30 citations · 44 across the 6 of their papers we have counts for
7 papers
Turnslide: Scalable Multi-Turn Data Synthesis by Walking a Finite-State Machine
Aaron Fainman, Gabriela Kadlecová, Maciej Gryka +7
Small language models are inexpensive to serve and can run on private infrastructure, but base models are often not good enough at multi-turn tool calling, and fine-tuning them nee…
SAR Object Detection with Self-Supervised Pretraining and Curriculum-Aware Sampling
Yasin Almalioglu, Andrzej Kucik, Geoffrey French +3
Object detection in satellite-borne Synthetic Aperture Radar (SAR) imagery holds immense potential in tasks such as urban monitoring and disaster response. However, the inherent co…
Hyperparameter Optimization in Machine Learning
Luca Franceschi, Michele Donini, Valerio Perrone +5
Hyperparameters are configuration variables controlling the behavior of machine learning algorithms. They are ubiquitous in machine learning and artificial intelligence and the cho…
Structural Pruning of Pre-trained Language Models via Neural Architecture Search
Aaron Klein, Jacek Golebiowski, Xingchen Ma +2
Pre-trained language models (PLM), for example BERT or RoBERTa, mark the state-of-the-art for natural language understanding task when fine-tuned on labeled data. However, their la…
Explaining Probabilistic Models with Distributional Values
Luca Franceschi, Michele Donini, Cédric Archambeau +1
A large branch of explainable machine learning is grounded in cooperative game theory. However, research indicates that game-theoretic explanations may mislead or be hard to interp…
Geographical Erasure in Language Generation
Pola Schwöbel, Jacek Golebiowski, Michele Donini +2
Large language models (LLMs) encode vast amounts of world knowledge. However, since these models are trained on large swaths of internet data, they are at risk of inordinately capt…
Multiple Gaussian Process Models
Cedric Archambeau, Francis Bach
We consider a Gaussian process formulation of the multiple kernel learning problem. The goal is to select the convex combination of kernel matrices that best explains the data and…