4 papers
RLDISCOVER: LLM-driven co-evolution of reinforcement learning algorithms
Haoran Li, Zengle Ge, Xiaomin Yuan +14
LLM-guided program evolution has enabled discoveries in mathematics and computational optimization, raising the prospect of reinforcement learning (RL) algorithms that self-evolve…
AGAR: a reinforcement learning substrate for LLM program evolution
Haoran Li, Zengle Ge, Xiaomin Yuan +11
Given a task and an evaluator, a language model can rewrite a candidate program while a search loop decides which rewrites survive, offering a practical route to algorithm discover…
A Compact Selective State-Space Model for Cross-Sectional Stock Return Ranking from Raw Intraday Bars
Mingju Chen, Enze Zhang, Annan Li +5
We present STRATA (Staggered-Timescale Residual Architecture), a 244,633-parameter sequence model that maps five trading days of raw five-minute bar and order-book data directly to…
Centering Drives Normalization Gains: Price-Offset Nuisances in Cross-Sectional Return Prediction
Mingju Chen, Qianhui Liu, Yui Lo +1
Cross-sectional return prediction from raw intraday bars is sensitive to each instrument price level, an additive nuisance under a return-ranking hypothesis. We test whether removi…