Publications

An up-to-date list of my publications is available on my google scholar profile.
You can also see some project highlights on my research group webpage.

2026

• Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
  L. Boisvert, A. Puri, C. K. R. Evuru, N. M. Sepahvand, N. Chapados, Q. Cappart, J. Stanley, A. Lacoste, K. Dvijotham, A. Drouin
  Proceedings of CAIS 2026 conference (Best paper award)

• Deep Learning for Data-Driven Districting-and-Routing
  A. Ferraz, C. Ahmed, Q. Cappart, T. Vidal
  Transportation Science (2026)

2025

• DoomArena: A Framework for Testing AI Agents Against Evolving Security Threats
  L. Boisvert, A. Puri, G. Huang, M. Bansal, C. K. R. Evuru, A. Bose, M. Fazel, Q. Cappart, A. Lacoste, A. Drouin, K. Dvijotham
  Proceedings of COLM 2025 conference

• The BrowserGym Ecosystem for Web Agent Research
  T. Le Sellier De Chezelles, M. Gasse, A. Drouin, M. Caccia, L. Boisvert, M. Thakkar, T. Marty, R. Assouel, S. Shayegan, L. Jang, X. Lù, O. Yoran, De. Kong, F. Xu, S. Reddy, Q. Cappart, G. Neubig, R. Salakhutdinov, N. Chapados, A. Lacoste
  Transactions on Machine Learning Research (2025)

• Combining Constraint Programming and Machine Learning: From Current Progress to Future Opportunities
  Q. Cappart, T. Guns, M. Lombardi, G. Pesant, D. Tsouros
  Journal of Artificial Intelligence Research (2025)

• A Column Generation Heuristic for Multi-depot Electric Bus Scheduling
  Y.-S. Montanaro, T. Jacquet, Q. Cappart, G. Desaulniers
  Proceedings of CPAIOR 2025 conference

• Shaping Reward Signals in Reinforcement Learning Using Constraint Programming
  C. Yin, Q. Cappart, G. Pesant
  Proceedings of CPAIOR 2025 conference

• A machine-learning-based column generation heuristic for electric bus scheduling
  J. Gerbaux, Q. Cappart, G. Desaulniers
  Computers & Operations Research (2025)

• Learning Valid Dual Bounds in Constraint Programming: Boosted Lagrangian Decomposition with Self-Supervised Learning
  S. Bessa, D. Dabert, M. Bourgeat, L.-M. Rousseau, Q. Cappart
  Proceedings of AAAI 2025 conference

2024

• Learning and Fine-tuning a Generic Value-Selection Heuristic Inside a Constraint Programming Solver
  T. Marty, L. Boisvert T. François, P. Tessier, L. Gauthier, L.-M. Rousseau, Q. Cappart
  Constraints (2024)

• WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
  L. Boisvert, M. Thakkar, M. Gasse, M. Caccia, T. Le Sellier De Chezelles, Q. Cappart, N. Chapados, A. Lacoste, A. Drouin
  Proceedings of NeurIPS 2024 Datasets and Benchmark (to appear)

• Learning Precedences for Scheduling Problems with Graph Neural Networks
  H. Verhaeghe, Q. Cappart, G. Pesant, C.-G. Quimper
  Proceedings of CP 2024 conference

• Learning Lagrangian Multipliers for the Travelling Salesman Problem
  A. Parjadis, Q. Cappart, B. Dilkina, A. Ferber, L.-M. Rousseau
  Proceedings of CP 2024 conference (Best ML paper award)

• Estimating Road Construction Costs with Explainable Machine Learning
  R. Larocque, A.-M. Boulé, Q. Cappart
  INFORMS Journal on Applied Analytics (2024)

• Winning the 2023 CityLearn Challenge: a Community-based Hierarchical Energy Systems Coordination Algorithm
  A. Garmendia, F. Morri, Q. Cappart, H. Le Cadre
  Proceedings of ECAI 2024 conference

• MARCO: A Memory-Augmented Reinforcement framework for Combinatorial Optimization
  A. Garmendia, J. Ceberio, A. Mendiburu, Q. Cappart
  Proceedings of IJCAI 2024 conference

• Acquiring Constraints for a Non-linear Transmission Maintenance Scheduling Problem
  H. Barral, M. Gaha, A. Dems, A. Côté, F. Nguewouo, Q. Cappart
  Proceedings of CPAIOR 2024 conference

• Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches
  L. Boisvert, H. Verhaeghe, Q. Cappart
  Proceedings of CPAIOR 2024 conference

• An Improved Neuro-Symbolic Architecture to Fine-Tune Generative AI Systems
  C. Yin, Q. Cappart, G. Pessant
  Proceedings of CPAIOR 2024 conference

• WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?
  A. Drouin, M. Gasse, M. Caccia, I. Laradji, M. Del Verme, T. Marty, L. Boisvert, M. Thakkar, Q. Cappart, D. Vazquez, N. Chapados, A. Lacoste
  ICLR 2024 Workshop on Large Language Model (LLM) Agent

• Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
  H. Hoppe, T. Enders, Q. Cappart, M. Schiffer
  Proceedings of L4DC conference

• An Exact Framework for Solving the Space-Time Dependent TSP
  I. Rudich, Q. Cappart, M. López-Ibáñez, M. Römer, L.-M. Rousseau
  Arxived (2024)

2023

• The Unsolved Challenges of LLMs as Generalist Web Agents: A Case Study
  R. Assouel, T. Marty, M. Caccia, I. H. Laradji, A. Drouin, S. Rajeswar, H. Palacios, Q. Cappart, D. Vazquez, N. Chapados, M. Gasse, A. Lacoste
  Foundation Models for Decision Making Workshop (affilated to NeurIPS 2023 conference)

