6 citations · 16 across the 8 of their papers we have counts for
8 papers
Unleashing Expert Opinion from Social Media for Stock Prediction
Wanyun Zhou, Saizhuo Wang, Xiang Li +3
While stock prediction task traditionally relies on volume-price and fundamental data to predict the return ratio or price movement trend, sentiment factors derived from social med…
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making
Jian Guo, Saizhuo Wang, Yiyan Qi
Multi-stage decision-making is crucial in various real-world artificial intelligence applications, including recommendation systems, autonomous driving, and quantitative investment…
Golden Touchstone: A Comprehensive Bilingual Benchmark for Evaluating Financial Large Language Models
Xiaojun Wu, Junxi Liu, Huanyi Su +10
As large language models (LLMs) increasingly permeate the financial sector, there is a pressing need for a standardized method to comprehensively assess their performance. Existing…
DSPO: An End-to-End Framework for Direct Sorted Portfolio Construction
Jianyuan Zhong, Zhijian Xu, Saizhuo Wang +3
In quantitative investment, constructing characteristic-sorted portfolios is a crucial strategy for asset allocation. Traditional methods transform raw stock data of varying freque…
Alpha-GPT 2.0: Human-in-the-Loop AI for Quantitative Investment
Hang Yuan, Saizhuo Wang, Jian Guo
Recently, we introduced a new paradigm for alpha mining in the realm of quantitative investment, developing a new interactive alpha mining system framework, Alpha-GPT. This system…
QuantAgent: Seeking Holy Grail in Trading by Self-Improving Large Language Model
Saizhuo Wang, Hang Yuan, Lionel M. Ni +1
Autonomous agents based on Large Language Models (LLMs) that devise plans and tackle real-world challenges have gained prominence.However, tailoring these agents for specialized do…
A Principled Framework for Knowledge-enhanced Large Language Model
Saizhuo Wang, Zhihan Liu, Zhaoran Wang +1
Large Language Models (LLMs) are versatile, yet they often falter in tasks requiring deep and reliable reasoning due to issues like hallucinations, limiting their applicability in…
On the Evolution of Knowledge Graphs: A Survey and Perspective
Xuhui Jiang, Chengjin Xu, Yinghan Shen +6
Knowledge graphs (KGs) are structured representations of diversified knowledge. They are widely used in various intelligent applications. In this article, we provide a comprehensiv…