STRATEGY

Summary from the TLDR AI newsletter

Traditional image-text matching models often mistakenly use highly similar but not matching samples, known as false negatives, which can misguide the learning process. This paper introduces the False Negative Elimination strategy, a novel method that carefully selects negatives by assessing their probability of being false negatives.