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This paper addresses the challenge of automatically assessing sympathetic-mediated pain (SMP) from facial videos collected in real clinical settings where.
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This paper tackles foundational challenges in learning-based memory systems for large language model (LLM) agents that evolve themselves through continual.
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This study addresses the challenging problem of automated rip-current detection and localization from UAV-acquired standard RGB imagery, which is critical.
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This paper tackles a fundamental limitation in multimodal Generative Recommendation (GR) systems, which traditionally require paired image-text data for.
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This paper addresses the challenging problem of aerial-ground person re-identification (ReID), where large viewpoint variations between aerial and ground.
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This study investigates the content and emotional tone of user discourse about AI companion bots within Reddit communities dedicated to AI companionship.
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This paper addresses a fundamental challenge in Explainable AI (XAI): objectively evaluating explanation quality by balancing explanation sparsity with.
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This paper addresses the challenge of reliably verifying and self-correcting mathematical problem solutions generated by large language models (LLMs).
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This paper addresses the critical challenge of training small language models (SLMs) for function-calling tasks, where training data scarcity and quality.
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This paper investigates data visualization style guides as socio-technical systems that organizations develop to coordinate visual communication practices.
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DynoDINO addresses key challenges in multi-phase medical image segmentation, specifically for contrast-enhanced CT (CECT) used in liver cancer diagnosis.
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ExtractBench addresses the enterprise challenge of schema-guided extraction, where given a schema and a document, an AI agent extracts structured data.
