activity
20192026
most citedEvolving Structures in Complex Systems

12 citations · 22 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Shieldstral

Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +273

We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7 its size on text safety benchmarks and set…

cs.NE2023

Unsupervised Learning in Complex Systems

Hugo Cisneros

In this thesis, we explore the use of complex systems to study learning and adaptation in natural and artificial systems. The goal is to develop autonomous systems that can learn w…

cs.CL2022★ 4 cited

Preserving Semantics in Textual Adversarial Attacks

David Herel, Hugo Cisneros, Tomas Mikolov

The growth of hateful online content, or hate speech, has been associated with a global increase in violent crimes against minorities [23]. Harmful online content can be produced e…

cs.LG2022★ 1 cited

Benchmarking Learning Efficiency in Deep Reservoir Computing

Hugo Cisneros, Josef Sivic, Tomas Mikolov

It is common to evaluate the performance of a machine learning model by measuring its predictive power on a test dataset. This approach favors complicated models that can smoothly…

nlin.CG2021★ 3 cited

Visualizing computation in large-scale cellular automata

Hugo Cisneros, Josef Sivic, Tomas Mikolov

Emergent processes in complex systems such as cellular automata can perform computations of increasing complexity, and could possibly lead to artificial evolution. Such a feat woul…

nlin.CG2019★ 12 cited

Evolving Structures in Complex Systems

Hugo Cisneros, Josef Sivic, Tomas Mikolov

In this paper we propose an approach for measuring growth of complexity of emerging patterns in complex systems such as cellular automata. We discuss several ways how a metric for…

cs.CL2019★ 2 cited

Hybrid Approaches for our Participation to the n2c2 Challenge on Cohort Selection for Clinical Trials

Xavier Tannier, Nicolas Paris, Hugo Cisneros +10

Objective: Natural language processing can help minimize human intervention in identifying patients meeting eligibility criteria for clinical trials, but there is still a long way…