Structured LLM agents correct agricultural yield forecasts from models like XGBoost, cutting MAE by 20-28% and MASE by up to 66% on strawberry and corn datasets.
C hatgpt informed graph neural network for stock movement prediction
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Relational Probing replaces the LM output head with a trainable relation head that induces graphs from hidden states and optimizes them end-to-end for stock trend prediction, showing gains over co-occurrence baselines.
FundaPod presents a multi-persona AI agent architecture with knowledge-graph memory to support human-adjudicated fundamental investment research through independent agent work and verifiable evidence links.
This review synthesizes LLM uses in stock forecasting and catalogs key practical pitfalls from a hedge-fund viewpoint.
A survey synthesizing recent LLM research and assessing its applicability to financial data analysis.
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Bridging Language Models and Financial Analysis
A survey synthesizing recent LLM research and assessing its applicability to financial data analysis.