1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025
How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?
Meiqi Liu, Zhuoqun Huang, Yue Xing
With the rise of powerful foundation models, a pre-training-fine-tuning paradigm becomes increasingly popular these days: A foundation model is pre-trained using a huge amount of d…
cs.LG2024★ 1 cited
Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective
Shenglai Zeng, Jiankun Zhang, Bingheng Li +8
Retrieval-Augmented Generation (RAG) systems have shown promise in enhancing the performance of Large Language Models (LLMs). However, these systems face challenges in effectively…