Accepted Papers

Implicit feedback -- the main data source for training Recommender Systems (RSs) -- is inherently noisy and has been shown to negatively affect recommendation effectiveness. Denoising has been proposed as a method for removing noisy implicit feedback and improving recommendations. Prior work has foc...

Transformer-based cross-encoders, such as MonoT5, achieve state-of-the-art performance in several retrieval tasks. In particular, MonoT5 is based on a sequence-to-sequence architecture and trained on MS MARCO for passage re-ranking, where it predicts the relevance of a passage given an input query. ...