6 citations · 6 across the 6 of their papers we have counts for
7 papers
Consensus is Strategically Insufficient: Reasoning-Trace Disagreement as a Knowledge-Representation Signal
Michał Wawer, Jarosław A. Chudziak
Multi-agent systems are commonly designed to reduce disagreement through voting, consensus protocols, debate, or fault-tolerant aggregation. We argue that this objective is insuffi…
Who Decides What Is Harmful? Content Moderation Policy Through A Multi-Agent Personalised Inference Framework
Ewelina Gajewska, Michal Wawer, Katarzyna Budzynska +1
The increasing scale and complexity of online platforms raises critical policy questions around harmful content, digital well-being, and user autonomy. Traditional content moderati…
When AI Agents Disagree Like Humans: Reasoning Trace Analysis for Human-AI Collaborative Moderation
Michał Wawer, Jarosław A. Chudziak
When LLM-based multi-agent systems disagree, current practice treats this as noise to be resolved through consensus. We propose it can be signal. We focus on hate speech moderation…
On Theoretically-Driven LLM Agents for Multi-Dimensional Discourse Analysis
Maciej Uberna, Michał Wawer, Jarosław A. Chudziak +1
Identifying the strategic uses of reformulation in discourse remains a key challenge for computational argumentation. While LLMs can detect surface-level similarity, they often fai…
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…
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…
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…