Nov 18, 2025 · Artificial Intelligence

How ReAct and Reflexion Boost Large Language Models for Complex, Real‑World Tasks

The article explains the limitations of large language models on multi‑step reasoning, real‑time information retrieval, and planning, then introduces the ReAct (Reasoning + Acting) framework and its Reflexion extension, detailing their mechanisms, examples, performance gains, practical applications, and future research directions.

LLM reasoningLarge Language ModelsPrompt Engineering

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How ReAct and Reflexion Boost Large Language Models for Complex, Real‑World Tasks

Bighead's Algorithm Notes

Oct 9, 2025 · Artificial Intelligence

Paper Review: TradingGroup – A Multi‑Agent Quantitative Trading System with Self‑Reflection and Data Synthesis

The paper introduces TradingGroup, a five‑agent LLM‑based quantitative trading framework that incorporates a self‑reflection mechanism, dynamic risk management, and an automated data‑synthesis pipeline, and demonstrates superior cumulative returns, Sharpe ratios, and lower drawdowns than rule‑based, ML, RL, and existing LLM strategies on five real‑world stock datasets.

Financial AILLMQuantitative Trading

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Paper Review: TradingGroup – A Multi‑Agent Quantitative Trading System with Self‑Reflection and Data Synthesis