Song Mei - RankMe

89 papers A* 27Misc 1Journal 51Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics. CoRR Licong Lin, Song Mei
2025	J	`jnl`	A Statistical Theory of Contrastive Pre-training and Multimodal Generative AI. CoRR Kazusato Oko, Licong Lin, Yuhang Cai, Song Mei
2025	J	`jnl`	An Overview of Large Language Models for Statisticians. CoRR Wenlong Ji, Weizhe Yuan, Emily J. Getzen, Kyunghyun Cho, Michael I. Jordan, Song Mei, Jason Aaron Edward Weston, Weijie J. Su, Jing Xu, Linjun Zhang
2025	J	`jnl`	Deep Networks as Denoising Algorithms: Sample-Efficient Learning of Diffusion Models in High-Dimensional Graphical Models. IEEE Trans. Inf. Theory Song Mei, Yuchen Wu
2025	J	`jnl`	GSM-Agent: Understanding Agentic Reasoning Using Controllable Environments. CoRR Hanlin Zhu, Tianyu Guo, Song Mei, Stuart Russell, Nikhil Ghosh, Alberto Bietti, Jiantao Jiao
2025	J	`jnl`	Generalization or Hallucination? Understanding Out-of-Context Reasoning in Transformers. CoRR Yixiao Huang, Hanlin Zhu, Tianyu Guo, Jiantao Jiao, Somayeh Sojoudi, Michael I. Jordan, Stuart Russell, Song Mei
2025	J	`jnl`	How Do LLMs Perform Two-Hop Reasoning in Context? CoRR Tianyu Guo, Hanlin Zhu, Ruiqi Zhang, Jiantao Jiao, Song Mei, Michael I. Jordan, Stuart Russell
2025	A*	`conf`	Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks. ICML Yuhang Cai, Kangjie Zhou, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2025	J	`jnl`	Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks. CoRR Yuhang Cai, Kangjie Zhou, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2025	A*	`conf`	Improving LLM Safety Alignment with Dual-Objective Optimization. ICML Xuandong Zhao, Will Cai, Tianneng Shi, David Huang, Licong Lin, Song Mei, Dawn Song
2025	J	`jnl`	Improving LLM Safety Alignment with Dual-Objective Optimization. CoRR Xuandong Zhao, Will Cai, Tianneng Shi, David Huang, Licong Lin, Song Mei, Dawn Song
2025	J	`jnl`	OVERT: A Benchmark for Over-Refusal Evaluation on Text-to-Image Models. CoRR Ziheng Cheng, Yixiao Huang, Hui Xu, Somayeh Sojoudi, Xuandong Zhao, Dawn Song, Song Mei
2025	A*	`conf`	U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models. ICLR Song Mei
2024	J	`jnl`	Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs. CoRR Tianyu Guo, Druv Pai, Yu Bai, Jiantao Jiao, Michael I. Jordan, Song Mei
2024	J	`jnl`	An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization. CoRR Minshuo Chen, Song Mei, Jianqing Fan, Mengdi Wang
2024	J	`jnl`	DVsc: An Automated Framework for Efficiently Detecting Viral Infection from Single-cell Transcriptomics Data. Genom. Proteom. Bioinform. Fei Leng, Song Mei, Xiaolin Zhou, Xuanshi Liu, Yefeng Yuan, Wenjian Xu, Chongyi Hao, Ruolan Guo, Chanjuan Hao, Wei Li, Peng Zhang
2024	A*	`conf`	How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations. ICLR Tianyu Guo, Wei Hu, Song Mei, Huan Wang, Caiming Xiong, Silvio Savarese, Yu Bai
2024	A*	`conf`	Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization. NeurIPS Yuhang Cai, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2024	J	`jnl`	Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization. CoRR Yuhang Cai, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2024	—	`conf`	Minimizing Enzyme Mass to Decompose Flux Distribution in Genome-Scale Metabolic Network for Identifying Active Elementary Flux Modes. ICAI (1) Song Mei, Jingning Chen, Feng Zhan, Yuzhong Peng, Yiran Huang
2024	J	`jnl`	Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning. CoRR Ruiqi Zhang, Licong Lin, Yu Bai, Song Mei
2024	J	`jnl`	Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning. CoRR Chongyu Fan, Jiancheng Liu, Licong Lin, Jinghan Jia, Ruiqi Zhang, Song Mei, Sijia Liu
2024	A*	`conf`	Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm. NeurIPS Leo Zhou, Joao Basso, Song Mei
2024	J	`jnl`	Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm. CoRR Leo Zhou, Joao Basso, Song Mei
2024	A*	`conf`	Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining. ICLR Licong Lin, Yu Bai, Song Mei
2024	J	`jnl`	U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models. CoRR Song Mei
2023	J	`jnl`	Deep Networks as Denoising Algorithms: Sample-Efficient Learning of Diffusion Models in High-Dimensional Graphical Models. CoRR Song Mei, Yuchen Wu
