6 citations · 6 across the 2 of their papers we have counts for
3 papers
cs.CE2025
ElliottAgents: A Natural Language-Driven Multi-Agent System for Stock Market Analysis and Prediction
Jarosław A. Chudziak, Michał Wawer
This paper presents ElliottAgents, a multi-agent system leveraging natural language processing (NLP) and large language models (LLMs) to analyze complex stock market data. The syst…
cs.CY2025
Leveraging a Multi-Agent LLM-Based System to Educate Teachers in Hate Incidents Management
Ewelina Gajewska, Michal Wawer, Katarzyna Budzynska +1
Computer-aided teacher training is a state-of-the-art method designed to enhance teachers' professional skills effectively while minimising concerns related to costs, time constrai…
cs.CE2025★ 6 cited
Integrating Traditional Technical Analysis with AI: A Multi-Agent LLM-Based Approach to Stock Market Forecasting
Michał Wawer, Jarosław A. Chudziak
Traditional technical analysis methods face limitations in accurately predicting trends in today's complex financial markets. This paper introduces ElliottAgents, an multi-agent sy…