23 citations · 108 across the 18 of their papers we have counts for
5 papers · 1 filter
Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks
Samuele Poppi, Zheng-Xin Yong, Yifei He +4
Recent advancements in Large Language Models (LLMs) have sparked widespread concerns about their safety. Recent work demonstrates that safety alignment of LLMs can be easily remove…
Preference Tuning For Toxicity Mitigation Generalizes Across Languages
Xiaochen Li, Zheng-Xin Yong, Stephen H. Bach
Detoxifying multilingual Large Language Models (LLMs) has become crucial due to their increasing global use. In this work, we explore zero-shot cross-lingual generalization of pref…
A Safe Harbor for AI Evaluation and Red Teaming
Shayne Longpre, Sayash Kapoor, Kevin Klyman +20
Independent evaluation and red teaming are critical for identifying the risks posed by generative AI systems. However, the terms of service and enforcement strategies used by promi…
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model
Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong +14
Recent breakthroughs in large language models (LLMs) have centered around a handful of data-rich languages. What does it take to broaden access to breakthroughs beyond first-class…
LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons
Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach
Data scarcity in low-resource languages can be addressed with word-to-word translations from labeled task data in high-resource languages using bilingual lexicons. However, bilingu…