Clustering-Oriented Representation Learning with Attractive-Repulsive Loss. - Kian Kenyon-Dean; Andre Cianflone; Lucas Page-Caccia; Guillaume Rabusseau; Jackie Chi Kit Cheung; Doina Precup (CoRR, 2018)

Deep Generative Modeling of LiDAR Data. - Lucas Caccia; Herke van Hoof; Aaron C. Courville; Joelle Pineau (IROS, 2019)

Online Continual Learning with Maximal Interfered Retrieval. - Rahaf Aljundi; Eugene Belilovsky; Tinne Tuytelaars; Laurent Charlin; Massimo Caccia; Min Lin; Lucas Page-Caccia (NeurIPS, 2019)

Recurrent Value Functions. - Pierre Thodoroff; Nishanth Anand; Lucas Caccia; Doina Precup; Joelle Pineau (CoRR, 2019)

Online Continual Learning with Maximally Interfered Retrieval. - Rahaf Aljundi; Lucas Caccia; Eugene Belilovsky; Massimo Caccia; Min Lin; Laurent Charlin; Tinne Tuytelaars (CoRR, 2019)

Online Learned Continual Compression with Stacked Quantization Module. - Lucas Caccia; Eugene Belilovsky; Massimo Caccia; Joelle Pineau (CoRR, 2019)

Language GANs Falling Short. - Massimo Caccia; Lucas Caccia; William Fedus; Hugo Larochelle; Joelle Pineau; Laurent Charlin (ICLR, 2020)

Online Learned Continual Compression with Adaptive Quantization Modules. - Lucas Caccia; Eugene Belilovsky; Massimo Caccia; Joelle Pineau (ICML, 2020)

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. - Massimo Caccia; Pau Rodríguez; Oleksiy Ostapenko; Fabrice Normandin; Min Lin; Lucas Page-Caccia; Issam Hadj Laradji; Irina Rish; Alexandre Lacoste; David Vázquez 001; Laurent Charlin (NeurIPS, 2020)

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. - Massimo Caccia; Pau Rodríguez; Oleksiy Ostapenko; Fabrice Normandin; Min Lin; Lucas Caccia; Issam H. Laradji; Irina Rish; Alexandre Lacoste; David Vázquez 001; Laurent Charlin (CoRR, 2020)

SPeCiaL: Self-supervised Pretraining for Continual Learning. - Lucas Caccia; Joelle Pineau (CSSL, 2021)

Reducing Representation Drift in Online Continual Learning. - Lucas Caccia; Rahaf Aljundi; Tinne Tuytelaars; Joelle Pineau; Eugene Belilovsky (CoRR, 2021)

Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning. - Eugene Belilovsky; Louis Leconte; Lucas Caccia; Michael Eickenberg; Edouard Oyallon (CoRR, 2021)

On Anytime Learning at Macroscale. - Lucas Caccia; Jing Xu; Myle Ott; Marc'Aurelio Ranzato; Ludovic Denoyer (CoLLAs, 2022)

New Insights on Reducing Abrupt Representation Change in Online Continual Learning. - Lucas Caccia; Rahaf Aljundi; Nader Asadi; Tinne Tuytelaars; Joelle Pineau; Eugene Belilovsky (ICLR, 2022)

Multi-Head Adapter Routing for Data-Efficient Fine-Tuning. - Lucas Caccia; Edoardo Maria Ponti; Lucas Liu; Matheus Pereira; Nicolas Le Roux; Alessandro Sordoni (CoRR, 2022)

Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning. - Gwen Legate; Lucas Caccia; Eugene Belilovsky (CoLLAs, 2023)

Building a Subspace of Policies for Scalable Continual Learning. - Jean-Baptiste Gaya; Thang Doan; Lucas Caccia; Laure Soulier; Ludovic Denoyer; Roberta Raileanu (ICLR, 2023)

Guiding The Last Layer in Federated Learning with Pre-Trained Models. - Gwen Legate; Nicolas Bernier; Lucas Page-Caccia; Edouard Oyallon; Eugene Belilovsky (NeurIPS, 2023)

Multi-Head Adapter Routing for Cross-Task Generalization. - Lucas Page-Caccia; Edoardo Maria Ponti; Zhan Su 002; Matheus Pereira; Nicolas Le Roux; Alessandro Sordoni (NeurIPS, 2023)

Guiding Language Model Reasoning with Planning Tokens. - Xinyi Wang 003; Lucas Caccia; Oleksiy Ostapenko; Xingdi Yuan; Alessandro Sordoni (CoRR, 2023)

Towards Modular LLMs by Building and Reusing a Library of LoRAs. - Oleksiy Ostapenko; Zhan Su 002; Edoardo M. Ponti; Laurent Charlin; Nicolas Le Roux; Lucas Caccia; Alessandro Sordoni (ICML, 2024)

Towards Modular LLMs by Building and Reusing a Library of LoRAs. - Oleksiy Ostapenko; Zhan Su 002; Edoardo Maria Ponti; Laurent Charlin; Nicolas Le Roux; Matheus Pereira; Lucas Caccia; Alessandro Sordoni (CoRR, 2024)

A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment. - Jean-Philippe Corbeil; Amin Dada; Jean-Michel Attendu; Asma Ben Abacha; Alessandro Sordoni; Lucas Caccia; François Beaulieu; Thomas Lin; Jens Kleesiek; Paul Vozila (ACL (1), 2025)

A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning. - Prateek Yadav; Colin Raffel; Mohammed Muqeeth; Lucas Caccia; Haokun Liu; Tianlong Chen 001; Mohit Bansal; Leshem Choshen; Alessandro Sordoni (Trans. Mach. Learn. Res., 2025)

Generative Modeling of Individual Behavior at Scale. - Nabil Omi; Lucas Caccia; Anurag Sarkar; Jordan T. Ash; Siddhartha Sen 001 (CoRR, 2025)

Training Plug-n-Play Knowledge Modules with Deep Context Distillation. - Lucas Caccia; Alan Ansell; Edoardo M. Ponti; Ivan Vulic; Alessandro Sordoni (CoRR, 2025)

debug-gym: A Text-Based Environment for Interactive Debugging. - Xingdi Yuan; Morgane M. Moss; Charbel El Feghali; Chinmay Singh; Darya Moldavskaya; Drew MacPhee; Lucas Caccia; Matheus Pereira; Minseon Kim; Alessandro Sordoni; Marc-Alexandre Côté (CoRR, 2025)

Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts. - Samin Yeasar Arnob; Zhan Su 002; Minseon Kim; Oleksiy Ostapenko; Riyasat Ohib; Esra'a Saleh; Doina Precup; Lucas Caccia; Alessandro Sordoni (CoRR, 2025)