A Counterfactual Approach for Addressing Individual User Unfairness in Collaborative Recommender System
arXiv 2603.13253•53b90cc38a2de9e06a72226f832d605edd77da3c353a716c86855a13d1a33a8f
GraphRAGLLM-retrievalNepaliOpenExtractQLoRAboolean-matrix-factorizationcollaborative-filteringcounterfactualdatasetsdense-retrievaldistillationevaluation-benchmarksfairnesshallucination-mitigationhypergraphknowledge-graphlate-interactionlow-resource-NLPmultimodal-retrievalpersonalized-learningpreference-alignmentquery-expansionquery-rewritingrecommender-systemssystematic-review-automation
Paper metadata
- arXiv ID
- 2603.13253
- Version
- Not specified by this published record
- Category
- Computer Science — Information Retrieval (cs.IR)
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Evidence and limitations
- Source ID
- arxiv_cs_ir
- Record identifier
- 53b90cc38a2de9e06a72226f832d605edd77da3c353a716c86855a13d1a33a8f
- Enrichment time
- 2026-03-17T08:52:14Z
- AI-assisted enrichment
- Yes
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