Yun Xiong

Bridging pre-trained models and downstream tasks for source code understanding

2022 · Proceedings of the 44th International Conference on Software Engineering

With the great success of pre-trained models, the pretrain-then-finetune paradigm has been widely adopted on downstream tasks for source code understanding. However, compared to costly training a large-scale model from scratch, how to effectively adapt …

LAMEE: A Light All-MLP Framework for TimeSeries Prediction Empowering Recommendations

2023 · Research Square

Abstract Exogenous variables, unrelated to the recommendation system itself, can significantly enhance its performance. Therefore, integrating these time-evolving exogenous variables into a time series and conducting time series predictions can maximize the potential of recommendation …

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

2021

In order to model the evolution of user preference, we should learn user/item embeddings based on time-ordered item purchasing sequences, which is defined as Sequential Recommendation~(SR) problem. Existing methods leverage sequential patterns to model item …

Retrieval-Augmented Generation for Large Language Models: A Survey

2023 · arXiv (Cornell University)

Large Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes. Retrieval-Augmented Generation (RAG) has emerged as a promising solution by incorporating knowledge from external databases. This …