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LineageEvo enhances LLM-based financial factor mining using evolutionary lineage control

By PulseAugur Editorial · [1 sources] ·

Researchers have developed LineageEvo, a novel method for controlling evolutionary search in large language models (LLMs) for financial factor mining. This approach leverages lineage, which tracks the evolutionary descent of factor variants, to improve search direction and diversity. LineageEvo incorporates lineage-conditioned LLM variation and lineage-stratified search allocation to guide LLM generation and balance factor quality against lineage concentration. Evaluations on CSI 500 and S&P 500 data demonstrated that LineageEvo achieves superior predictive performance and a broader factor pool compared to existing methods. AI

IMPACT This research could lead to more efficient and diverse discovery of predictive financial factors using LLMs.

RANK_REASON The cluster contains a research paper detailing a new method for LLM-based evolutionary factor mining. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LineageEvo enhances LLM-based financial factor mining using evolutionary lineage control

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The cluster contains a research paper detailing a new method for LLM-based evolutionary factor mining. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Xintong Liu, Chenkai Zhang, Yanzhao Ma, Peng Yang ·

    Lineage-Aware Search Control for LLM-Based Evolutionary Factor Mining

    arXiv:2610.29663v1 Announce Type: cross Abstract: Formulaic alpha factor mining searches for symbolic expressions that transform market data into predictive signals. Recent LLM-based evolutionary factor mining methods use large language models as semantic variation operators. Und…

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