21 citations · 63 across the 17 of their papers we have counts for
3 papers · 1 filter
Fast or Better? Balancing Accuracy and Cost in Retrieval-Augmented Generation with Flexible User Control
Jinyan Su, Jennifer Healey, Preslav Nakov +1
Retrieval-Augmented Generation (RAG) has emerged as a powerful approach to mitigate large language model (LLM) hallucinations by incorporating external knowledge retrieval. However…
Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks
Jinyan Su, Jin Peng Zhou, Zhengxin Zhang +2
Retrieval-Augmented Generation (RAG) systems have emerged as a promising solution to mitigate LLM hallucinations and enhance their performance in knowledge-intensive domains. Howev…
Corpus Poisoning via Approximate Greedy Gradient Descent
Jinyan Su, Preslav Nakov, Claire Cardie
Dense retrievers are widely used in information retrieval and have also been successfully extended to other knowledge intensive areas such as language models, e.g., Retrieval-Augme…