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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
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This paper tackles a concrete limitation in wireless foundation models: most prior WFMs are modality-specific, even though wireless systems expose multiple views of the same propagation event, incl…
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This paper asks a practical question that most text-only plagiarism detectors dodge: can we detect LLM-assisted academic dishonesty by looking at how the text was produced, not just the final prose…
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This paper addresses the increasing ineffectiveness of conventional human verification methods such as CAPTCHAs against advanced AI bots capable of solving visual puzzles, emulating typing behavior…
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This paper addresses online learning to rank under adversarially corrupted click feedback, modeled as cascading bandits
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This paper studies robust streaming algorithms under a novel adversarial model where the adversary is adaptive but memory constrained—either memoryless (no persistent memory) or low-memory (a small…
