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Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis.

, , , , , , and . KDD, page 305-315. ACM, (2022)

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Interpretable Fashion Matching with Rich Attributes., , , , , , and . SIGIR, page 775-784. ACM, (2019)Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure., , , and . CoRR, (2019)Think Twice Before Assure: Confidence Estimation for Large Language Models through Reflection on Multiple Answers., , , , , and . CoRR, (2024)Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure., , , and . IEEE Trans. Knowl. Data Eng., 33 (6): 2493-2504 (2021)Cross-GCN: Enhancing Graph Convolutional Network with $k$k-Order Feature Interactions., , , and . IEEE Trans. Knowl. Data Eng., 35 (1): 225-236 (2023)SLED: Structure Learning based Denoising for Recommendation., , , , , , , , , and 1 other author(s). ACM Trans. Inf. Syst., 42 (2): 43:1-43:31 (March 2024)Causal Disentangled Recommendation Against User Preference Shifts., , , , , and . CoRR, (2023)Data-efficient Fine-tuning for LLM-based Recommendation., , , , , , and . CoRR, (2024)Mitigating Spurious Correlations for Self-supervised Recommendation., , , , and . CoRR, (2022)Label Denoising through Cross-Model Agreement., , , , , and . CoRR, (2023)