133 citations · 152 across the 11 of their papers we have counts for
11 papers
Governing Well in the Algorithmic Age: The Foundations of Digital Statecraft
Zeynep Engin, Tim Gordon, Viviana Bastidas +14
The digital substrate - data, algorithms, infrastructure, platforms, applications - is being governed without adequate conceptual foundations. The ability and legitimacy required t…
The Role of Dataset Linguistic Structure in the Cultural Awareness of Large Language Models
Reem I. Masoud, Chen Feng, Shunta Asano +3
The global deployment of large language models (LLMs) has raised concerns about cultural misalignment, yet the linguistic properties of fine-tuning datasets used for cultural adapt…
An Impulse Control Approach to Market Making in a Hawkes LOB Market
Konark Jain, Nick Firoozye, Jonathan Kochems +1
We study the optimal Market Making problem in a Limit Order Book (LOB) market simulated using a high-fidelity, mutually exciting Hawkes process. Departing from traditional Brownian…
Cultural Alignment in Large Language Models Using Soft Prompt Tuning
Reem I. Masoud, Martin Ferianc, Philip Treleaven +1
Large Language Model (LLM) alignment is commonly achieved through supervised fine-tuning or reinforcement learning, both of which require labeled or preference data and update mode…
The Algorithmic State Architecture (ASA): An Integrated Framework for AI-Enabled Government
Zeynep Engin, Jon Crowcroft, David Hand +1
As artificial intelligence transforms public sector operations, governments struggle to integrate technological innovations into coherent systems for effective service delivery. Th…
The Effect of Model Size on LLM Post-hoc Explainability via LIME
Henning Heyen, Amy Widdicombe, Noah Y. Siegel +2
Large language models (LLMs) are becoming bigger to boost performance. However, little is known about how explainability is affected by this trend. This work explores LIME explanat…
BERT vs GPT for financial engineering
Edward Sharkey, Philip Treleaven
The paper benchmarks several Transformer models [4], to show how these models can judge sentiment from a news event. This signal can then be used for downstream modelling and signa…
Limit Order Book Simulations: A Review
Konark Jain, Nick Firoozye, Jonathan Kochems +1
Limit Order Books (LOBs) serve as a mechanism for buyers and sellers to interact with each other in the financial markets. Modelling and simulating LOBs is quite often necessary fo…
Limit Order Book Dynamics and Order Size Modelling Using Compound Hawkes Process
Konark Jain, Nick Firoozye, Jonathan Kochems +1
Hawkes Process has been used to model Limit Order Book (LOB) dynamics in several ways in the literature however the focus has been limited to capturing the inter-event times while…
Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions
Reem I. Masoud, Ziquan Liu, Martin Ferianc +2
The deployment of large language models (LLMs) raises concerns regarding their cultural misalignment and potential ramifications on individuals and societies with diverse cultural…
Twitter Sentiment Analysis: Lexicon Method, Machine Learning Method and Their Combination
Olga Kolchyna, Tharsis T. P. Souza, Philip Treleaven +1
This paper covers the two approaches for sentiment analysis: i) lexicon based method; ii) machine learning method. We describe several techniques to implement these approaches and…