activity
20242026
collaborators

10 papers

q-fin.GN2026

Methodology for Modelling Token Economies and Performing Event Impact Analysis with DeTEcT

Rem Sadykhov, Geoffrey Goodell, Philip Treleaven

The objective of this paper is to provide a methodology for applying the DeTEcT framework to modelling token economies, to formalise the configuration of the simulation environment…

q-fin.GN2026

Impacts of Economic Policies on Wealth Distribution in Token Economies

Rem Sadykhov, Geoff Goodell, Philip Treleaven

In this paper, we analyse the impacts of exogenous and endogenous factors on wealth distribution in the Bitcoin token economy, where wealth distribution refers to the distribution…

cs.CL2025

Knowledge Collapse in LLMs: When Fluency Survives but Facts Fail under Recursive Synthetic Training

Figarri Keisha, Zekun Wu, Ze Wang +2

Large language models increasingly rely on synthetic data due to human-written content scarcity, yet recursive training on model-generated outputs leads to model collapse, a degene…

cs.CL2025

Personality as a Probe for LLM Evaluation: Method Trade-offs and Downstream Effects

Gunmay Handa, Zekun Wu, Adriano Koshiyama +1

Personality manipulation in large language models (LLMs) is increasingly applied in customer service and agentic scenarios, yet its mechanisms and trade-offs remain unclear. We pre…

q-fin.GN2025

Economic Policy Taxonomy

Rem Sadykhov, Geoff Goodell, Philip Treleaven

This paper proposes a framework for categorizing economic policies in a form of a tree taxonomy. The purpose of this approach is to construct an exhaustive and standardized list of…

cs.CL2025

From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs

Navya Jain, Zekun Wu, Cristian Munoz +5

The manipulation of the personality traits of large language models (LLMs) has emerged as a key area of research. Methods like prompt-based In-Context Knowledge Editing (IKE) and g…