RWoDSN extracts feature points from point clouds via a novel DSN descriptor and random walk graph analysis, reporting 22% higher recall than prior state-of-the-art with 0.784 precision.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Peer review reports in AI conferences have grown longer and more standardized after LLMs, with increased emphasis on surface-level clarity and summaries at the expense of deeper critiques on originality and replicability.
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Random Walk on Point Clouds for Feature Detection
RWoDSN extracts feature points from point clouds via a novel DSN descriptor and random walk graph analysis, reporting 22% higher recall than prior state-of-the-art with 0.784 precision.
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Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI
Peer review reports in AI conferences have grown longer and more standardized after LLMs, with increased emphasis on surface-level clarity and summaries at the expense of deeper critiques on originality and replicability.