Changxin Tian

Can Small Language Models be Good Reasoners for Sequential Recommendation?

2024 · arXiv (Cornell University)

Large language models (LLMs) open up new horizons for sequential recommendations, owing to their remarkable language comprehension and generation capabilities. However, there are still numerous challenges that should be addressed to successfully implement sequential recommendations …

RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms

2021

In recent years, there are a large number of recommendation algorithms proposed in the literature, from traditional collaborative filtering to deep learning algorithms. However, the concerns about how to standardize open source implementation of recommendation …

Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning

2022 · Proceedings of the ACM Web Conference 2022

Recently, graph collaborative filtering methods have been proposed as an effective recommendation approach, which can capture users’ preference over items by modeling the user-item interaction graphs. Despite the effectiveness, these methods suffer from data sparsity …