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The Fifth Elephant 2025 Winter Edition Call for Proposals

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Balamurugan P

@balamuruganperiyasamy

[Talk] Hybrid LSTM and LLM Framework for Anomaly Detection in Real-Time Market Data

Submitted Nov 15, 2025

Type of submission: 15 mins talk

Brief
Markets move fast, which makes anomaly detection difficult. Models based on tree methods become stale and fail to track time-based patterns or understand complex context. This talk presents a hybrid system that combines LSTM networks with large language models to detect anomalies in real time market feeds. LSTM layers capture time-based patterns at a granular level. LLM layers add semantic insight from news, sentiment, and macro indicators. The session includes live examples from crypto markets and shows why this approach delivers stronger performance.

Takeaways

  • How to evaluate anomalies in data
  • How LSTM and LLM models work together for real time anomaly detection

Audience

  • For anyone working with tabular data

Bio
I work at a trading firm building real-time pipelines to handle market data. A key part of my day is keeping the data clean and reducing false alarms.

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