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EdgeJury addresses the challenge of hallucinations and untruthful answers in question answering under resource-constrained, serverless edge inference settings, where using very large models or retr…
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This paper addresses the critical problem of detecting social bots on social media platforms by leveraging the heterogeneity of local network structures through a theoretically grounded motif-based…
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This paper addresses the challenge of detecting collaborative fraud within massive heterogeneous account graphs representing online payment platforms
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This paper asks a simple but important question for bot-defense and biometric security: if a generative human-animation model makes a video look convincing, does it also preserve the subject’s gait…
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This paper investigates whether promotional social bots on Twitter exhibit systematic behavioural changes over time, challenging the common assumption that bot behaviours and associated features re…
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The paper analyzes EIP-7702, a delegation-based Ethereum authorization scheme that allows an externally owned account (EOA) to sign a single authorization tuple which reroutes all subsequent calls …
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This paper investigates the privacy practices and risks associated with browser agents—tools that automate web browsing using large language models (LLMs)
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This paper addresses the critical problem of detecting phishing URLs, a major cybersecurity threat used to steal personal information
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This paper addresses the problem of perfect Lp sampling in turnstile data streams, focusing on vectors x∈{−poly(n),...,poly(n)}^n updated by turnstile operations, and sampling indices with exact pr…
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This paper studies a failure mode the authors call “confusion” for multimodal large language models (MLLMs): instead of trying to make the model follow a malicious instruction or predict the wrong …
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DLADiff addresses a gap that most prior anti-customization work leaves open: defenses for diffusion-model fine-tuning existed, but zero-shot identity customization (for example, FaceID-style method…
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This paper studies how Active Queue Management (AQM) algorithms influence modern speed test measurements, specifically metrics related to latency under load and throughput variability