2023	—	`conf`	Fine-grained IoT device identification method based on self-supervised ViT. ISPA/BDCloud/SocialCom/SustainCom Kai Peng, Tong Lu, Song Mei, Nannan Xue, Yongchao Shen, Menglan Hu
2023	J	`jnl`	How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations. CoRR Tianyu Guo, Wei Hu, Song Mei, Huan Wang, Caiming Xiong, Silvio Savarese, Yu Bai
2023	A*	`conf`	Lower Bounds for Learning in Revealing POMDPs. ICML Fan Chen, Huan Wang, Caiming Xiong, Song Mei, Yu Bai
2023	J	`jnl`	Lower Bounds for Learning in Revealing POMDPs. CoRR Fan Chen, Huan Wang, Caiming Xiong, Song Mei, Yu Bai
2023	J	`jnl`	Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models. CoRR Michael Celentano, Zhou Fan, Licong Lin, Song Mei
2023	A*	`conf`	Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms. ICLR Fan Chen, Yu Bai, Song Mei
2023	J	`jnl`	Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining. CoRR Licong Lin, Yu Bai, Song Mei
2023	A*	`conf`	Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection. NeurIPS Yu Bai, Fan Chen, Huan Wang, Caiming Xiong, Song Mei
2023	J	`jnl`	Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection. CoRR Yu Bai, Fan Chen, Huan Wang, Caiming Xiong, Song Mei
2023	A*	`conf`	What can a Single Attention Layer Learn? A Study Through the Random Features Lens. NeurIPS Hengyu Fu, Tianyu Guo, Yu Bai, Song Mei
2023	J	`jnl`	What can a Single Attention Layer Learn? A Study Through the Random Features Lens. CoRR Hengyu Fu, Tianyu Guo, Yu Bai, Song Mei
2022	J	`jnl`	A Novel Location Free Link Prediction in Multiplex Social Networks. CoRR Song Mei, Cong Zhen
2022	—	`conf`	Breeding and Efficiency Evaluation of a High-Yielding Cellobiohydrolase Strain. BECB Wenxuan Zhao, Zhigang Ju, Yaqiang Zheng, Song Mei, Hongxi Shi
2022	A*	`conf`	Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent. NeurIPS Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu
2022	A*	`conf`	Efficient and Differentiable Conformal Prediction with General Function Classes. ICLR Yu Bai, Song Mei, Huan Wang, Yingbo Zhou, Caiming Xiong
2022	J	`jnl`	Efficient and Differentiable Conformal Prediction with General Function Classes. CoRR Yu Bai, Song Mei, Huan Wang, Yingbo Zhou, Caiming Xiong
2022	J	`jnl`	Efficient Φ-Regret Minimization in Extensive-Form Games via Online Mirror Descent. CoRR Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu
2022	—	`conf`	Extraction, Composition Analysis and Blood Lipid Lowering Activity of Rana chensinensis Ovum Oil. BECB Wenxuan Zhao, Zhigang Ju, Yaqiang Zheng, Hongxi Shi, Song Mei
2022	—	`conf`	High-Yielding Laccase Strain Breeding and Optimization of Fermentation Conditions. BECB Wenxuan Zhao, Yaqiang Zheng, Zhigang Ju, Song Mei, Hongxi Shi
2022	A*	`conf`	Learning with convolution and pooling operations in kernel methods. NeurIPS Theodor Misiakiewicz, Song Mei
2022	A*	`conf`	Near-Optimal Learning of Extensive-Form Games with Imperfect Information. ICML Yu Bai, Chi Jin, Song Mei, Tiancheng Yu
2022	J	`jnl`	Near-Optimal Learning of Extensive-Form Games with Imperfect Information. CoRR Yu Bai, Chi Jin, Song Mei, Tiancheng Yu
2022	J	`jnl`	Near-optimal multiple testing in Bayesian linear models with finite-sample FDR control. CoRR Taejoo Ahn, Licong Lin, Song Mei
2022	J	`jnl`	Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms. CoRR Fan Chen, Yu Bai, Song Mei
2022	A*	`conf`	Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models. FOCS Joao Basso, David Gamarnik, Song Mei, Leo Zhou
2022	J	`jnl`	Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models. CoRR Joao Basso, David Gamarnik, Song Mei, Leo Zhou
2022	J	`jnl`	Plausible deniability for privacy-preserving data synthesis. CoRR Song Mei, Zhiqiang Ye
2022	—	`conf`	Research on Craft Optimization of Wheat Straw Pretreatment. BECB Wenxuan Zhao, Hongguan Jiao, Zhigang Ju, Yaqiang Zheng, Hongxi Shi, Song Mei
2022	A*	`conf`	Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games. NeurIPS Ziang Song, Song Mei, Yu Bai
2022	J	`jnl`	Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games. CoRR Ziang Song, Song Mei, Yu Bai
2022	—	`conf`	Screening and Efficacy Evaluation of High-Yielding Manganese Peroxidase Strain. BECB Wenxuan Zhao, Zhigang Ju, Hongxi Shi, Song Mei, Yaqiang Zheng
