65 citations · 307 across the 25 of their papers we have counts for
6 papers · 1 filter
AgenticTagger: Structured Item Representation for Recommendation with LLM Agents
Zhouhang Xie, Bo Peng, Zhankui He +11
High-quality representations are a core requirement for effective recommendation. In this work, we study the problem of LLM-based descriptor generation, i.e., keyphrase-like natura…
ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
Yupeng Hou, Jianmo Ni, Zhankui He +5
Generative recommendation (GR) is an emerging paradigm where user actions are tokenized into discrete token patterns and autoregressively generated as predictions. However, existin…
Infinite Recommendation Networks: A Data-Centric Approach
Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-Jean Wu +1
We leverage the Neural Tangent Kernel and its equivalence to training infinitely-wide neural networks to devise -AE: an autoencoder with infinitely-wide bottleneck layers.…
SVP-CF: Selection via Proxy for Collaborative Filtering Data
Noveen Sachdeva, Carole-Jean Wu, Julian McAuley
We study the practical consequences of dataset sampling strategies on the performance of recommendation algorithms. Recommender systems are generally trained and evaluated on sampl…
How Useful are Reviews for Recommendation? A Critical Review and Potential Improvements
Noveen Sachdeva, Julian McAuley
We investigate a growing body of work that seeks to improve recommender systems through the use of review text. Generally, these papers argue that since reviews 'explain' users' op…
Attentive Neural Architecture Incorporating Song Features For Music Recommendation
Noveen Sachdeva, Kartik Gupta, Vikram Pudi
Recommender Systems are an integral part of music sharing platforms. Often the aim of these systems is to increase the time, the user spends on the platform and hence having a high…