Yiding Jiang - RankMe

43 papers A* 14B 1Journal 25Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence. CoRR Marc Finzi, Shikai Qiu, Yiding Jiang, Pavel Izmailov, J. Zico Kolter, Andrew Gordon Wilson
2026	J	`jnl`	Maximum Likelihood Reinforcement Learning. CoRR Fahim Tajwar, Guanning Zeng, Yueer Zhou, Yuda Song, Daman Arora, Yiding Jiang, Jeff G. Schneider, Ruslan Salakhutdinov, Haiwen Feng, Andrea Zanette
2025	A*	`conf`	Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws. ICLR Yiding Jiang, Allan Zhou, Zhili Feng, Sadhika Malladi, J. Zico Kolter
2025	J	`jnl`	Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. Trans. Mach. Learn. Res. Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Nathaniel Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J. Zico Kolter
2025	J	`jnl`	Learning Parameterized Skills from Demonstrations. CoRR Vedant Gupta, Haotian Fu, Calvin Luo, Yiding Jiang, George Konidaris
2025	J	`jnl`	Looking beyond the next token. CoRR Abitha Thankaraj, Yiding Jiang, J. Zico Kolter, Yonatan Bisk
2025	J	`jnl`	Safety Pretraining: Toward the Next Generation of Safe AI. CoRR Pratyush Maini, Sachin Goyal, Dylan Sam, Alexander Robey, Yash Savani, Yiding Jiang, Andy Zou, Zacharcy C. Lipton, J. Zico Kolter
2025	A*	`conf`	Training a Generally Curious Agent. ICML Fahim Tajwar, Yiding Jiang, Abitha Thankaraj, Sumaita Sadia Rahman, J. Zico Kolter, Jeff Schneider, Russ Salakhutdinov
2025	J	`jnl`	Training a Generally Curious Agent. CoRR Fahim Tajwar, Yiding Jiang, Abitha Thankaraj, Sumaita Sadia Rahman, J. Zico Kolter, Jeff Schneider, Ruslan Salakhutdinov
2024	J	`jnl`	Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws. CoRR Yiding Jiang, Allan Zhou, Zhili Feng, Sadhika Malladi, J. Zico Kolter
2024	J	`jnl`	Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. CoRR Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J. Zico Kolter
2024	J	`jnl`	Improving Generalization on the ProcGen Benchmark with Simple Architectural Changes and Scale. CoRR Andrew Jesson, Yiding Jiang
2024	A*	`conf`	On the Joint Interaction of Models, Data, and Features. ICLR Yiding Jiang, Christina Baek, J. Zico Kolter
2024	A*	`conf`	Understanding prompt engineering may not require rethinking generalization. ICLR Victor Akinwande, Yiding Jiang, Dylan Sam, J. Zico Kolter
2023	B	`conf`	A Wavelet Decomposition Network Based Edge Monitoring System for Classification of Electrical Equipment. SMC Xianchen Wang, Di Cao, Yiding Jiang, Yanjing Lei, Linghao Ying
2023	A*	`conf`	Language Models are Weak Learners. NeurIPS Hariharan Manikandan, Yiding Jiang, J. Zico Kolter
2023	J	`jnl`	Language models are weak learners. CoRR Hariharan Manikandan, Yiding Jiang, J. Zico Kolter
2023	A*	`conf`	Neural Functional Transformers. NeurIPS Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn
2023	J	`jnl`	Neural Functional Transformers. CoRR Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn
2023	A*	`conf`	On the Importance of Exploration for Generalization in Reinforcement Learning. NeurIPS Yiding Jiang, J. Zico Kolter, Roberta Raileanu
2023	J	`jnl`	On the Importance of Exploration for Generalization in Reinforcement Learning. CoRR Yiding Jiang, J. Zico Kolter, Roberta Raileanu
2023	J	`jnl`	On the Joint Interaction of Models, Data, and Features. CoRR Yiding Jiang, Christina Baek, J. Zico Kolter
2023	A*	`conf`	Permutation Equivariant Neural Functionals. NeurIPS Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn
2023	J	`jnl`	Permutation Equivariant Neural Functionals. CoRR Allan Zhou, Kaien Yang, Kaylee Burns, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn
2023	J	`jnl`	Understanding prompt engineering may not require rethinking generalization. CoRR Victor Akinwande, Yiding Jiang, Dylan Sam, J. Zico Kolter
2022	J	`jnl`	Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift. CoRR Christina Baek, Yiding Jiang, Aditi Raghunathan, Zico Kolter
2022	A*	`conf`	Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift. NeurIPS Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter
2022	A*	`conf`	Assessing Generalization of SGD via Disagreement. ICLR Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
2022	A*	`conf`	Learning Options via Compression. NeurIPS Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn
2022	J	`jnl`	Learning Options via Compression. CoRR Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, Zico Kolter, Chelsea Finn
2021	J	`jnl`	Ask & Explore: Grounded Question Answering for Curiosity-Driven Exploration. CoRR Jivat Neet Kaur, Yiding Jiang, Paul Pu Liang
2021	J	`jnl`	Assessing Generalization of SGD via Disagreement. CoRR Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
2020	A*	`conf`	Fantastic Generalization Measures and Where to Find Them. ICLR Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio
2020	—	`conf`	Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning. NeurIPS (Competition and Demos) Yiding Jiang, Parth Natekar, Manik Sharma, Sumukh K. Aithal, Dhruva Kashyap, Natarajan Subramanyam, Carlos Lassance, Daniel M. Roy, Gintare Karolina Dziugaite, Suriya Gunasekar, Isabelle Guyon, Pierre Foret, Scott Yak, Hossein Mobahi, Behnam Neyshabur, Samy Bengio
2020	J	`jnl`	NeurIPS 2020 Competition: Predicting Generalization in Deep Learning. CoRR Yiding Jiang, Pierre Foret, Scott Yak, Daniel M. Roy, Hossein Mobahi, Gintare Karolina Dziugaite, Samy Bengio, Suriya Gunasekar, Isabelle Guyon, Behnam Neyshabur
2020	A*	`conf`	Observational Overfitting in Reinforcement Learning. ICLR Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur
2019	—	`conf`	Adversarial Grasp Objects. CASE David Wang, David Tseng, Pusong Li, Yiding Jiang, Menglong Guo, Michael Danielczuk, Jeffrey Mahler, Jeffrey Ichnowski, Ken Goldberg
2019	J	`jnl`	Fantastic Generalization Measures and Where to Find Them. CoRR Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio
2019	A*	`conf`	Language as an Abstraction for Hierarchical Deep Reinforcement Learning. NeurIPS Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn
2019	J	`jnl`	Language as an Abstraction for Hierarchical Deep Reinforcement Learning. CoRR Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn
2019	J	`jnl`	Observational Overfitting in Reinforcement Learning. CoRR Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur
2019	—	`conf`	Predicting the Generalization Gap in Deep Networks with Margin Distributions. ICLR (Poster) Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio
2018	J	`jnl`	Predicting the Generalization Gap in Deep Networks with Margin Distributions. CoRR Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio