1 citations · 1 across the 6 of their papers we have counts for
6 papers
One Analyst Is Not Ground Truth: Grading Agent-Built Financial Models Against Observed Professional Practice
Jiacheng Lu, Sinuo Wang, Yiming Li +15
Language model agents can now construct complete financial models, but it remains unclear whether they have learned the financial judgment that gives those models meaning. Existing…
ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization
Weibo Huang, Cheng Hua
Bayesian Optimization is widely used for expensive black-box optimization, yet its success often depends on choosing a kernel that matches the objective's unknown structure. In thi…
Trade-R1: Bridging Verifiable Rewards to Stochastic Environments via Process-Level Reasoning Verification
Rui Sun, Yifan Sun, Sheng Xu +5
Reinforcement Learning (RL) has enabled Large Language Models (LLMs) to achieve remarkable reasoning in domains like mathematics and coding, where verifiable rewards provide clear…
Alpha-R1: Alpha Screening with LLM Reasoning via Reinforcement Learning
Zuoyou Jiang, Li Zhao, Rui Sun +6
Signal decay and regime shifts pose recurring challenges for data-driven investment strategies in non-stationary markets, where conventional time-series and machine learning approa…
Reinforcement-Learning Portfolio Allocation with Dynamic Embedding of Market Information
Jinghai He, Cheng Hua, Chunyang Zhou +1
We develop a portfolio allocation framework that leverages deep learning techniques to address challenges arising from high-dimensional, non-stationary, and low-signal-to-noise mar…
Collaborative Intelligence in Sequential Experiments: A Human-in-the-Loop Framework for Drug Discovery
Jinghai He, Cheng Hua, Yingfei Wang +1
Drug discovery is a complex process that involves sequentially screening and examining a vast array of molecules to identify those with the target properties. This process, also re…