# Resisting Manipulative Bots in Meme Coin Copy Trading: A Multi-Agent Approach with Chain-of-Thought Reasoning

arXiv: https://arxiv.org/abs/2601.08641 · HTML: https://mlsanity.com/paper/2601.08641/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning.
- Builds on 29 of its 56 references that are in the map.
- First posted on arXiv 13 Jan 2026.

## Placed in

- LLM reasoning / [Reasoning for agents, planning and code](https://mlsanity.com/lr/reasoning-for-agents-planning-and-code/)
- LLM agents and tool use / [Financial trading and forecasting agents](https://mlsanity.com/agents/financial-trading-and-forecasting-agents/)

## Builds on (most cited first, 29 of 29)

- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [A Unified Approach to Interpreting Model Predictions](https://mlsanity.com/paper/1705.07874/) (2017)
- [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation](https://mlsanity.com/paper/2308.08155/) (2023)
- [A Survey on Multimodal Large Language Models](https://mlsanity.com/paper/2306.13549/) (2023)
- [Vision-Language Models for Vision Tasks: A Survey](https://mlsanity.com/paper/2304.00685/) (2023)
- [Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond](https://mlsanity.com/paper/2304.13712/) (2023)
- [Large Language Models in Finance: A Survey](https://mlsanity.com/paper/2311.10723/) (2023)
- [PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance](https://mlsanity.com/paper/2306.05443/) (2023)
- [Chain of Hindsight Aligns Language Models with Feedback](https://mlsanity.com/paper/2302.02676/) (2023)
- [Automate Strategy Finding with LLM in Quant Investment](https://mlsanity.com/paper/2409.06289/) (2024)
- [Calibrating LLM Confidence by Probing Perturbed Representation Stability](https://mlsanity.com/paper/2505.21772/) (2025)
- [SoK: Decentralized Exchanges (DEX) with Automated Market Maker (AMM) Protocols](https://mlsanity.com/paper/2103.12732/) (2021)
- [LLM-Powered Multi-Agent System for Automated Crypto Portfolio Management](https://mlsanity.com/paper/2501.00826/) (2025)
- [FinChain: A Symbolic Benchmark for Verifiable Chain-of-Thought Financial Reasoning](https://mlsanity.com/paper/2506.02515/) (2025)
- [TradExpert: Revolutionizing Trading with Mixture of Expert LLMs](https://mlsanity.com/paper/2411.00782/) (2024)
- [Enhancing Long Chain-of-Thought Reasoning through Multi-Path Plan Aggregation](https://mlsanity.com/paper/2510.11620/) (2025)
- [A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading](https://mlsanity.com/paper/2407.09546/) (2024)
- [Unveiling Wash Trading in Popular NFT Markets](https://mlsanity.com/paper/2403.10361/) (2024)
- [CoinCLIP: A Multimodal Framework for Assessing Viability in Web3 Memecoins](https://mlsanity.com/paper/2412.07591/) (2024)
- [FinCoT: Grounding Chain-of-Thought in Expert Financial Reasoning](https://mlsanity.com/paper/2506.16123/) (2025)
- [Auto.gov: Learning-based Governance for Decentralized Finance (DeFi)](https://mlsanity.com/paper/2302.09551/) (2023)
- [SoK: Design, Vulnerabilities, and Security Measures of Cryptocurrency Wallets](https://mlsanity.com/paper/2307.12874/) (2023)
- [Detecting Various DeFi Price Manipulations with LLM Reasoning](https://mlsanity.com/paper/2502.11521/) (2025)
- [Know Your Intent: An Autonomous Multi-Perspective LLM Agent Framework for DeFi User Transaction Intent Mining](https://mlsanity.com/paper/2511.15456/) (2025)
- [Exploring LLM Cryptocurrency Trading Through Fact-Subjectivity Aware Reasoning](https://mlsanity.com/paper/2410.12464/) (2024)
- [Bridging Culture and Finance: A Multimodal Analysis of Memecoins in the Web3 Ecosystem](https://mlsanity.com/paper/2412.04913/) (2024)
- [AiRacleX: Automated Detection of Price Oracle Manipulations via LLM-Driven Knowledge Mining and Prompt Generation](https://mlsanity.com/paper/2502.06348/) (2025)
- [A Midsummer Meme's Dream: Investigating Market Manipulations in the Meme Coin Ecosystem](https://mlsanity.com/paper/2507.01963/) (2025)
- [Measuring Memecoin Fragility](https://mlsanity.com/paper/2512.00377/) (2025)

## Built on by (most cited first, 1 of 1)

- [DLT-Corpus: A Large-Scale Text Collection for the Distributed Ledger Technology Domain](https://mlsanity.com/paper/2602.22045/) (2026)

## Abstract (arXiv)

Copy trading has become the dominant entry strategy in meme coin markets. However, due to the market's extremely illiquid and volatile nature, the strategy exposes an exploitable attack surface: adversaries deploy manipulative bots to front-run trades, conceal positions, and fabricate sentiment, systematically extracting value from na"ive copiers at scale. Despite its prevalence, bot-driven manipulation remains largely unexplored, and no robust defensive framework exists. We propose a manipulation-resistant copy-trading system based on a multi-agent architecture powered by a multi-modal large language model (LLM) and chain-of-thought (CoT) reasoning. Our approach outperforms zero-shot and most statistic-driven baselines in prediction accuracy as well as all baselines in economic performance, achieving an average copier return of 3% per meme coin investment under realistic market frictions. Overall, our results demonstrate the effectiveness of agent-based defenses and predictability of trader profitability in adversarial meme coin markets, providing a practical foundation for robust copy trading.