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Linxun Chen

2 accepted papers

2024

Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random

NeurIPS 2024poster

In most practical applications such as recommendation systems, display advertising, and so forth, the collected data often contains missing values and those missing values are generally missing-not-at-random, which deteriorates the prediction performance of models. Some existing estimators and regul…

Cited by 3SourcePDFScholar
2024

Fine-Tuning Large Language Model Based Explainable Recommendation with Explainable Quality Reward

AAAI 2024technical

Large language model-based explainable recommendation (LLM-based ER) systems can provide remarkable human-like explanations and have widely received attention from researchers. However, the original LLM-based ER systems face three low-quality problems in their generated explanations, i.e., lack of p…