42 citations · 112 across the 11 of their papers we have counts for
11 papers
MM-Forecast: A Multimodal Approach to Temporal Event Forecasting with Large Language Models
Haoxuan Li, Zhengmao Yang, Yunshan Ma +3
We study an emerging and intriguing problem of multimodal temporal event forecasting with large language models. Compared to using text or graph modalities, the investigation of ut…
LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation
Rebecca Salganik, Xiaohao Liu, Yunshan Ma +2
As online music consumption increasingly shifts towards playlist-based listening, the task of playlist continuation, in which an algorithm suggests songs to extend a playlist in a…
Analyzing Temporal Complex Events with Large Language Models? A Benchmark towards Temporal, Long Context Understanding
Zhihan Zhang, Yixin Cao, Chenchen Ye +3
The digital landscape is rapidly evolving with an ever-increasing volume of online news, emphasizing the need for swift and precise analysis of complex events. We refer to the comp…
CIRP: Cross-Item Relational Pre-training for Multimodal Product Bundling
Yunshan Ma, Yingzhi He, Wenjun Zhong +3
Product bundling has been a prevailing marketing strategy that is beneficial in the online shopping scenario. Effective product bundling methods depend on high-quality item represe…
Contrastive Pre-training for Deep Session Data Understanding
Zixuan Li, Lizi Liao, Yunshan Ma +1
Session data has been widely used for understanding user's behavior in e-commerce. Researchers are trying to leverage session data for different tasks, such as purchase intention p…
Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models
Kelvin J. L. Koa, Yunshan Ma, Ritchie Ng +1
Explaining stock predictions is generally a difficult task for traditional non-generative deep learning models, where explanations are limited to visualizing the attention weights…