The paper presents a curriculum-grounded LLM-as-Judge pipeline for question-level marking that assembles authorized syllabus artifacts to generate rubrics and evaluate student responses.
Graph-based robust cloud removal via optical-sar image fusion,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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IB-HFN introduces a dual-stream backbone with spatial information bottleneck fusion, local-global gating, and joint optimization to achieve superior structural and spectral fidelity in SAR-assisted optical cloud removal on the SEN12MS-CR dataset.
citing papers explorer
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LLM-as-Judge in Education: A Curriculum-Grounded Marking Pipeline
The paper presents a curriculum-grounded LLM-as-Judge pipeline for question-level marking that assembles authorized syllabus artifacts to generate rubrics and evaluate student responses.
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IB-HFN: Information Bottleneck-Driven SAR-Optical Fusion Network for High-Fidelity Cloud Removal
IB-HFN introduces a dual-stream backbone with spatial information bottleneck fusion, local-global gating, and joint optimization to achieve superior structural and spectral fidelity in SAR-assisted optical cloud removal on the SEN12MS-CR dataset.