Nan Ding - RankMe

57 papers A* 9A 1B 3Misc 1Journal 26Unranked 16

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Graders Should Cheat: Privileged Information Enables Expert-Level Automated Evaluations. EMNLP Jin Peng Zhou, Sébastien M. R. Arnold, Nan Ding, Kilian Q. Weinberger, Nan Hua, Fei Sha
2025	J	`jnl`	Graders should cheat: privileged information enables expert-level automated evaluations. CoRR Jin Peng Zhou, Sébastien M. R. Arnold, Nan Ding, Kilian Q. Weinberger, Nan Hua, Fei Sha
2024	A*	`conf`	CausalLM is not optimal for in-context learning. ICLR Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut
2023	J	`jnl`	CausalLM is not optimal for in-context learning. CoRR Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut
2023	A*	`conf`	Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization. CVPR Zifan Wang, Nan Ding, Tomer Levinboim, Xi Chen, Radu Soricut
2023	A*	`conf`	PaLI: A Jointly-Scaled Multilingual Language-Image Model. ICLR Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo
2022	—	`conf`	All You May Need for VQA are Image Captions. NAACL-HLT Soravit Changpinyo, Doron Kukliansky, Idan Szpektor, Xi Chen, Nan Ding, Radu Soricut
2022	J	`jnl`	All You May Need for VQA are Image Captions. CoRR Soravit Changpinyo, Doron Kukliansky, Idan Szpektor, Xi Chen, Nan Ding, Radu Soricut
2022	J	`jnl`	Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization. CoRR Zifan Wang, Nan Ding, Tomer Levinboim, Xi Chen, Radu Soricut
2022	—	`conf`	PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks. ECCV (34) Nan Ding, Xi Chen, Tomer Levinboim, Soravit Changpinyo, Radu Soricut
2022	J	`jnl`	PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks. CoRR Nan Ding, Xi Chen, Tomer Levinboim, Beer Changpinyo, Radu Soricut
2022	J	`jnl`	PaLI: A Jointly-Scaled Multilingual Language-Image Model. CoRR Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
2021	A*	`conf`	Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning. NeurIPS Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut
2021	J	`jnl`	Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning. CoRR Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut
2021	A*	`conf`	Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts. CVPR Soravit Changpinyo, Piyush Sharma, Nan Ding, Radu Soricut
2021	J	`jnl`	Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts. CoRR Soravit Changpinyo, Piyush Sharma, Nan Ding, Radu Soricut
2021	—	`conf`	Do Transformer Modifications Transfer Across Implementations and Applications? EMNLP (1) Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel
2021	J	`jnl`	Do Transformer Modifications Transfer Across Implementations and Applications? CoRR Sharan Narang, Hyung Won Chung, Yi Tay, William Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel
2020	J	`jnl`	Attention that does not Explain Away. CoRR Nan Ding, Xinjie Fan, Zhenzhong Lan, Dale Schuurmans, Radu Soricut
2020	—	`conf`	Improving Text Generation Evaluation with Batch Centering and Tempered Word Mover Distance. Eval4NLP Xi Chen, Nan Ding, Tomer Levinboim, Radu Soricut
2020	J	`jnl`	Improving Text Generation Evaluation with Batch Centering and Tempered Word Mover Distance. CoRR Xi Chen, Nan Ding, Tomer Levinboim, Radu Soricut
2020	J	`jnl`	Talking-Heads Attention. CoRR Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou
2020	—	`conf`	TeaForN: Teacher-Forcing with N-grams. EMNLP (1) Sebastian Goodman, Nan Ding, Radu Soricut
2020	J	`jnl`	TeaForN: Teacher-Forcing with N-grams. CoRR Sebastian Goodman, Nan Ding, Radu Soricut
2018	—	`conf`	Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning. ACL (1) Piyush Sharma, Nan Ding, Sebastian Goodman, Radu Soricut
2018	—	`conf`	SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation. NAACL-HLT Ye Zhang, Nan Ding, Radu Soricut
2018	J	`jnl`	SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation. CoRR Ye Zhang, Nan Ding, Radu Soricut
2017	—	`conf`	Cold-Start Reinforcement Learning with Softmax Policy Gradient. NIPS Nan Ding, Radu Soricut
