Jean Kaddour - RankMe

29 papers A* 7Journal 20Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Agentic Uncertainty Reveals Agentic Overconfidence. CoRR Jean Kaddour, Srijan Patel, Gbètondji J.-S. Dovonon, Leo Richter, Pasquale Minervini, Matt J. Kusner
2025	—	`conf`	Are We Done with MMLU? NAACL (Long Papers) 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
2025	A*	`conf`	BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions. ICLR 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.
2025	J	`jnl`	Causal Machine Learning: A Survey and Open Problems. Found. Trends Optim. Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva
2025	J	`jnl`	REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards. CoRR Zafir Stojanovski, Oliver Stanley, Joe Sharratt, Richard Jones, Abdulhakeem Adefioye, Jean Kaddour, Andreas Köpf
2024	J	`jnl`	Are We Done with MMLU? CoRR 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
2024	J	`jnl`	Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models. CoRR Georgy Tyukin, Gbètondji J.-S. Dovonon, Jean Kaddour, Pasquale Minervini
2024	J	`jnl`	BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions. CoRR 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
2023	J	`jnl`	Challenges and Applications of Large Language Models. CoRR Jean Kaddour, Joshua Harris, Maximilian Mozes, Herbie Bradley, Roberta Raileanu, Robert McHardy
2023	A*	`conf`	DAG Learning on the Permutahedron. ICLR Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt J. Kusner, Vlad Niculae
2023	J	`jnl`	DAG Learning on the Permutahedron. CoRR Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt J. Kusner, Vlad Niculae
2023	A*	`conf`	Evaluating Self-Supervised Learning for Molecular Graph Embeddings. NeurIPS Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu
2023	A*	`conf`	No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. NeurIPS Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner
2023	J	`jnl`	No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. CoRR Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner
2023	J	`jnl`	Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases. CoRR Aengus Lynch, Gbètondji J.-S. Dovonon, Jean Kaddour, Ricardo Silva
2023	J	`jnl`	TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models. CoRR Yuwei Yin, Jean Kaddour, Xiang Zhang, Yixin Nie, Zhenguang Liu, Lingpeng Kong, Qi Liu
2023	J	`jnl`	Text Data Augmentation in Low-Resource Settings via Fine-Tuning of Large Language Models. CoRR Jean Kaddour, Qi Liu
2023	J	`jnl`	The MiniPile Challenge for Data-Efficient Language Models. CoRR Jean Kaddour
2023	J	`jnl`	Understanding the Effectiveness of Early Weight Averaging for Training Large Language Models. CoRR Sunny Sanyal, Jean Kaddour, Abhishek Kumar, Sujay Sanghavi
2022	J	`jnl`	Causal Machine Learning: A Survey and Open Problems. CoRR Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva
2022	J	`jnl`	Evaluating Self-Supervised Learning for Molecular Graph Embeddings. CoRR Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Matt J. Kusner, Joan Lasenby, Qi Liu
2022	J	`jnl`	Questions for Flat-Minima Optimization of Modern Neural Networks. CoRR Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J. Kusner
2022	J	`jnl`	Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging. CoRR Jean Kaddour
2022	A*	`conf`	When Do Flat Minima Optimizers Work? NeurIPS Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J. Kusner
2021	A*	`conf`	Causal Effect Inference for Structured Treatments. NeurIPS Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J. Kusner, Ricardo Silva
2021	J	`jnl`	Graph Intervention Networks for Causal Effect Estimation. CoRR Jean Kaddour, Qi Liu, Yuchen Zhu, Matt J. Kusner, Ricardo Silva
2020	A*	`conf`	Probabilistic Active Meta-Learning. NeurIPS Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth
2020	J	`jnl`	Probabilistic Active Meta-Learning. CoRR Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth
2018	—	`conf`	SATISFy: Towards a Self-Learning Analyzer for Time Series Forecasting in Self-Improving Systems. FAS*W@SASO/ICAC Christian Krupitzer, Martin Pfannemüller, Jean Kaddour, Christian Becker