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BRIDGE is presented as a response to two intertwined problems in IoT botnet detection: most papers only report single-dataset results, and the available IoT security datasets use incompatible featu…
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This paper addresses the metric structure of graphs excluding a fixed graph H as a fat minor, a coarse analogue of the classic minor exclusion in graph theory
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This paper asks a practical, under-studied question: once teams turn on CI/CD caching in GitHub Actions, how do they actually keep it working over time? The authors treat caching as a maintenance p…
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This paper addresses the challenge of social bot detection across multiple heterogeneous social media platforms, where data distributions and model architectures vary and privacy constraints preven…
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This paper asks a verifier-centered question that prior synthetic-face work usually avoids: given a fixed face-recognition threshold, how many latent identities can a generator produce so that same…
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This paper addresses the challenge of retrieving relevant information from long, multi-modal web interaction histories in agentic web navigation tasks
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This paper addresses a fundamental incentive problem in Bitcoin's proof-of-work mining: the standard Bitcoin mining protocol is not a Nash equilibrium because miners can increase their payoff by de…
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The authors provide an honest production-scale evaluation, including failure-mode analysis, a successful recovery protocol that restored 25 lost papers, and lessons on scaling AI peer review networks
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This paper addresses the challenge of transforming static digital assets, particularly code repositories, into autonomous, interoperable agents within the envisioned Agentic Web ecosystem
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This paper addresses the challenge that state-of-the-art multimodal large language models (LLMs) have rendered traditional CAPTCHAs ineffective for distinguishing humans from automated agents
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The paper addresses the emerging threat of social bots driven by large language models (LLMs), which generate highly human-like content that evades traditional bot detection methods
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This paper addresses a core inefficiency in autonomous web agents that currently rely heavily on browser automation to interact with websites designed for human users
