Francesco Faccio

Dalle Molle Institute for Artificial Intelligence Research — Switzerland

Computer Science · Physical Sciences

4h-index70citations28works0.82yr avg
OpenAlex↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Reinforcement Learning in Robotics(10), Topic Modeling(3), Software Engineering Research(3), Natural Language Processing Techniques(2), Neural Networks and Applications(2)

Publications28 total

Towards an Extremely Robust Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms
2025
On the Convergence and Stability of Upside-Down Reinforcement Learning, Goal-Conditioned Supervised Learning, and Online Decision Transformers
arXiv (Cornell University)·2025Open Access
Mindstorms in Natural Language-Based Societies of Mind
Computational Visual Media·2025· 4 citedOpen Access
Upside Down Reinforcement Learning with Policy Generators
arXiv (Cornell University)·2025Open Access
How to Correctly do Semantic Backpropagation on Language-based Agentic Systems
arXiv (Cornell University)·2024Open Access
Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning
arXiv (Cornell University)·2024Open Access
Highway Value Iteration Networks
arXiv (Cornell University)·2024Open Access
Highway Reinforcement Learning
arXiv (Cornell University)·2024Open Access
Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms
arXiv (Cornell University)·2024Open Access
Faster Diffusion via Temporal Attention Decomposition
arXiv (Cornell University)·2024· 2 citedOpen Access
Learning Useful Representations of Recurrent Neural Network Weight Matrices
arXiv (Cornell University)·2024· 1 citedOpen Access
Language Agents as Optimizable Graphs
arXiv (Cornell University)·2024· 2 citedOpen Access
Learning to Identify Critical States for Reinforcement Learning from Videos
2023· 4 cited
The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute
arXiv (Cornell University)·2023· 2 citedOpen Access
Learning to Identify Critical States for Reinforcement Learning from Videos
arXiv (Cornell University)·2023Open Access
Goal-Conditioned Generators of Deep Policies
Proceedings of the AAAI Conference on Artificial Intelligence·2023· 3 citedOpen Access
Mindstorms in Natural Language-Based Societies of Mind
arXiv (Cornell University)·2023· 14 citedOpen Access
Goal-Conditioned Generators of Deep Policies
arXiv (Cornell University)·2022· 1 citedOpen Access
General Policy Evaluation and Improvement by Learning to Identify Few But Crucial States
arXiv (Cornell University)·2022· 3 citedOpen Access
Reward-Weighted Regression Converges to a Global Optimum
Proceedings of the AAAI Conference on Artificial Intelligence·2022· 1 citedOpen Access
page 1 of 2Next →

Frequent Co-authors

Jürgen Schmidhuber(25), Dylan R. Ashley(11), Vincent Herrmann(7), Louis Kirsch(7), Mingchen Zhuge(5), Haozhe Liu(5), Miroslav Štrupl(5), Aditya Ramesh(4), Wenyi Wang(4), Yuhui Wang(4), Bernard Ghanem(4), Rupesh K. Srivastava(4), Kazuki Irie(3), Bing Li(3), Imanol Schlag(3), Aleksandar Stanić(3), Qingyuan Wu(3), Róbert Csordás(2), Anand Gopalakrishnan(2), Abdullah Hamdi(2)