11 citations · 22 across the 8 of their papers we have counts for
4 papers · 2 filters
Dynamic Skill Adaptation for Large Language Models
Jiaao Chen, Diyi Yang
We present Dynamic Skill Adaptation (DSA), an adaptive and dynamic framework to adapt novel and complex skills to Large Language Models (LLMs). Compared with previous work which le…
Distilling an End-to-End Voice Assistant Without Instruction Training Data
William Held, Ella Li, Michael Ryan +3
Voice assistants, such as Siri and Google Assistant, typically model audio and text separately, resulting in lost speech information and increased complexity. Recent efforts to add…
DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph
Zhehao Zhang, Jiaao Chen, Diyi Yang
The current paradigm of evaluating Large Language Models (LLMs) through static benchmarks comes with significant limitations, such as vulnerability to data contamination and a lack…
How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs
Yi Zeng, Hongpeng Lin, Jingwen Zhang +3
Most traditional AI safety research has approached AI models as machines and centered on algorithm-focused attacks developed by security experts. As large language models (LLMs) be…