• GunosyDMについて
• Predicting Audience-Rated News Quality: Using Survey, Text Mining, and Neural Network Methods
• Surrogate for Long-Term User Experience in Recommender Systems
• Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)
• Wu+'22 Is News Recommendation a Sequential Recommendation Task? (SIGIR 2022)
• [Covington+'16] Deep Neural Networks for YouTube Recommendations (RecSys 2016)
• Identifying New Podcasts with High General Appeal Using a Pure Exploration Infinitely-Armed Bandit Strategy
• Competition-Level Code Generation with AlphaCode
• Raffel+'19 Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
• Diversity Vs Relevance: A Practical Multi-objective Study in Luxury Fashion Recommendations
• Generalizing to the Future Mitigating Entity Bias in Fake News Detection
• Forest-based Deep Recommender
• Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting
• How Do Mothers and Fathers Talk About Parenting to Different Audiences?
• MINDSim: User Simulator for News Recommenders
• Lie to Me: Abusing the Mobile Content Sharing Service for Fun and Profit
• Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework
• Disentangling Long and Short-Term Interests for Recommendation
• Masked Summarization to Generate Factually Inconsistent Summaries for Improved Factual Consistency Checking
• Using Survival Models to Estimate User Engagement in Online Experiments