2017	J	`jnl`	Cold-Start Reinforcement Learning with Softmax Policy Gradients. CoRR Nan Ding, Radu Soricut
2016	J	`jnl`	Building Large Machine Reading-Comprehension Datasets using Paragraph Vectors. CoRR Radu Soricut, Nan Ding
2016	J	`jnl`	Multilingual Word Embeddings using Multigraphs. CoRR Radu Soricut, Nan Ding
2016	—	`conf`	Stochastic Gradient MCMC with Stale Gradients. NIPS Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin
2016	J	`jnl`	Stochastic Gradient MCMC with Stale Gradients. CoRR Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin
2016	J	`jnl`	Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task. CoRR Nan Ding, Sebastian Goodman, Fei Sha, Radu Soricut
2015	J	`jnl`	Differential Topic Models. IEEE Trans. Pattern Anal. Mach. Intell. Changyou Chen, Wray L. Buntine, Nan Ding, Lexing Xie, Lan Du
2015	—	`conf`	Embedding Inference for Structured Multilabel Prediction. NIPS Farzaneh Mirzazadeh, Siamak Ravanbakhsh, Nan Ding, Dale Schuurmans
2015	—	`conf`	On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators. NIPS Changyou Chen, Nan Ding, Lawrence Carin
2015	A*	`conf`	Probabilistic Label Relation Graphs with Ising Models. ICCV Nan Ding, Jia Deng, Kevin P. Murphy, Hartmut Neven
2015	J	`jnl`	Probabilistic Label Relation Graphs with Ising Models. CoRR Nan Ding, Jia Deng, Kevin Murphy, Hartmut Neven
2015	J	`jnl`	Totally Corrective Boosting with Cardinality Penalization. CoRR Vasil S. Denchev, Nan Ding, Shin Matsushima, S. V. N. Vishwanathan, Hartmut Neven
2014	—	`conf`	Bayesian Sampling Using Stochastic Gradient Thermostats. NIPS Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert D. Skeel, Hartmut Neven
2014	J	`jnl`	Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing. CoRR Ryan Babbush, Vasil S. Denchev, Nan Ding, Sergei Isakov, Hartmut Neven
2014	—	`conf`	Large-Scale Object Classification Using Label Relation Graphs. ECCV (1) Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, Hartwig Adam
2012	J	`jnl`	Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling CoRR Changyou Chen, Nan Ding, Wray L. Buntine
2012	A*	`conf`	Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling. ICML Changyou Chen, Nan Ding, Wray L. Buntine
2012	A*	`conf`	Robust Classification with Adiabatic Quantum Optimization. ICML Vasil S. Denchev, Nan Ding, S. V. N. Vishwanathan, Hartmut Neven
2012	J	`jnl`	Theory of Dependent Hierarchical Normalized Random Measures CoRR Changyou Chen, Wray L. Buntine, Nan Ding
2011	—	`conf`	t-divergence Based Approximate Inference. NIPS Nan Ding, S. V. N. Vishwanathan, Yuan (Alan) Qi
2010	A	`conf`	Nonparametric Bayesian Matrix Factorization by Power-EP. AISTATS Nan Ding, Yuan (Alan) Qi, Rongjing Xiang, Ian M. Molloy, Ninghui Li
2010	Misc	`conf`	Variational nonparametric Bayesian Hidden Markov Model. ICASSP Nan Ding, Zhijian Ou
2010	—	`conf`	t-logistic regression. NIPS Nan Ding, S. V. N. Vishwanathan
2008	B	`conf`	A Bayesian view on the polynomial distribution model in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation Nan Ding, Shude Zhou, Ji Xu, Zengqi Sun
2008	J	`jnl`	Histogram-Based Estimation of Distribution Algorithm: A Competent Method for Continuous Optimization. J. Comput. Sci. Technol. Nan Ding, Shude Zhou, Zengqi Sun
2008	—	`ch.`	Linkages Detection in Histogram-Based Estimation of Distribution Algorithm. Linkage in Evolutionary Computation Nan Ding, Shude Zhou
2008	B	`conf`	Marginal probability distribution estimation in characteristic space of covariance-matrix. IEEE Congress on Evolutionary Computation Nan Ding, Shude Zhou, Hao Zhang, Zengqi Sun
2007	B	`conf`	Reducing computational complexity of estimating multivariate histogram-based probabilistic model. IEEE Congress on Evolutionary Computation Nan Ding, Ji Xu, Shude Zhou, Zengqi Sun
2006	—	`conf`	Optimizing Continuous Problems Using Estimation of Distribution Algorithm Based on Histogram Model. SEAL Nan Ding, Shude Zhou, Zengqi Sun