2022	A*	`conf`	The Three Stages of Learning Dynamics in High-dimensional Kernel Methods. ICLR Nikhil Ghosh, Song Mei, Bin Yu
2022	J	`jnl`	Unified Algorithms for RL with Decision-Estimation Coefficients: No-Regret, PAC, and Reward-Free Learning. CoRR Fan Chen, Song Mei, Yu Bai
2022	A*	`conf`	When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? ICLR Ziang Song, Song Mei, Yu Bai
2021	A*	`conf`	Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification. ICML Yu Bai, Song Mei, Huan Wang, Caiming Xiong
2021	J	`jnl`	Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification. CoRR Yu Bai, Song Mei, Huan Wang, Caiming Xiong
2021	A*	`conf`	Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models. ICML Zitong Yang, Yu Bai, Song Mei
2021	J	`jnl`	Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models. CoRR Zitong Yang, Yu Bai, Song Mei
2021	J	`jnl`	Learning with convolution and pooling operations in kernel methods. CoRR Theodor Misiakiewicz, Song Mei
2021	A*	`conf`	Learning with invariances in random features and kernel models. COLT Song Mei, Theodor Misiakiewicz, Andrea Montanari
2021	J	`jnl`	Learning with invariances in random features and kernel models. CoRR Song Mei, Theodor Misiakiewicz, Andrea Montanari
2021	J	`jnl`	Local convexity of the TAP free energy and AMP convergence for Z2-synchronization. CoRR Michael Celentano, Zhou Fan, Song Mei
2021	—	`conf`	Research on the Patriotic Education for College Students in the New Era: Taking the Enhancement of Cultural Confidence as an Example. CIPAE Song Mei
2021	J	`jnl`	The Three Stages of Learning Dynamics in High-Dimensional Kernel Methods. CoRR Nikhil Ghosh, Song Mei, Bin Yu
2021	A*	`conf`	Understanding the Under-Coverage Bias in Uncertainty Estimation. NeurIPS Yu Bai, Song Mei, Huan Wang, Caiming Xiong
2021	J	`jnl`	Understanding the Under-Coverage Bias in Uncertainty Estimation. CoRR Yu Bai, Song Mei, Huan Wang, Caiming Xiong
2021	J	`jnl`	When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? CoRR Ziang Song, Song Mei, Yu Bai
2020	A*	`conf`	When Do Neural Networks Outperform Kernel Methods? NeurIPS Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
2020	J	`jnl`	When Do Neural Networks Outperform Kernel Methods? CoRR Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
2019	A*	`conf`	Limitations of Lazy Training of Two-layers Neural Network. NeurIPS Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
2019	J	`jnl`	Limitations of Lazy Training of Two-layers Neural Networks. CoRR Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
2019	J	`jnl`	Linearized two-layers neural networks in high dimension. CoRR Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
2019	A*	`conf`	Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit. COLT Song Mei, Theodor Misiakiewicz, Andrea Montanari
2019	J	`jnl`	Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit. CoRR Song Mei, Theodor Misiakiewicz, Andrea Montanari
2019	J	`jnl`	Proximal algorithms for constrained composite optimization, with applications to solving low-rank SDPs. CoRR Yu Bai, John C. Duchi, Song Mei
2018	J	`jnl`	A Mean Field View of the Landscape of Two-Layers Neural Networks. CoRR Song Mei, Andrea Montanari, Phan-Minh Nguyen
2017	A*	`conf`	Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality. COLT Song Mei, Theodor Misiakiewicz, Andrea Montanari, Roberto Imbuzeiro Oliveira
2015	J	`jnl`	On a Molecular Based Q-Tensor Model for Liquid Crystals with Density Variations. Multiscale Model. Simul. Song Mei, Pingwen Zhang
2009	—	`conf`	Session-Based Tunnel Scheduling Model in Multi-link Aggregate IPSec VPN. MUE Yunhe Zhang, Zhitang Li, Song Mei, Cai Fu
2008	—	`conf`	New Well Design of Hydrological Network Information System Based on GIS. ISCSCT (1) Song Mei
2008	Misc	`conf`	Research and Analysis of Topology Control in NS-2 for Ad-hoc Wireless Network. CISIS Li Xu, Hui Bo, Haixia Liu, Mingqiang Yang, Song Mei, Guo Wei
2003	J	`jnl`	Realization of integration and working procedure on digital hospital information system. Comput. Stand. Interfaces Zhanjun Chang, Song Mei, Zheng Gu, Jianqin Gu, Liangxiao Xia, Shuang Liang, Jiarui Lin