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mu@elyaraomtqi.mebt.c [unscramble]
Tom
Marty
I’m a Ph.D. student at Mila under
the supervision of Dhanya Sridhar.
I'm originally from Réunion
Island  . I own an
engineering
degree from École
Polytechnique (X2018) in Paris, and a Master's degree in
Operational Research from Polytechnique Montréal.
My current research interest falls at the crossroad of language
understanding, generalization and Deep Learning with a focus on :
- Probabilistic and Causal Modelling
- Meta-learning
In a previous researcher life, I specialized in Reinforcement Learning
and Combinatorial Optimization. I developed SeaPearl, a fully
functional Open-Source Constraint Programming solver capable of learning
optimal branching heuristic
using RL.
Feel free to reach out to me via email if you have any
questions or for
potential collaborations.
Scholar
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CV
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GitHub
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Twitter
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LinkedIn
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News
Research Experience
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Visiting ResearcherMarch. 2023 - October 2023
Service Now Research, Montréal, Canada
Supervisor: Alexandre Piche, Maxime Gasse, Quentin Cappart
Research Area: LLM, Task solving, Webpage processing
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Research CoordinatorFebruary. 2022 - July 2022
Research InternFebruary. 2021 - July 2021
Corail
Research Group, Montréal, Canada
Supervisor: Quentin Cappart, Louis-Martin Rousseau
Research Area: Constraint Programming, Reinforcement Learning, GNN
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Software Development InternJun. 2020 - Sept. 2020
Dronisos,
Bordeaux, France
Developed Harmony, a particle based meta-heuristic that secures massive
drone swarms (+500 agents)
Research Area: Meta-heuristics, Force fields.
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In-Context Learning as causal structure learners
Dec' 24
Work in progress...
Keywords : Causal Structure Learning, Compression, Meta-learning
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In-Context Learning and Occam's razor
Mar' 24 - Oct' 24
We propose an explanation for the strong generalization abilities of
in-context learners at inference time, by drawing connections between
meta-learning, In-Context Learning and Information theory.
Keywords : Meta-learning, Kolmogorov complexity, Occam's razor.
Paper
(Under review) /
Code
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The BrowserGym Ecosystem for Web Agent Research
BrowserGym is a fully deployed Open-Source Gym environment for Web-Automation. It serves to evaluate Web
Agents at solving a wide range of tasks on the web. it's a common effort between Service Now Research, CMU
and Mila.
Keywords : Web-Automation, Task solving, benchmark.
Journal Paper
(Accepted at TMLR) /
Code
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WorkArena : LLMs as Generalist Web Agents
Avr' 23 - Mar' 24
As part of my research at ServiceNow Research, I worked on WorkArena : an
Open-Source benchmark as a Gym environment to evaluate Web Agent to solve common knowledge
task on a Web Browser. Published at NeurIPS 2023 FMDM Workshop and ICML 2024.
Keywords : Web-Automation, Task solving, benchmark.
Paper
(Accepted
at ICML2024) /
Website
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Code
Workshop Paper
(Accepted
at FMDM@NeurIPS2023)
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SeaPearl : a Constraint Programming Solver guided by
Reinforcement Learning
Feb' 21 - Jul' 24
I was an active lead maintainer of the Open-Source and collaborative
project SeaPearl. The goal is to develop an intelligent constraint
programming solver that can learn to solve any Constraint Optimization
Problems using Reinforcement Learning on Graphs.
The entire solver is written in Julia  . Click
here for detailed
explanations.
Keywords : Combinatorial Optimization, Reinforcement learning, GNNs
Journal Paper
(Accepted
at Constraint)
Original Paper (Accepted
at CP2023)
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Code
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Adversarial Attacks on Sentiment Analysis models
Mar' 22 - May' 22
This project was carried out in the framework of the IFT6167 seminar led by Prof. Irina
Rish (Mila, Québec).
In this work, we aim to show, regarding Natural Language
Sentiment Analysis, that there exists a relationship between model size and
robustness to adversarial attacks. Ultimately, uncovering the emergence of power laws and
testing the robustness of language model with scale. We evaluate the performance of various
Eleuther AI GPT
models such as GPT-Neo 125M, GPT-Neo 1.3B, GPT-Neo 2.7B, GPT-J 6B against adversarial
attacks. We fined-tuned (trained on adversarial example) our different GPT models on common
datasets (Rotten Tomatoes, IMDB...) and evaluated them separately to quantify the effects of
scale on adversarial training.
