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New benchmark and agent framework tackle social media privacy leakage

By PulseAugur Editorial · [1 sources] ·

Researchers have developed SopriBench, a new benchmark designed to evaluate user-level privacy leakage from social media posts. This benchmark utilizes a synthetic dataset derived from real social media accounts and introduces a Privacy Exposure Score (PES) to quantify leakage severity. Additionally, they created Argus, an agentic framework that improves leakage inference by aggregating evidence across multiple posts. AI

IMPACT Introduces novel methods for assessing and mitigating privacy risks in user-generated content.

RANK_REASON The cluster contains a research paper detailing a new benchmark and framework for evaluating privacy leakage. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark and agent framework tackle social media privacy leakage

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The cluster contains a research paper detailing a new benchmark and framework for evaluating privacy leakage. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper, safety
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High
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94 days old
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zifan Peng, Yini Huang, Aiwen Lu, Qiming Ye, Peixian Zhang, Jingyi Zheng, Yule Liu, Xuechao Wang, Xinlei He, Jiaheng Wei ·

    What Your Posts Reveal: A Benchmark and Agentic Framework for User-Level Privacy Leakage on Social Media

    arXiv:2606.06784v1 Announce Type: cross Abstract: Public social media posts can reveal private information through weak cues scattered across text, images, or metadata. Such leakage is often cumulative and cross-post: cues that appear harmless in isolation may jointly expose a us…

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