Controlled experiments across six benchmarks and four models show RAG context enrichment with metadata, structure, or strategies mostly lowers accuracy, with model-context alignment as the determining factor.
InProceedings of the ACM Web Conference 2024 (WWW ’24)
3 Pith papers cite this work. Polarity classification is still indexing.
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Presents MBFC-2025 dataset and multi-view embeddings with fusion methods for media bias and factuality, reporting SOTA results on ACL-2020 and new benchmarks on MBFC-2025.
Representation Curriculum stages feature introduction during training to prioritize content merit signals over exposure-dependent ones, reducing shortcut learning and improving cold-start robustness in ranking.
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Representation Curriculum: Stagewise Training for Robust Ranking and Allocation
Representation Curriculum stages feature introduction during training to prioritize content merit signals over exposure-dependent ones, reducing shortcut learning and improving cold-start robustness in ranking.