparisons and incorporating uncertainty measures. This work is crucial for building trustworthy AI systems across diverse applications, ranging from educational tools and medical information systems to security and legal contexts, where reliable and explainable answers are paramount.