With recent developments in language modeling (LM) research, machine-generated text applications have spread to a number of previously untapped domains. However, a significant issue remains that LM-generated text frequently contains factual errors or inconsistencies. This problem usually arises in any LM generation scenario, but it is particularly problematic when generation is performed in uncommon domains … Continue reading AI21 Labs Proposes A New Method Called ‘In-Context RALM’ That Can Add Ready-Made External Knowledge Sources To The Existing Language Model