12 citations · 15 across the 4 of their papers we have counts for
4 papers
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…
ViPlan: A Benchmark for Visual Planning with Symbolic Predicates and Vision-Language Models
Matteo Merler, Nicola Dainese, Minttu Alakuijala +5
Integrating Large Language Models with symbolic planners is a promising direction for obtaining verifiable and grounded plans, with recent works extending this idea to visual domai…
Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
Nicola Dainese, Matteo Merler, Minttu Alakuijala +1
In this work we consider Code World Models, world models generated by a Large Language Model (LLM) in the form of Python code for model-based Reinforcement Learning (RL). Calling c…
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…