5 papers
Poster: Exploring the Limits of Audio-Based Detection of Turkish Phone Call Scams
Arda Eren, Micheal Cheung, Youqian Zhang +2
Scam phone calls exploit vulnerable communities worldwide, yet research on detection has focused almost exclusively on English and other high-resource languages. In low-resource se…
One Size Fits All? A Modular Adaptive Sanitization Kit (MASK) for Customizable Privacy-Preserving Phone Scam Detection
Kangzhong Wang, Zitong Shen, Youqian Zhang +4
Phone scams remain a pervasive threat to both personal safety and financial security worldwide. Recent advances in large language models (LLMs) have demonstrated strong potential i…
CMIS-Net: A Cascaded Multi-Scale Individual Standardization Network for Backchannel Agreement Estimation
Yuxuan Huang, Kangzhong Wang, Eugene Yujun Fu +2
Backchannels are subtle listener responses, such as nods, smiles, or short verbal cues like "yes" or "uh-huh," which convey understanding and agreement in conversations. These sign…
"It Warned Me Just at the Right Moment": Exploring LLM-based Real-time Detection of Phone Scams
Zitong Shen, Sineng Yan, Youqian Zhang +3
Despite living in the era of the internet, phone-based scams remain one of the most prevalent forms of scams. These scams aim to exploit victims for financial gain, causing both mo…
Combating Phone Scams with LLM-based Detection: Where Do We Stand?
Zitong Shen, Kangzhong Wang, Youqian Zhang +2
Phone scams pose a significant threat to individuals and communities, causing substantial financial losses and emotional distress. Despite ongoing efforts to combat these scams, sc…