Can Deception Detection Go Deeper? Dataset, Evaluation, and Benchmark for Deception Reasoning

arXiv:2402.11432v1 Announce Type: new
Abstract: Deception detection has attracted increasing attention due to its importance in many practical scenarios. Currently, data scarcity harms the development of this field. On the one hand, it is costly to hire participants to simulate deception scenarios. On the other hand, it is difficult to collect videos containing deceptive behaviors on the Internet. To address data scarcity, this paper proposes a new data collection pipeline. Specifically, we use GPT-4 to simulate a role-play between a …

abstract arxiv attention benchmark cs.cl data dataset deception detection development evaluation importance practical reasoning type