Abstract: One effective approach for solving few-shot classification is learning deep representations that measure the similarity between query images and a few support images of specific categories.
FRACTURED-SORRY-Bench is a framework for evaluating the safety of Large Language Models (LLMs) against multi-turn conversational attacks. Building upon the SORRY-Bench dataset, we propose a simple yet ...
Abstract: Zero-shot learning models are capable of classifying new classes by transferring knowledge from the seen classes using auxiliary information. While most of the existing zero-shot learning ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results