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Min Xian

Verified
  • State College Bureau Local Accountability Reporter, Spotlight PA
As seen in: Spotlight PA, MSN, Wiley Online Library, Yahoo Canada, Yahoo News, Aol, MDPI, Philadelphia Business Journal, Yahoo Sports Canada, The Philadelphia Inquirer, Yahoo and
local accountability reporting @SpotlightPA. i read the fine prints, and it takes forever. tell me about cui bono: mxian@spotlightpa.org
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Articles

Computer Science > Computer Vision and Pattern Recognition

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By Matthew Anderson, Min Xian Verified, Elijah Danquah
| arXiv
Interactive image segmentation is critical for efficient image annotation; however, existing methods often require many corrective clicks or rely on passive refinement schemes that converge slowly. We propose Uncertainty-Guided Cascade Forward Refinement (U-CFR), a novel inference-time framework that enables models to autonomously self-correct after each user interaction.
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Failure Event Mining With Fine‐Tuned Large Language Model: Case Study of Analyzing United States Nuclear Power Plant Failure Event Reports

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By Sai Zhang, Min Xian Verified, Shahidur Rahoman Sohag
| Wiley Online Library Verified
1 Introduction The reliability parameters of nuclear power plant components can be estimated with statistical approaches using observed failure counts and the number of demands or operating hours. However, since the nuclear power industry is highly reliable, there is a challenge in gathering sufficient failure data to perform statistical reliability parameter estimations. Industry-wide operating experience is a critical source of raw data for component reliability estimations (Eide et al.
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Police misreporting 100s of rapes ‘didn’t make any difference’ to how cases were handled, oversight board says

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By Min Xian Verified
| Meadville Tribune Verified
This story was produced by the {/em}State College regional bureau of Spotlight PA, an independent, nonpartisan newsroom dedicated to investigative and public-service journalism for Pennsylvania.
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