AlphaCrafter deploys Miner, Screener, and Trader agents in a continuously adaptive pipeline that outperforms baselines on CSI 300 and S&P 500 with lower variance in risk-adjusted returns.
Designing heterogeneous llm agents for financial sentiment analysis
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Incorporating BERT-derived Discord sentiment into an LSTM improves MANA token return forecasts over a historical-price baseline.
citing papers explorer
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AlphaCrafter: A Full-Stack Multi-Agent Framework for Cross-Sectional Quantitative Trading
AlphaCrafter deploys Miner, Screener, and Trader agents in a continuously adaptive pipeline that outperforms baselines on CSI 300 and S&P 500 with lower variance in risk-adjusted returns.
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Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token
Incorporating BERT-derived Discord sentiment into an LSTM improves MANA token return forecasts over a historical-price baseline.