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This paper rigorously evaluates the security of user authentication code generated by five prominent AI coding assistants (GitHub Copilot with Claude.
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This paper addresses the growing ineffectiveness of conventional CAPTCHAs against modern AI solvers and behavioral biometric mimicry by introducing a.
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This paper challenges the prevailing framing of agent security as primarily a question of action content—i.e., whether the commands agents perform look.
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This paper presents HERITRACE, an open-source web application designed to support expert-driven curation of RDF data stored in triplestores.
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CausalForge addresses the challenge of automating theoretical research in causal inference, focusing not only on generating candidate results but also on.
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This paper investigates whether current agent benchmarks reliably measure the intended capabilities of AI agents, particularly as capabilities and.
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This paper explores an isoperimetric problem in discrete geometry concerning polyforms — connected subsets of tiles in the three regular plane.
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This paper identifies a fundamental vulnerability in current deepfake detection methods: they rely primarily on digital synthesis artifacts and ignore.
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LinkML-Scala addresses the performance, portability, and consistency limitations of the original Python implementation of LinkML, a unified modeling.
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MineValiCoder addresses critical challenges in automated code generation via test-driven development (TDD) using Large Language Models (LLMs).
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This study investigates how commercial large language models (LLMs) from four major families—Claude, Grok, GPT, and Gemini—evaluate pseudo-scientific.
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This paper addresses the challenge of lightweight, physical-layer authentication (PLA) of backscatter devices (BDs) in ambient IoT (A-IoT) systems using.
