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MGDIL tackles cross-domain social bot detection under two practical problems that most prior systems do not handle well: missing or inconsistent user fields, and severe train-test distribution shif…
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SFDemorpher tackles a practical gap in face demorphing research: most prior methods are trained and evaluated as if every document image is a morph, which is not how border control or document enro…
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This paper addresses a practical gap in bot defense — many websites need something cheaper and less intrusive than CAPTCHAs, but more effective than simple user-agent blacklists
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This paper addresses the looming challenge of scaling AI agents from isolated tools or closed orchestrators into socially integrated, persistent participants in an evolving digital ecosystem dubbed…
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This paper tackles a critical practical barrier for digital accessibility compliance in mathematics education following 2024 Title II ADA updates in the US
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This paper investigates how Android developers perceive platform efforts to reduce user tracking via device fingerprinting, a stealthy method that circumvents user controls and privacy protections
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The paper introduces the 'novelty bottleneck,' a conceptual framework that explains why human effort in AI-assisted tasks scales linearly with task size rather than sublinearly, despite advances in…
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This paper studies a question that most bot-detection work ignores: what happens when the bots are not static, but reinforcement-learning agents that adapt during the campaign? The authors use data…
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This paper addresses the challenge of training large language models (LLMs) for multi-step tool orchestration—executing sequences of API calls with interdependencies—where prior state-of-the-art su…
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This paper addresses the challenging problem of enabling native GUI agents—end-to-end vision-language models that operate directly on raw screenshots—to robustly solve modern interactive CAPTCHA ch…
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SkillProbe addresses critical security challenges in emerging Large Language Model (LLM) agent skill marketplaces, notably semantic-behavioral inconsistencies and inter-skill combinatorial risks
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This paper addresses the critical challenge of understanding and quantifying DRAM cell vulnerabilities that enable multiple security attacks, such as retention failures, Rowhammer, and Rowpress dis…
