2024/08/14 by Ivory Yang, Yang, Ivory, Xiaobo Guo +5 · 3 citations
Computer Science · Neuroscience · #Cognitive Science and Education Research #Computation and Language (cs.CL) #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Neural Networks and Applications
paper · pdf · doi:10.48550/arxiv.2408.07676
openalex publication_date 2024/08/14 · openalex created_date 2024/09/11 · openalex updated_date 2026/07/28
This study presents a comprehensive, long-term project to explore the effectiveness of various prompting techniques in detecting dialogical mental manipulation. We implement Chain-of-Thought prompting with Zero-Shot and Few-Shot settings on a binary mental manipulation detection task, building upon existing work conducted with Zero-Shot and Few- Shot prompting. Our primary objective is to decipher why certain prompting techniques display superior performance, so as to craft a novel framework tailored for detection of mental manipulation. Preliminary findings suggest that advanced prompting techniques may not be suitable for more complex models, if they are not trained through example-based learning.