26 citations · 46 across the 7 of their papers we have counts for
9 papers · 1 filter
Large Language Models for User Interest Journeys
Konstantina Christakopoulou, Alberto Lalama, Cj Adams +10
Large language models (LLMs) have shown impressive capabilities in natural language understanding and generation. Their potential for deeper user understanding and improved persona…
KNNs of Semantic Encodings for Rating Prediction
Léo Laugier, Raghuram Vadapalli, Thomas Bonald +1
This paper explores a novel application of textual semantic similarity to user-preference representation for rating prediction. The approach represents a user's preferences as a gr…
Augmenting the User-Item Graph with Textual Similarity Models
Federico López, Martin Scholz, Jessica Yung +3
This paper introduces a simple and effective form of data augmentation for recommender systems. A paraphrase similarity model is applied to widely available textual data, such as r…
Civil Rephrases Of Toxic Texts With Self-Supervised Transformers
Leo Laugier, John Pavlopoulos, Jeffrey Sorensen +1
Platforms that support online commentary, from social networks to news sites, are increasingly leveraging machine learning to assist their moderation efforts. But this process does…
Six Attributes of Unhealthy Conversation
Ilan Price, Jordan Gifford-Moore, Jory Fleming +6
We present a new dataset of approximately 44000 comments labeled by crowdworkers. Each comment is labelled as either 'healthy' or 'unhealthy', in addition to binary labels for the…
Toxicity Detection: Does Context Really Matter?
John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon +2
Moderation is crucial to promoting healthy on-line discussions. Although several `toxicity' detection datasets and models have been published, most of them ignore the context of th…