234 citations · 504 across the 22 of their papers we have counts for
23 papers
Latent space bias directions in LLMs capture confidence, not fairness
Stephanie Buttigieg, Maeve Madigan, Parameswaran Kamalaruban +1
Activation steering has gained popularity as a lightweight inference-time debiasing technique for large language models. However, prior work reports that steering vectors generalis…
MINT: A Universal Zero-Shot Predictor for Transaction Data
Parameswaran Kamalaruban, Viktor Drobnyi, Maeve Madigan +3
Banks analyse sequential financial transaction data to perform many tasks, including fraud prevention, credit risk assessment and offer personalization. To improve the predictive a…
Log-Likelihood, Simpson's Paradox, and the Detection of Machine-Generated Text
Tom Kempton, Viktor Drobnyi, Maeve Madigan +1
The ability to reliably distinguish human-written text from that generated by large language models is of profound societal importance. The dominant approach to this problem exploi…
DMAP: A Distribution Map for Text
Tom Kempton, Julia Rozanova, Parameswaran Kamalaruban +5
Large Language Models (LLMs) are a powerful tool for statistical text analysis, with derived sequences of next-token probability distributions offering a wealth of information. Ext…
Emergent Bias and Fairness in Multi-Agent Decision Systems
Maeve Madigan, Parameswaran Kamalaruban, Glenn Moynihan +3
Multi-agent systems have demonstrated the ability to improve performance on a variety of predictive tasks by leveraging collaborative decision making. However, the lack of effectiv…
Fairness-Aware Low-Rank Representation Fine-Tuning
Parameswaran Kamalaruban, Mark Anderson, Stuart Burrell +3
Pre-trained foundation models can be efficiently adapted for specific tasks using Low-Rank Adaptation (LoRA), but the fairness properties of these adapted classifiers remain undere…
A critical study of the Monte Carlo replica method
Mark N. Costantini, Maeve Madigan, Luca Mantani +1
We present a detailed mathematical study of the Monte Carlo replica method as applied in the global fitting literature from the high-energy physics theory community. For the first…
Di-Higgs production via Axion-Like Particles
Fabian Esser, Maeve Madigan, Alexandre Salas-Bernardez +2
Due to the pseudo-scalar nature of the axion-like particle (ALP), the CP- conserving production of two Higgs bosons via the ALP necessarily involves an additional Z or boson. W…
SIMUnet: an open-source tool for simultaneous global fits of EFT Wilson coefficients and PDFs
Mark N. Costantini, Elie Hammou, Zahari Kassabov +5
We present the open-source SIMUnet code, designed to fit Standard Model Effective Field Theory (SMEFT) Wilson coefficient alongside Parton Distribution Functions (PDFs) of the prot…
Staying on Top of SMEFT-Likelihood Analyses
Nina Elmer, Maeve Madigan, Tilman Plehn +1
We present a new global SMEFT analysis of LHC data in the top sector. After updating our set of measurements, we show how public ATLAS likelihoods can be incorporated into an exter…
Hide and seek: how PDFs can conceal New Physics
Elie Hammou, Zahari Kassabov, Maeve Madigan +5
The interpretation of LHC data, and the assessment of possible hints of new physics, require the precise knowledge of the proton structure in terms of parton distribution functions…
The top quark legacy of the LHC Run II for PDF and SMEFT analyses
Zahari Kassabov, Maeve Madigan, Luca Mantani +4
We assess the impact of top quark production at the LHC on global analyses of parton distributions (PDFs) and of Wilson coefficients in the SMEFT, both separately and in the framew…
On the coupling of axion-like particles to the top quark
Fabian Esser, Maeve Madigan, Veronica Sanz +1
In this paper we explore the coupling of a light axion-like particle (ALP) to top quarks. We use high-energy LHC probes, and examine both the direct probe to this coupling in assoc…
Top, Higgs, Diboson and Electroweak Fit to the Standard Model Effective Field Theory
Maeve Madigan
The Standard Model Effective Field Theory (SMEFT) provides a powerful theoretical framework for searching for subtle deviations from the Standard Model. In this talk, we present th…
Unbinned multivariate observables for global SMEFT analyses from machine learning
Raquel Gomez Ambrosio, Jaco ter Hoeve, Maeve Madigan +2
Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the i…
SMEFT Analysis of
Emanuele Bagnaschi, John Ellis, Maeve Madigan +3
We use the Fitmaker tool to incorporate the recent CDF measurement of in a global fit to electroweak, Higgs, and diboson data in the Standard Model Effective Field Theory (SM…
Parton distributions in the SMEFT from high-energy Drell-Yan tails
Maeve Madigan, James Moore
We present a study of the interplay between PDF and EFT effects in high-mass Drell-Yan at the LHC. We quantify the impact of a consistent joint determination of the PDFs and Wilson…
Publishing statistical models: Getting the most out of particle physics experiments
Kyle Cranmer, Sabine Kraml, Harrison B. Prosper +30
The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In…
A Supersymmetric Anomaly-free Atlas
B. C. Allanach, Maeve Madigan, Joseph Tooby-Smith
Extensions of the minimal supersymmetric standard model (MSSM) gauge group abound in the literature. Several of these include an additional gauge group. Chiral fermions' c…
Parton distributions in the SMEFT from high-energy Drell-Yan tails
Admir Greljo, Shayan Iranipour, Zahari Kassabov +5
The high-energy tails of charged- and neutral-current Drell-Yan processes provide important constraints on the light quark and anti-quark parton distribution functions (PDFs) in th…
Top, Higgs, Diboson and Electroweak Fit to the Standard Model Effective Field Theory
John Ellis, Maeve Madigan, Ken Mimasu +2
The search for effective field theory deformations of the Standard Model (SM) is a major goal of particle physics that can benefit from a global approach in the framework of the St…
Sensitivity of Future Hadron Colliders to Leptoquark Pair Production in the Di-Muon Di-Jets Channel
B. C. Allanach, Tyler Corbett, Maeve Madigan
We estimate the future sensitivity of the high luminosity (HL-) and high energy (HE-) modes of the Large Hadron Collider (LHC) and of a 100 TeV future circular collider (FCC-hh) to…
astroABC: An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation
Elise Jennings, Maeve Madigan
Given the complexity of modern cosmological parameter inference where we are faced with non-Gaussian data and noise, correlated systematics and multi-probe correlated data sets, th…