128 citations · 143 across the 11 of their papers we have counts for
12 papers
CogScale: Scalable Benchmark for Sequence Processing
Yannis Bendi-Ouis, Romain de Coudenhove, Xavier Hinaut
The ability to maintain and manipulate information over time is a fundamental aspect of living beings and Artificial Intelligence. While modern models have achieved remarkable succ…
Fast Linear Reservoirs via Diagonalization
Romain de Coudenhove, Yannis Bendi-Ouis, Anthony Strock +1
We introduce a diagonalization-based optimization for Linear Echo State Networks (ESNs) that reduces the per-step computational complexity of reservoir state updates from quadratic…
Software Engineering Agents for Embodied Controller Generation : A Study in Minigrid Environments
Timothé Boulet, Xavier Hinaut, Clément Moulin-Frier
Software Engineering Agents (SWE-Agents) have proven effective for traditional software engineering tasks with accessible codebases, but their performance for embodied tasks requir…
ReservoirChat: Interactive Documentation Enhanced with LLM and Knowledge Graph for ReservoirPy
Virgile Boraud, Yannis Bendi-Ouis, Paul Bernard +1
We introduce a tool designed to improve the capabilities of Large Language Models (LLMs) in assisting with code development using the ReservoirPy library, as well as in answering c…
Echo State Transformer: Attention Over Finite Memories
Yannis Bendi-Ouis, Xavier Hinaut
While Large Language Models and their underlying Transformer architecture are remarkably efficient, they do not reflect how our brain processes and learns a diversity of cognitive…
Deploying Open-Source Large Language Models: A performance Analysis
Yannis Bendi-Ouis, Dan Dutartre, Xavier Hinaut
Since the release of ChatGPT in November 2022, large language models (LLMs) have seen considerable success, including in the open-source community, with many open-weight models ava…
Evolving Reservoirs for Meta Reinforcement Learning
Corentin Léger, Gautier Hamon, Eleni Nisioti +2
Animals often demonstrate a remarkable ability to adapt to their environments during their lifetime. They do so partly due to the evolution of morphological and neural structures.…
Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey)
Subba Reddy Oota, Zijiao Chen, Manish Gupta +4
Can artificial intelligence unlock the secrets of the human brain? How do the inner mechanisms of deep learning models relate to our neural circuits? Is it possible to enhance AI b…
A journey in ESN and LSTM visualisations on a language task
Alexandre Variengien, Xavier Hinaut
Echo States Networks (ESN) and Long-Short Term Memory networks (LSTM) are two popular architectures of Recurrent Neural Networks (RNN) to solve machine learning task involving sequ…
Transfer between long-term and short-term memory using Conceptors
Anthony Strock, Nicolas Rougier, Xavier Hinaut
We introduce a recurrent neural network model of working memory combining short-term and long-term components. e short-term component is modelled using a gated reservoir model that…
A Simple Reservoir Model of Working Memory with Real Values
Anthony Strock, Nicolas Rougier, Xavier Hinaut
The prefrontal cortex is known to be involved in many high-level cognitive functions, in particular, working memory. Here, we study to what extent a group of randomly connected uni…
Sustainable computational science: the ReScience initiative
Nicolas P. Rougier, Konrad Hinsen, Frédéric Alexandre +42
Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In…