Ambiguous Interpretation

Ambiguous interpretation, the challenge of assigning meaning to inherently unclear information, is a central problem across diverse fields, from linguistics and psychology to artificial intelligence. Current research focuses on understanding how humans and machines resolve ambiguity, exploring techniques like Bayesian modeling for interpreting child speech and leveraging large language models (LLMs) augmented with external knowledge to generate comprehensive answers to ambiguous questions. These efforts aim to improve human-computer interaction, enhance natural language processing capabilities, and provide deeper insights into cognitive processes underlying meaning construction.