Semantic Equivalence

Semantic equivalence focuses on identifying when different representations—be they queries, code, or sentences—convey the same meaning, a crucial task across diverse fields. Current research emphasizes developing efficient algorithms and models, including machine learning-based approaches and those leveraging abstract meaning representations or execution results, to detect this equivalence automatically, even across modalities like vision and language. This work is significant for improving the efficiency of large-scale data processing, enhancing the reliability of AI systems, and optimizing user experiences in applications like e-commerce search and natural language-to-code translation.