Can Promptriever's prompting capability be extended to improve robustness against adversarial query perturbati

Abstract

Abstract: This article surveys and organizes research works in a new paradigm in natural language processing, which we dub “prompt-based learning.” Unlike traditional supervised learning, which trains a model to take in an input x and predict an output y as P ( y|x ), prompt-based learning is based on language models that model the probability of text directly. To use these models to perform prediction tasks, the original input x is modified using a template into a textual string prompt x′ that has some unfilled slots, and then the language model is used to probabilistically fill the unfilled informatio

Research Question

Can Promptriever's prompting capability be extended to improve robustness against adversarial query perturbations in multi-hop QA retrieval tasks, evaluated via accuracy drop under attack compared to non-promptable retrieval models?

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