• Learning a Generic Value-Selection Heuristic Inside a Constraint Programming Solver
  T. Marty, T. François, P. Tessier, L. Gauthier, L.-M. Rousseau, Q. Cappart
  Proceedings of CP 2023 conference (Distinguished paper)

• Improved Peel-and-Bound: Methods for Generating Dual Bounds with Multivalued Decision Diagrams
  I. Rudich, Q. Cappart, L.-M. Rousseau
  Journal of Artificial Intelligence Research (2023)

• Combinatorial optimization and reasoning with graph neural networks
  Q. Cappart, D. Chételat, E. Khalil, A. Lodi, C. Morris, P. Veličković
  Journal of Machine Learning Research (2023)

• Dynamic Routing and Wavelength Assignment with Reinforcement Learning
  P. Kafaei, Q. Cappart, N. Chapados, H. Pouya, L.-M. Rousseau
  INFORMS Journal on Optimization (2023)

• Explaining the Behavior of Reinforcement Learning Agents using Association Rules
  Z. Parham, V.T. de Lille, Q. Cappart
  Proceedings of LION 2023 conference

• Repositioning Fleet Vehicles: a Learning Pipeline
  A. Parjadis, Q. Cappart, Q. Massoteau, L.-M. Rousseau
  Proceedings of LION 2023 conference

2022

• Peel-and-Bound: Generating Stronger Relaxed Bounds with Multivalued Decision Diagrams
  I. Rudich, Q. Cappart, L.-M. Rousseau
  Proceedings of CP 2022 conference (Best paper award)

• Scheduling the Equipment Maintenance of an Electric Power Transmission Network Using Constraint Programming
  L. Popovic, A. Côté, M. Gaha, F. Nguewouo, Q. Cappart
  Proceedings of CP 2022 conference

• Improving Variable Orderings of Approximate Decision Diagrams Using Reinforcement Learning
  Q. Cappart, D. Bergman, L.-M. Rousseau, I. Prémont-Schwarz, A. Parjadis
  INFORMS Journal on Computing (2022)

• Learning the travelling salesperson problem requires rethinking generalization
  C. K. Joshi, Q. Cappart, L.-M. Rousseau, T. Laurent
  Constraints Journal (2022)

• On Causal Inference for Data-free Structured Pruning
  M. Ferianc, A. Sankaran, O. Mastropietro, E. Saboori, Q. Cappart
  Proceedings of ITCI’22 workshop (affilated to AAAI 2022 conference)

2021

• The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
  M. Gasse, Q. Cappart, A. Parjadis, et al.
  NeurIPS 2021 Competitions and Demonstrations Track

• Graph neural networks and deep reinforcement learning for simultaneous beam orientation and trajectory optimization of Cyberknife
  P. Kafaei, Q. Cappart, M.-A. Renaud, N. Chapados, L.-M. Rousseau
  Physics in Medicine & Biology Journal (2021)

• Improving branch-and-bound using decision diagrams and reinforcement learning
  A. Parjadis, Q. Cappart, L.-M. Rousseau, D. Bergman
  Proceedings of CPAIOR 2021 conference

• SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
  F. Chalumeau, I. Coulon, Q. Cappart, L.-M. Rousseau
  Proceedings of CPAIOR 2021 conference

• Combining reinforcement learning and constraint programming for combinatorial optimization
  Q. Cappart, T. Moisan, L.-M. Rousseau, I. Prémont-Schwarz, A. Cire
  Proceedings of AAAI 2021 conference

2020 and before

• Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning
  Q. Cappart, E. Goutierre, D. Bergman, L.-M. Rousseau
  Proceedings of AAAI 2019 conference

• How to Evaluate Machine Learning Approaches for Combinatorial Optimization: Application to the Travelling Salesman Problem
  A. François, Q. Cappart, L.-M. Rousseau
  ArXived (2019)

• A constraint programming approach for solving patient transportation problems
  Q. Cappart, C. Thomas, P. Schaus, L.-M. Rousseau
  Proceedings of CP 2018 conference

• EpisodeSupport: A global constraint for mining frequent patterns in a long sequence of events
  Q. Cappart, J. Aoga, P. Schaus
  Proceedings of CPAIOR 2018 conference

• Verification of interlocking systems using statistical model checking
  Q. Cappart, C. Limbrée, P. Schaus, J. Quilbeuf, L.-M. Traonouez, A. Legay
  Proceedings of HASE 2017 conference (IEEE)

• Rescheduling railway traffic on real time situations using time-interval variables
  Q. Cappart, P. Schaus
  Proceedings of CPAIOR 2017 conference

• A dedicated algorithm for verification of interlocking systems
  Q. Cappart, P. Schaus
  Proceedings of SAFECOMP 2016 conference

• Verification of Railway Interlocking - Compositional Approach with OCRA
  C. Limbrée, Q. Cappart, C. Pecheur, S. Tonetta
  Proceedings of RSSRail 2016 conference

• The World Migration Network: rankings, groups and gravity models
  Q. Cappart, A. Thonet
  Proceedings of EUROCON 2015 conference (IEEE - Student paper contest third prize)

• Verification by discrete simulation of interlocking systems
  Q. Cappart, C. Limbrée, P. Schaus, A. Legay
  Proceedings of ESM 2015 conference (EUROSIS)

• Verification of railway interlocking systems
  S. Busard, Q. Cappart, C. Limbrée, C. Pecheur, P. Schaus
  Proceedings of ESSS 2015 workshop (affilated to FM 2015 symposium)