Semantic Interpretation

Semantic interpretation focuses on understanding the meaning of text and data, aiming to bridge the gap between raw input and meaningful representation. Current research emphasizes improving the accuracy and robustness of semantic interpretation across diverse data types, including tabular data, natural language sentences (especially ambiguous ones), and graph structures, leveraging large language models, attention mechanisms, and various neural network architectures. This work is crucial for enhancing the explainability and trustworthiness of AI systems, particularly in applications requiring human-understandable insights from complex data.