Papers by Benjamin Ashpole

2 papers
MATCHED: Multimodal Authorship-Attribution To Combat Human Trafficking in Escort-Advertisement Data (2025.findings-acl)

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Challenge: Existing methods for human trafficking detection ignore the multimodal nature of online ads . sex trafficking is a pervasive crime exploiting individuals of all ages and genders .
Approach: They propose to use multimodal authorship attributes to identify suspicious ads that combine text and images to improve vendor identification and verification tasks.
Outcome: The proposed model outperforms existing methods for vendor identification and verification tasks using text-only, vision-only and multimodal training objectives.
IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements (2023.emnlp-main)

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Challenge: a significant number of human trafficking cases are associated with online advertisements . identification of HT vendors is challenging for law enforcement agencies .
Approach: IDTraffickers uses 87,595 text ads and 5,244 vendor labels to link HT vendors . a macro-F1 score is achieved in a closed-set classification environment .
Outcome: IDTraffickers is a dataset that enables verification and identification of HT vendors . the model achieves a macro-F1 score in a closed-set classification environment .

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