Jean Kaddour

According to our database, Jean Kaddour authored at least 23 papers between 2018 and 2025.

Collaborative distances:

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

2025

REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards.

Zafir Stojanovski, Oliver Stanley, Joe Sharratt, Richard Jones, Abdulhakeem Adefioye, Jean Kaddour, Andreas Köpf

CoRR, May, 2025

Causal Machine Learning: A Survey and Open Problems.

Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva

Found. Trends Optim., 2025

Are We Done with MMLU?

Aryo Pradipta Gema, Joshua Ong Jun Leang, Giwon Hong, Alessio Devoto, Alberto Carlo Maria Mancino, Rohit Saxena, Xuanli He, Yu Zhao, Xiaotang Du, Mohammad Reza Ghasemi Madani, Claire Barale, Robert McHardy, Joshua Harris, Jean Kaddour, Emile van Krieken, Pasquale Minervini

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

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.

Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, Simon Brunner, Chen Gong, James Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, et al.

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models.

Georgy Tyukin, Gbètondji J.-S. Dovonon, Jean Kaddour, Pasquale Minervini

CoRR, 2024

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.

Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, Simon Brunner, Chen Gong, Thong Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, Naman Jain, Alex Gu, Zhoujun Cheng, Jiawei Liu, Qian Liu, Zijian Wang, David Lo, Binyuan Hui, Niklas Muennighoff, Daniel Fried, Xiaoning Du, Harm de Vries, Leandro von Werra

CoRR, 2024

2023

Text Data Augmentation in Low-Resource Settings via Fine-Tuning of Large Language Models.

Jean Kaddour, Qi Liu

CoRR, 2023

Challenges and Applications of Large Language Models.

Jean Kaddour, Joshua Harris, Maximilian Mozes, Herbie Bradley, Roberta Raileanu, Robert McHardy

CoRR, 2023

Understanding the Effectiveness of Early Weight Averaging for Training Large Language Models.

Sunny Sanyal, Jean Kaddour, Abhishek Kumar, Sujay Sanghavi

CoRR, 2023

TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models.

Yuwei Yin, Jean Kaddour, Xiang Zhang, Yixin Nie, Zhenguang Liu, Lingpeng Kong, Qi Liu

CoRR, 2023

The MiniPile Challenge for Data-Efficient Language Models.

Jean Kaddour

CoRR, 2023

Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases.

Aengus Lynch, Gbètondji J.-S. Dovonon, Jean Kaddour, Ricardo Silva

CoRR, 2023

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

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

No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models.

Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner

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

DAG Learning on the Permutahedron.

Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt J. Kusner, Vlad Niculae

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging.

Jean Kaddour

CoRR, 2022

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Matt J. Kusner, Joan Lasenby, Qi Liu

CoRR, 2022

Questions for Flat-Minima Optimization of Modern Neural Networks.

Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J. Kusner

CoRR, 2022

When Do Flat Minima Optimizers Work?

Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J. Kusner

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Graph Intervention Networks for Causal Effect Estimation.

Jean Kaddour, Qi Liu, Yuchen Zhu, Matt J. Kusner, Ricardo Silva

CoRR, 2021

Causal Effect Inference for Structured Treatments.

Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J. Kusner, Ricardo Silva

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Probabilistic Active Meta-Learning.

Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

SATISFy: Towards a Self-Learning Analyzer for Time Series Forecasting in Self-Improving Systems.

Christian Krupitzer, Martin Pfannemüller, Jean Kaddour, Christian Becker

Proceedings of the 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS*W), 2018