Salem Lahlou

According to our database, Salem Lahlou authored at least 24 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Improved Exploration in GFlownets via Enhanced Epistemic Neural Networks.

Sajan Muhammad, Salem Lahlou

CoRR, June, 2025

FinChain: A Symbolic Benchmark for Verifiable Chain-of-Thought Financial Reasoning.

Zhuohan Xie, Dhruv Sahnan, Debopriyo Banerjee, Georgi Georgiev, Rushil Thareja, Hachem Madmoun, Jinyan Su, Aaryamonvikram Singh, Yuxia Wang, Rui Xing, Fajri Koto, Haonan Li, Ivan Koychev, Tanmoy Chakraborty, Salem Lahlou, Veselin Stoyanov, Preslav Nakov

CoRR, June, 2025

SVRPBench: A Realistic Benchmark for Stochastic Vehicle Routing Problem.

Ahmed Heakl, Yahia Salaheldin Shaaban, Martin Takác, Salem Lahlou, Zangir Iklassov

CoRR, May, 2025

Semantic Communication meets System 2 ML: How Abstraction, Compositionality and Emergent Languages Shape Intelligence.

Mehdi Bennis, Salem Lahlou

CoRR, May, 2025

Loss-Guided Auxiliary Agents for Overcoming Mode Collapse in GFlowNets.

Idriss Malek, Abhijith Sharma, Salem Lahlou

CoRR, May, 2025

LLM-BABYBENCH: Understanding and Evaluating Grounded Planning and Reasoning in LLMs.

Omar Choukrani, Idriss Malek, Daniil Orel, Zhuohan Xie, Zangir Iklassov, Martin Takác, Salem Lahlou

CoRR, May, 2025

Mitigating Societal Cognitive Overload in the Age of AI: Challenges and Directions.

Salem Lahlou

CoRR, April, 2025

Accurate and Diverse LLM Mathematical Reasoning via Automated PRM-Guided GFlowNets.

Adam Younsi, Abdalgader Abubaker, Mohamed El Amine Seddik, Hakim Hacid, Salem Lahlou

CoRR, April, 2025

On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis.

Junyi Guan, Abhijith Sharma, Chong Tian, Salem Lahlou

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

PORT: Preference Optimization on Reasoning Traces.

Salem Lahlou, Abdalgader Abubaker, Hakim Hacid

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

2024

On Generalization for Generative Flow Networks.

Anas Krichel, Nikolay Malkin, Salem Lahlou, Yoshua Bengio

CoRR, 2024

Investigating Regularization of Self-Play Language Models.

Réda Alami, Abdalgader Abubaker, Mastane Achab, Mohamed El Amine Seddik, Salem Lahlou

CoRR, 2024

2023

DEUP: Direct Epistemic Uncertainty Prediction.

Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio

Trans. Mach. Learn. Res., 2023

GFlowNet Foundations.

Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J. Hu, Mo Tiwari, Emmanuel Bengio

J. Mach. Learn. Res., 2023

BatchGFN: Generative Flow Networks for Batch Active Learning.

Shreshth A. Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal

CoRR, 2023

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks.

Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo de Lazcano, Lucas Willems, Salem Lahlou, Suman Pal, Pablo Samuel Castro, Jordan K. Terry

CoRR, 2023

torchgfn: A PyTorch GFlowNet library.

Salem Lahlou, Joseph D. Viviano, Victor Schmidt

CoRR, 2023

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks.

Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo Perez-Vicente, Lucas Willems, Salem Lahlou, Suman Pal, Pablo Samuel Castro, Jordan K. Terry

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GFlowOut: Dropout with Generative Flow Networks.

Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio

Proceedings of the International Conference on Machine Learning, 2023

A theory of continuous generative flow networks.

Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin

Proceedings of the International Conference on Machine Learning, 2023

GFlowNets and variational inference.

Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2020

Mastering Rate based Curriculum Learning.

Lucas Willems, Salem Lahlou, Yoshua Bengio

CoRR, 2020

2019

BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning.

Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop.

Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio

CoRR, 2018