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This paper investigates how existing Requirements Engineering (RE) practices support explainability requirements in AI-based systems, focusing on an.
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This paper addresses the interpretability gap in audio deepfake detection systems that use self-supervised learning (SSL) models as feature extractors.
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The paper addresses challenges in collaborative creative writing, particularly the fragmentation of ideas, coordination inefficiency, and individual.
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The paper addresses the challenge of long-form article generation, a complex task for large language models (LLMs) due to the need to handle long context.
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HASTE addresses a critical challenge in post-disaster rapid response: producing accurate building-level damage assessments within hours of a disaster.
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This paper investigates the security vulnerability of Quantum Neural Networks (QNNs) to backdoor attacks, focusing on a novel threat model called.
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JobHop v2 addresses a critical gap in publicly available career trajectory datasets by providing a large-scale, richly annotated collection of 355,315.
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This paper introduces Mako, the first instance of a novel agent architecture called the Self-Evolving Agentic Operating System (SE-AOS), designed to.
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This paper provides the first comprehensive and systematic survey of metacognition in large language models (LLMs), a critical yet underexplored.
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This paper tackles the challenge of model order reduction (MOR) for sliding beams as found in telescopic structures, where effective beam length and.
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Omni-Decision addresses the challenge of omni-modal evidence-seeking question answering (QA), where relevant evidence is sparsely distributed across.
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This paper addresses the critical and practical challenge of determining the optimal operating temperature for silicon spin qubits in large-scale.
