RecSys
#RecommenderSystems#LanguageModel#Contents-based#Finetuning (SFT)#Adapter/LoRA#Zero/FewShotLearning
Issue Date: 2025-03-30 TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation, Keqin Bao+, RecSys23 Comment下記のようなユーザのプロファイルとターゲットアイテムと、binaryの明示的なrelevance feedbackデータを用いてLoRA、かつFewshot Learningの設定でSFTすることでbinaryのlike/dislikeの予測性能を向上。PromptingだけでなくSFTを実施した初 ... #RecommenderSystems
Issue Date: 2022-04-05 Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison, Sun+, RecSys20 Comment日本語解説：https://qiita.com/smochi/items/c4cecc48e4aba0071ead ... #RecommenderSystems#NeuralNetwork#CollaborativeFiltering
Issue Date: 2022-04-11 Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches, Politecnico di Milano, Maurizio+, RecSys19 CommentRecSys'19のベストペーパー 日本語解説：https://qiita.com/smochi/items/98dbd9429c15898c5dc7Deep learning techniques have become the method of choice forresearchers wo ...
Issue Date: 2025-03-30 TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation, Keqin Bao+, RecSys23 Comment下記のようなユーザのプロファイルとターゲットアイテムと、binaryの明示的なrelevance feedbackデータを用いてLoRA、かつFewshot Learningの設定でSFTすることでbinaryのlike/dislikeの予測性能を向上。PromptingだけでなくSFTを実施した初 ... #RecommenderSystems
Issue Date: 2022-04-05 Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison, Sun+, RecSys20 Comment日本語解説：https://qiita.com/smochi/items/c4cecc48e4aba0071ead ... #RecommenderSystems#NeuralNetwork#CollaborativeFiltering
Issue Date: 2022-04-11 Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches, Politecnico di Milano, Maurizio+, RecSys19 CommentRecSys'19のベストペーパー 日本語解説：https://qiita.com/smochi/items/98dbd9429c15898c5dc7Deep learning techniques have become the method of choice forresearchers wo ...
#RecommenderSystems#NeuralNetwork#NaturalLanguageGeneration#Pocket#NLP#ReviewGeneration
Issue Date: 2019-08-17 Improving Explainable Recommendations with Synthetic Reviews, Ouyang+, RecSys18 #RecommenderSystems#NeuralNetwork#Pocket
Issue Date: 2018-12-27 Deep Neural Networks for YouTube Recommendations, Covington+, RecSys16 #RecommenderSystems#Tutorial#InteractiveRecommenderSystems#Slide
Issue Date: 2017-12-28 Interactive Recommender Systems, Netflix, RecSys15, 2015.09 #Article#RecommenderSystems#Novelty
Issue Date: 2017-12-28 “I like to explore sometimes”: Adapting to Dynamic User Novelty Preferences, Kapoor et al. （with Konstan）, RecSys’15 Comment・典型的なRSは，推薦リストのSimilarityとNoveltyのcriteriaを最適化する．このとき，両者のバランスを取るためになんらかの定数を導入してバランスをとるが，この定数はユーザやタイミングごとに異なると考えられるので（すなわち人やタイミングによってnoveltyのpreference ...
Issue Date: 2019-08-17 Improving Explainable Recommendations with Synthetic Reviews, Ouyang+, RecSys18 #RecommenderSystems#NeuralNetwork#Pocket
Issue Date: 2018-12-27 Deep Neural Networks for YouTube Recommendations, Covington+, RecSys16 #RecommenderSystems#Tutorial#InteractiveRecommenderSystems#Slide
Issue Date: 2017-12-28 Interactive Recommender Systems, Netflix, RecSys15, 2015.09 #Article#RecommenderSystems#Novelty
Issue Date: 2017-12-28 “I like to explore sometimes”: Adapting to Dynamic User Novelty Preferences, Kapoor et al. （with Konstan）, RecSys’15 Comment・典型的なRSは，推薦リストのSimilarityとNoveltyのcriteriaを最適化する．このとき，両者のバランスを取るためになんらかの定数を導入してバランスをとるが，この定数はユーザやタイミングごとに異なると考えられるので（すなわち人やタイミングによってnoveltyのpreference ...