4 papers
IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs
Chuan Guo, Juan Felipe Ceron Uribe, Sicheng Zhu +10
Instruction hierarchy (IH) defines how LLMs prioritize system, developer, user, and tool instructions under conflict, providing a concrete, trust-ordered policy for resolving instr…
Mapping Smarter, Not Harder: A Test-Time Reinforcement Learning Agent That Improves Without Labels or Model Updates
Wen-Kwang Tsao, Yao-Ching Yu, Chien-Ming Huang
The Enterprise Intelligence Platform must integrate logs from numerous third-party vendors in order to perform various downstream tasks. However, vendor documentation is often unav…
Primus: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training
Yao-Ching Yu, Tsun-Han Chiang, Cheng-Wei Tsai +2
Large Language Models (LLMs) have shown remarkable advancements in specialized fields such as finance, law, and medicine. However, in cybersecurity, we have noticed a lack of open-…
Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling
Yao-Ching Yu, Chun-Chih Kuo, Ziqi Ye +2
Ensembling multiple models has always been an effective approach to push the limits of existing performance and is widely used in classification tasks by simply averaging the class…