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Syn-TurnTurk tackles a very practical bottleneck in spoken dialogue systems: deciding when a Turkish user has actually finished a turn, instead of relying on crude silence thresholds that often mis…
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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 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 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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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…
