Simple Linguistic Inferences of Large Language Models (LLMs): Blind Spots and Blinds

arXiv:2305.14785v2 Announce Type: replace
Abstract: We evaluate LLMs' language understanding capacities on simple inference tasks that most humans find trivial. Specifically, we target (i) grammatically-specified entailments, (ii) premises with evidential adverbs of uncertainty, and (iii) monotonicity entailments. We design evaluation sets for these tasks and conduct experiments in both zero-shot and chain-of-thought setups, and with multiple prompts and LLMs. The models exhibit moderate to low performance on these evaluation sets. Subsequent experiments show that embedding the premise in syntactic constructions …

abstract arxiv blind cs.ai cs.cl design evaluation humans iii inference inferences language language models language understanding large language large language models llms simple tasks type uncertainty understanding