12 citations · 21 across the 15 of their papers we have counts for
4 papers · 1 filter
MiniLingua: A Small Open-Source LLM for European Languages
Anna Aksenova, Boris Zverkov, Nicola Dainese +2
Large language models are powerful but often limited by high computational cost, privacy concerns, and English-centric training. Recent progress demonstrates that small, efficient…
Efficient Knowledge Injection in LLMs via Self-Distillation
Kalle Kujanpää, Pekka Marttinen, Harri Valpola +1
In many practical applications, large language models (LLMs) need to acquire new knowledge not present in their pre-training data. Efficiently leveraging this knowledge usually rel…
In-Context Symbolic Regression: Leveraging Large Language Models for Function Discovery
Matteo Merler, Katsiaryna Haitsiukevich, Nicola Dainese +1
State of the art Symbolic Regression (SR) methods currently build specialized models, while the application of Large Language Models (LLMs) remains largely unexplored. In this work…
Improved Compositional Generalization by Generating Demonstrations for Meta-Learning
Sam Spilsbury, Pekka Marttinen, Alexander Ilin
Meta-learning and few-shot prompting are viable methods to induce certain types of compositional behaviour. However, these methods can be very sensitive to the choice of support ex…