93 citations · 143 across the 9 of their papers we have counts for
9 papers
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
Shiyu Wang, Haixu Wu, Xiaoming Shi +5
Time series forecasting is widely used in extensive applications, such as traffic planning and weather forecasting. However, real-world time series usually present intricate tempor…
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt
Gangwei Jiang, Caigao Jiang, Siqiao Xue +4
Continual pre-training has been urgent for adapting a pre-trained model to a multitude of domains and tasks in the fast-evolving world. In practice, a continually pre-trained model…
Prompt-augmented Temporal Point Process for Streaming Event Sequence
Siqiao Xue, Yan Wang, Zhixuan Chu +7
Neural Temporal Point Processes (TPPs) are the prevalent paradigm for modeling continuous-time event sequences, such as user activities on the web and financial transactions. In re…
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference
Yan Wang, Zhixuan Chu, Tao Zhou +9
Asynchronous time series, also known as temporal event sequences, are the basis of many applications throughout different industries. Temporal point processes(TPPs) are the standar…
Leveraging Large Language Models for Pre-trained Recommender Systems
Zhixuan Chu, Hongyan Hao, Xin Ouyang +9
Recent advancements in recommendation systems have shifted towards more comprehensive and personalized recommendations by utilizing large language models (LLM). However, effectivel…
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
Yan Wang, Zhixuan Chu, Xin Ouyang +10
Recommendation systems aim to provide users with relevant suggestions, but often lack interpretability and fail to capture higher-level semantic relationships between user behavior…
WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine
Siqiao Xue, Fan Zhou, Yi Xu +10
We present WeaverBird, an intelligent dialogue system designed specifically for the finance domain. Our system harnesses a large language model of GPT architecture that has been tu…
EasyTPP: Towards Open Benchmarking Temporal Point Processes
Siqiao Xue, Xiaoming Shi, Zhixuan Chu +9
Continuous-time event sequences play a vital role in real-world domains such as healthcare, finance, online shopping, social networks, and so on. To model such data, temporal point…
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning
Xiaoming Shi, Siqiao Xue, Kangrui Wang +5
Large language models have shown astonishing performance on a wide range of reasoning tasks. In this paper, we investigate whether they could reason about real-world events and hel…