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A Cost-Effective LLM-based Approach to Identify Wildlife Trafficking in Online Marketplaces

Summary: Cost-efficient data labeling for wildlife-ad detection using LLM-generated pseudo labels on a diverse, small sample to train specialized classifiers. A sampling-driven pipeline reduces labeling costs while maintaining coverage, achieving up to 95% F1 and enabling scalable analysis of wildlife trafficking in online marketplaces. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7256
Venue
SIGMOD
Year
2025
Pagerank
5.093636e-05
Overall Rank
10,746 | 26.28%
DOI
10.1145/3725256

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BibTeX Citation

@inproceedings{barbosa_sigmod25,
        title = {{A Cost-Effective LLM-based Approach to Identify Wildlife Trafficking in Online Marketplaces}},
        author = {Barbosa, Juliana Silva and Gondhali, Ulhas and Petrossian, Gohar and Sharma, Kinshuk and Chakraborty, Sunandan and Jacquet, Jennifer and Freire, Juliana},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3725256},
        url = {https://dl.acm.org/doi/10.1145/3725256},
        year = {2025}
}

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