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HumanForge introduces a comprehensive human-centric deepfake video benchmark designed to address critical limitations in existing datasets, such as narrow.
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This paper addresses the challenge of evaluating whether AI systems can accurately reason about and generate scientific ideas grounded in their lineage, i.e.
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This paper tackles the challenge of enabling adaptive, iterative reasoning within continuous robotic control policies by introducing the Latent Memory.
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This paper addresses the challenge of recovering high-quality video from sparse, asynchronous event camera streams, a problem complicated by the ill-posed.
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This paper addresses the limitations of traditional Milky Way analogue (MWA) searches that focus primarily on present-day galaxy properties such as.
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This paper investigates security vulnerabilities arising from improper integration of OAuth-based Authentication (OBA) flows in mini-programs embedded.
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This paper addresses the privacy risks inherent in user and programmatic interactions with Large Language Models (LLMs), which often involve sending.
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This paper addresses a fundamental challenge in automated diabetic retinopathy (DR) lesion segmentation: the extreme variation in lesion sizes from tiny.
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MulTTiPop addresses a critical gap in automatic music transcription (AMT) research by providing a curated dataset of multitrack MIDI transcriptions.
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This paper addresses a fundamental issue in Small Area Estimation (SAE) using the Fay-Herriot (FH) model: the classical assumption that sampling variances.
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This paper addresses the emerging challenge of protecting high-value online textual content against unauthorized scraping and reuse by advanced LLM-based.
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PolyUQuest addresses a core limitation in existing retrieval-augmented generation (RAG) systems that treat web pages as flat text, losing important.
