8 papers
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…
Rethinking Explainable Disease Prediction: Synergizing Accuracy and Reliability via Reflective Cognitive Architecture
Zijian Shao, Haiyang Shen, Mugeng Liu +4
In clinical decision-making, predictive models face a persistent trade-off: accurate models are often opaque "black boxes," while interpretable methods frequently lack predictive p…
DRAGON: Domain-specific Robust Automatic Data Generation for RAG Optimization
Haiyang Shen, Hang Yan, Zhongshi Xing +6
Retrieval-augmented generation (RAG) can substantially enhance the performance of LLMs on knowledge-intensive tasks. Various RAG paradigms - including vanilla, planning-based, and…
Accelerating Mobile Language Model via Speculative Decoding and NPU-Coordinated Execution
Zhiyang Chen, Daliang Xu, Haiyang Shen +5
Performing Retrieval-Augmented Generation (RAG) directly on mobile devices is promising for data privacy and responsiveness but is hindered by the architectural constraints of mobi…
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…