4 citations · 5 across the 4 of their papers we have counts for
4 papers
SambaLingo: Teaching Large Language Models New Languages
Zoltan Csaki, Bo Li, Jonathan Li +7
Despite the widespread availability of LLMs, there remains a substantial gap in their capabilities and availability across diverse languages. One approach to address these issues h…
Efficiently Adapting Pretrained Language Models To New Languages
Zoltan Csaki, Pian Pawakapan, Urmish Thakker +1
Recent large language models (LLM) exhibit sub-optimal performance on low-resource languages, as the training data of these models is usually dominated by English and other high-re…
Adversarial Example Decomposition
Horace He, Aaron Lou, Qingxuan Jiang +3
Research has shown that widely used deep neural networks are vulnerable to carefully crafted adversarial perturbations. Moreover, these adversarial perturbations often transfer acr…
Intermediate Level Adversarial Attack for Enhanced Transferability
Qian Huang, Zeqi Gu, Isay Katsman +5
Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool trained models. Adversarial examples often exhibit black-box transfer, meaning that adversa…