Kaddour, Jean

18 publications

ICLR 2025 BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions Terry Yue Zhuo, Vu Minh Chien, 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, Naman Jain, Alex Gu, Zhoujun Cheng, Jiawei Liu, Qian Liu, Zijian Wang, Binyuan Hui, Niklas Muennighoff, David Lo, Daniel Fried, Xiaoning Du, Harm de Vries, Leandro Von Werra

NeurIPS 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

ICLRW 2025 Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases Aengus Lynch, Gbetondji Jean-Sebastien Dovonon, Jean Kaddour, Ricardo Silva

ICMLW 2024 Attention Is All You Need but You Don’t Need All of It for Inference of Large Language Models Georgy Tyukin, Gbetondji Jean-Sebastien Dovonon, Jean Kaddour, Pasquale Minervini

ICLR 2023 DAG Learning on the Permutahedron Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt Kusner, Vlad Niculae

NeurIPSW 2023 Early Weight Averaging Meets High Learning Rates for LLM Pre-Training Sunny Sanyal, Atula Tejaswi Neerkaje, Jean Kaddour, Abhishek Kumar, Sujay Sanghavi

NeurIPS 2023 Evaluating Self-Supervised Learning for Molecular Graph Embeddings Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

NeurIPSW 2023 Local LoRA: Memory-Efficient Fine-Tuning of Large Language Models Oscar Key, Jean Kaddour, Pasquale Minervini

NeurIPS 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

ICLRW 2022 DAG Learning on the Permutahedron Valentina Zantedeschi, Jean Kaddour, Luca Franceschi, Matt Kusner, Vlad Niculae

ICMLW 2022 Evaluating Self-Supervised Learned Molecular Graphs Hanchen Wang, Shengchao Liu, Jean Kaddour, Qi Liu, Jian Tang, Matt Kusner, Joan Lasenby

ICMLW 2022 Evaluating Self-Supervised Learned Molecular Graphs Hanchen Wang, Shengchao Liu, Jean Kaddour, Qi Liu, Jian Tang, Matt Kusner, Joan Lasenby

NeurIPSW 2022 Evaluating the Impact of Geometric and Statistical Skews on Out-of-Distribution Generalization Performance Aengus Lynch, Jean Kaddour, Ricardo Silva

NeurIPSW 2022 Evaluating the Impact of Geometric and Statistical Skews on Out-of-Distribution Generalization Performance Aengus Lynch, Jean Kaddour, Ricardo Silva

NeurIPSW 2022 Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging Jean Kaddour

NeurIPS 2022 When Do Flat Minima Optimizers Work? Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J Kusner

NeurIPS 2021 Causal Effect Inference for Structured Treatments Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J Kusner, Ricardo Silva

NeurIPS 2020 Probabilistic Active Meta-Learning Jean Kaddour, Steindor Saemundsson, Marc Deisenroth