4 papers
HIPO: Instruction Hierarchy via Constrained Reinforcement Learning
Keru Chen, Jun Luo, Sen Lin +4
Hierarchical Instruction Following (HIF) refers to the problem of prompting large language models with a priority-ordered stack of instructions. Standard methods like RLHF and DPO…
Capturing the Effects of Quantization on Trojans in Code LLMs
Aftab Hussain, Sadegh AlMahdi Kazemi Zarkouei, Md Rafiqul Islam Rabin +3
Large language models of code exhibit high capability in performing diverse software engineering tasks, such as code translation, defect detection, text-to-code generation, and cod…
Unlearning Trojans in Large Language Models: A Comparison Between Natural Language and Source Code
Mahdi Kazemi, Aftab Hussain, Md Rafiqul Islam Rabin +2
This work investigates the application of Machine Unlearning (MU) for mitigating the impact of trojans embedded in conventional large language models of natural language (Text-LLMs…
Optimal predictive probability designs for randomized biomarker-guided oncology trials
Emily C. Zabor, Alexander M. Kaizer, Nathan A. Pennell +1
Efforts to develop biomarker-targeted anti-cancer therapies have progressed rapidly in recent years. Six antibodies acting on programmed death ligand 1 or programmed death 1 pathwa…