Climbing towards Natural Language Understanding argues that LLMs fundamentally cannot understand anything and that the current results are hyped up by "humanizing" the systems.

We argue in this paper that genuine progress [in natural language understanding] - climbing the right hill - not just the hill on whose slope we currently sit - depends on maintaining clarity around big picture notions such as meaning and understanding in task design and reporting of experimental results.