10 citations · 46 across the 26 of their papers we have counts for
31 papers
More Claims, Less Evidence: Bounded Verification of AI-Generated Digital Knowledge Artifacts
Feliks Bańka, Jarosław A. Chudziak
Digital libraries, repositories, and AI-mediated knowledge services increasingly rely on generative systems to produce summaries, descriptions, and other multi-claim knowledge obje…
Interpreting at Write Time: A Policy Ablation for Multi-Goal Agent Memory
Albert Sadowski, Jarosław A. Chudziak
A long-running assistant cannot keep everything it has seen, so it summarises. Summarising is not neutral: what is kept depends on what the record is for, and the choice is made on…
Towards Mitigating Fabricated Consensus: The Active Provenance Gate for Multi-Agent Debate Synthesis
Jakub Masłowski, Jarosław A. Chudziak
Large language model-based multi-agent debate (MAD) systems are being increasingly used as complex decision pipelines in distributed processes. However, their final synthesis phase…
Benchmarking Argumentative Behaviour of LLMs: A Study of Defences Against Character Attacks
Ewelina Gajewska, Katarzyna Budzynska, Jaroslaw Chudziak
Large Language Models (LLMs) are increasingly deployed as argumentative agents in persuasive dialogues, necessitating rigorous evaluation of their debating competence relative to h…
Loss Choice or Model Choice? The Role of Forecast Level in Cryptocurrency Volatility Forecasting
Andrzej Tokajuk, Jarosław A. Chudziak
Volatility forecasts play a central role in financial risk management because their overall level and day-to-day movements affect downstream decisions. Most studies compare forecas…
Solving versus Verifying: Catching Contradictions in Tax Reasoning Systems
Albert Sadowski, Jarosław A. Chudziak
Large language models now compute correct tax liabilities on over 90% of well-formed cases in statutory benchmarks, which makes them candidates for the tax-advisory and compliance…
From Contexts to Values: Context-Dependent Defeat in Abstract Argumentation
Albert Sadowski, Jarosław A. Chudziak
In value-based argumentation, an audience's ordering of values decides which attacks succeed as defeats. In many settings the deciding factor is not the audience but the circumstan…
On Measuring Semantic Preservation in Legal Ontology Learning
Albert Sadowski, Jarosław A. Chudziak
Ontology learning transforms unstructured text into structured representations for automated reasoning. Yet structuring information risks losing it, and current evaluation methodol…
Compression-Based Behavioral Similarity for Open-World Sybil Discovery on Ethereum
Michał Bartnicki, Jarosław A. Chudziak
Sybil attackers are Blockchain actors that adopt the characteristics of regular users to exploit airdrops or influence governance. Current methods of Sybil actor detection include…
Modeling Decisions in Blockchain Analytics: A Leakage-Aware Evaluation of Tree-Based vs. Sequential Models
Michał Bartnicki, Jarosław A. Chudziak
Sybil bots are Ethereum actors that imitate legitimate users to extract airdrop rewards or influence governance. Recent Sybil detection methods increasingly use deep learning and t…
How Ethos and Pathos Appeals Resonate in Reader Interpretations of Social Media Messages
Ewelina Gajewska, Katarzyna Budzynska, Jaroslaw Chudziak +1
Rhetorical strategies and their influence on audiences are often studied through social media posts and comments. However, this focus overlooks the universal audience, which is the…
From Argument Components to Graphs: A Multi-Agent Debate with Confidence Gating for Argument Relations
Jakub Bąba, Jarosław A. Chudziak
Large Language Models (LLMs) are increasingly assessed and utilized in the field of Argument Mining (AM), thanks to their strong general reasoning capabilities. However, standard t…
Decoupling Thought from Speech: Knowledge-Grounded Counterfactual Reasoning for Resilient Multi-Agent Argumentation
Jakub Masłowski, Jarosław A. Chudziak
Multi-agent debate frameworks have been shown to improve large language model performance in convergent tasks, but they are currently optimized in a way that heavily favors final o…
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…
Improving Implicit Hate Speech Detection via a Community-Driven Multi-Agent Framework
Ewelina Gajewska, Katarzyna Budzynska, Jarosław A Chudziak
This work proposes a contextualised detection framework for implicitly hateful speech, implemented as a multi-agent system comprising a central Moderator Agent and dynamically cons…
Structured Decomposition for LLM Reasoning: Cross-Domain Validation and Semantic Web Integration
Albert Sadowski, Jarosław A. Chudziak
Rule-based reasoning over natural language input arises in domains where decisions must be auditable and justifiable: clinical protocols specify eligibility criteria in prose, evid…
Partial multivariate transformer as a tool for cryptocurrencies time series prediction
Andrzej Tokajuk, Jarosław A. Chudziak
Forecasting cryptocurrency prices is hindered by extreme volatility and a methodological dilemma between information-scarce univariate models and noise-prone full-multivariate mode…
Collaborative LLM Agents for C4 Software Architecture Design Automation
Kamil Szczepanik, Jarosław A. Chudziak
Software architecture design is a fundamental part of creating every software system. Despite its importance, producing a C4 software architecture model, the preferred notation for…
Algorithmic Fairness in NLP: Persona-Infused LLMs for Human-Centric Hate Speech Detection
Ewelina Gajewska, Arda Derbent, Jaroslaw A Chudziak +1
In this paper, we investigate how personalising Large Language Models (Persona-LLMs) with annotator personas affects their sensitivity to hate speech, particularly regarding biases…
On Evaluating Loss Functions for Stock Ranking: An Empirical Analysis With Transformer Model
Jan Kwiatkowski, Jarosław A. Chudziak
Quantitative trading strategies rely on accurately ranking stocks to identify profitable investments. Effective portfolio management requires models that can reliably order future…
DeltaHedge: A Multi-Agent Framework for Portfolio Options Optimization
Feliks Bańka, Jarosław A. Chudziak
In volatile financial markets, balancing risk and return remains a significant challenge. Traditional approaches often focus solely on equity allocation, overlooking the strategic…
On Verifiable Legal Reasoning: A Multi-Agent Framework with Formalized Knowledge Representations
Albert Sadowski, Jarosław A. Chudziak
Legal reasoning requires both precise interpretation of statutory language and consistent application of complex rules, presenting significant challenges for AI systems. This paper…
Cognitive Agents Powered by Large Language Models for Agile Software Project Management
Konrad Cinkusz, Jarosław A. Chudziak, Ewa Niewiadomska-Szynkiewicz
This paper investigates the integration of cognitive agents powered by Large Language Models (LLMs) within the Scaled Agile Framework (SAFe) to reinforce software project managemen…
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…