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This paper addresses the challenge of efficient parametric transient prediction for controlled dynamical systems, especially under unseen parameter values.
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This paper addresses the challenge of reliably verifying Cross-Site Scripting (XSS) vulnerabilities discovered by white-box AI coding agents that have.
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This paper addresses the critical challenge of spatial correctness and visual legibility in educational video synthesis generated via code-centric.
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This paper tackles the problem of pixel-level image tampering detection in the context of modern vision-language models (VLMs), such as ChatGPT, Gemini.
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SpEmoC addresses major limitations in multimodal emotion recognition datasets by providing a large-scale, balanced, and temporally aligned benchmark.
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This paper addresses the challenge of efficiently processing recursive database queries—such as transitive closure and same-generation relations—in web.
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This paper addresses the fundamental sim-to-real gap challenge in robotic control, where policies trained in simulation perform poorly on real robots due.
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This study rigorously evaluates the effectiveness of large language models (LLMs) for detecting online scams across multiple real-world scenarios without.
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This paper addresses the precise theoretical calculation of transition form factors (TFFs) for the semileptonic decay D_s^+ → K^{*0} ℓ^+ ν_ℓ, focusing on.
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This paper addresses the challenge of modeling the complex interplay between ferroelectric domain structures and optical properties, which is critical for.
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The paper addresses a key challenge in coding agent workflows where automatic repairs fixing failing test cases may not preserve the underlying domain.
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This paper addresses key limitations in Conversational Speech Synthesis (CSS) related to the restricted predefined emotion label space (typically 7 basic.
