4 papers
Policy-Invariant Reward Shaping from LLM Feedback: A Framework for Hybrid RL Agents
Christophe D. Hounwanou, John Emeka Eze, Yaé U. Gaba
Combining large language models with reinforcement learning is increasingly explored, yet the theoretical status of LLM-derived reward signals is often left implicit. We formalize…
Hybrid LLM-Augmented Reinforcement Learning Agents for Complex Sequential Decision Tasks
Christophe D. Hounwanou, John Emeka Eze, Yaé Ulrich Gaba
Large Language Models (LLMs) have recently shown strong capabilities in reasoning, planning, and tool-use, enabling new forms of autonomous agents. However, LLM-based agents strugg…
Deep Generative Models for Synthetic Financial Data: Applications to Portfolio and Risk Modeling
Christophe D. Hounwanou, Yae Ulrich Gaba
Synthetic financial data provides a practical solution to the privacy, accessibility, and reproducibility challenges that often constrain empirical research in quantitative finance…
Synthetic Financial Data Generation for Enhanced Financial Modelling
Christophe D. Hounwanou, Yae Ulrich Gaba, Pierre Ntakirutimana
Data scarcity and confidentiality in finance often impede model development and robust testing. This paper presents a unified multi-criteria evaluation framework for synthetic fina…