3 papers
cs.CL2024
Learning to Ask: When LLM Agents Meet Unclear Instruction
Wenxuan Wang, Juluan Shi, Zixuan Ling +7
Equipped with the capability to call functions, modern large language models (LLMs) can leverage external tools for addressing a range of tasks unattainable through language skills…
cs.SE2024
Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models
Wenxuan Wang, Yuk-Kit Chan, Zixuan Ling +7
Large Language Models (LLMs) like ChatGPT are foundational in various applications due to their extensive knowledge from pre-training and fine-tuning. Despite this, they are prone…
cs.CV2023
LFAA: Crafting Transferable Targeted Adversarial Examples with Low-Frequency Perturbations
Kunyu Wang, Juluan Shi, Wenxuan Wang
Deep neural networks are susceptible to adversarial attacks, which pose a significant threat to their security and reliability in real-world applications. The most notable adversar…