Machine Reading, Fast and Slow - When Do Models Understand Language?

Explore a thought-provoking lecture on the complexities of machine reading comprehension and the challenges in developing AI models that truly "understand" language. Delve into behavioral benchmarks, reading comprehension assessments, and the limitations of current transformer models. Examine why scale alone doesn't solve comprehension issues and how pre-training knowledge is underutilized. Investigate the lack of shortcuts in language processing, data-related problems, and testing methodologies. Conclude by considering open problems in the field of machine reading and language understanding.