6 papers
AlphaEval: A Comprehensive and Efficient Evaluation Framework for Formula Alpha Mining
Hongjun Ding, Binqi Chen, Jinsheng Huang +6
Formula alpha mining, which generates predictive signals from financial data, is critical for quantitative investment. Although various algorithmic approaches-such as genetic progr…
AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration
Binqi Chen, Hongjun Ding, Ning Shen +4
The automated mining of predictive signals, or alphas, is a central challenge in quantitative finance. While Reinforcement Learning (RL) has emerged as a promising paradigm for gen…
MEME: Modeling the Evolutionary Modes of Financial Markets
Taian Guo, Haiyang Shen, Junyu Luo +7
LLMs have demonstrated significant potential in quantitative finance by processing vast unstructured data to emulate human-like analytical workflows. However, current LLM-based met…
AlphaPROBE: Alpha Mining via Principled Retrieval and On-graph biased evolution
Taian Guo, Haiyang Shen, Junyu Luo +6
Extracting signals through alpha factor mining is a fundamental challenge in quantitative finance. Existing automated methods primarily follow two paradigms: Decoupled Factor Gener…
MASS: Muli-agent simulation scaling for portfolio construction
Taian Guo, Haiyang Shen, JinSheng Huang +9
The application of LLM-based agents in financial investment has shown significant promise, yet existing approaches often require intermediate steps like predicting individual stock…
MMEvalPro: Calibrating Multimodal Benchmarks Towards Trustworthy and Efficient Evaluation
Jinsheng Huang, Liang Chen, Taian Guo +13
Large Multimodal Models (LMMs) exhibit impressive cross-modal understanding and reasoning abilities, often assessed through multiple-choice questions (MCQs) that include an image,…