Report /
Slides
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Diffusion Geodesic : a new Metric for non-linear Dimensionality Reduction
Sep' 21 - Jan' 22
In collaboration with Ph.D. candidate Guillaume Huguet (Mila,
Québec), we present our method for non-linear dimensionality reduction called Diffusion Geodesic.
Dimensionality reduction techniques are often used to visualize the underlying geometry of a
high-dimensional dataset. These methods usually rely on specific similarity measures. In this project,
we first approximate the geodesic distance using a diffusion process over the underlying manifold, then
we use Multi-Dimentionnal Scaling combined with our previously defined pairwise
'distances' to embed our Manifold in a lower dimensional space. We compare our model with popular
algorithms such as PHATE, UMAP, and Isomap on toy datasets and RNA-seq dataset.
Report /
Code
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Autonomous Drone Swarm Deployment
Dec' 20 – Mar' 21
In collaboration with Sariah Al Saati (ENS), Mehdi Benharrats (X-HEC), Swann Chelly (Sorbonne
University) and Pierre Tessier, this report proposes a method for the coverage of a rescue zone with a
swarm of UAV’s in order to detect possible target of interest.
The method is based on Collaborative Reinforcement Learning. It also presents a pipeline to locate
points of interest in 3D from a set of 2D images using Inverse Projection Transformation and 3D ray clustering.
Report
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Realtime 3D Deep Motion Capture
Oct' 20 – Dec' 20
In collaboration with Pierre Tessier (MS, Columbia University), the objective of our project was to
implement a intelligent 2D to 3D Motion Capture mechanism that uses only the video stream of a webcam as
input. We were able to animate relatively accurately this Mk-44 Iron Man 3D model.
The project is based on the model DOPE presented in this paper for the automatic 3D rig
generation from video input coupled with a quaternion-based 3D rotation inference pipeline for 3D model animation.
Report (french) /
Video /
Code /
Slides
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Sketch-based Shape Retrieval
Sep' 20 – Dec' 20
In collaboration with Pierre Tessier (MS, Columbia University), the objective of our project is to
enable an efficient search in a 3D model bank models from simple hand drawings. The project is based on
this paper SIGGRAPH2012.
The project lies on differents techniques such Suggestive Contouring (Canny filter), Gabor filtering
(gaussian convolution on Fourier Transformation of the input image) and histogram representation using
Visual Vocabulary.
Looking back at this project, I saw that another paper with much more impressive results came out a few years later using
Siamese convolutional Neural Networks for feature extraction.
Report (french) /
Code /
Slides
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Procedural modeling of a 3D rendered scene
Mar' 20 – June' 20
In collaboration with Elsa Deville  (MS, Imperial College), the
objective of our project is to fully render a realistic 3D marine scene using only randomized procedural
modeling (OpenGL).
The project implements different visual elements among them terrain generation using Perlin Noise, a realistic simulation of a fish swarm movement based on this
paper and realistic-looking ocean waves. (Trochoidal Waves : exact
solution of the Euler equations for periodic surface gravity waves).
Report (french)
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Education
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Ph.D. in Machine LearningJanuary
2024 - Present
MILA
Advisor: Dhanya Sridhar
Montréal, Canada
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Master Thesis in Machine LearningSeptember
2021 - July 2023
Polytechnique Montréal
Advisor: Quentin
Cappart, Louis-Martin Rousseau
Montréal, Canada
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Bachelor of Science - Ingénieur Polytechnicien X2018Jun. 2018 - May. 2021
l'Ecole Polytechnique
Major in Computer Science
Minor in Applied Mathematics
Ranked 3rd out of 3000+ candidates at the national entrance exam for Ecole Polytechnique, the most
prestigious and selective engineering school in France.
Palaiseau, France
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CPGE : Higher School Preparatory ClassesJun.
2016 - May. 2018
Lycée Jean-Baptiste Say
Intensive multi-disciplinary program leading to competitive entrance exams of french Grande Ecoles.
Paris XVI, France
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Initiatives and Academic Services
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Grants, Scholarships and Awards
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Distinguished Paper Award at CP2023, Toronto Sep.
2023
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Mitacs Accelerate scholarship of two units (30000$ CAD) Mar.
2023
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Vallet Fondation scholarship for outstanding CPGE students 2018
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French state Scholarship for undergraduate studies2016
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