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Curtin University, Shanghai Jiao Tong University, Shanghai, China, Eastern Institute of Technology, Ningbo, China
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By dynamically weighting historical interactions, TIPS lets sequential recommenders see past the biases of what users *actually* clicked, revealing what they *would* have clicked.
