Zhenmei Shi
Orcid: 0009-0007-6741-7598
According to our database1,
Zhenmei Shi
authored at least 38 papers
between 2019 and 2024.
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Bibliography
2024
Theoretical Constraints on the Expressive Power of RoPE-based Tensor Attention Transformers.
CoRR, 2024
The Computational Limits of State-Space Models and Mamba via the Lens of Circuit Complexity.
CoRR, 2024
Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond.
CoRR, 2024
Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study.
CoRR, 2024
Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction.
CoRR, 2024
CoRR, 2024
Do Large Language Models Have Compositional Ability? An Investigation into Limitations and Scalability.
CoRR, 2024
Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models.
CoRR, 2024
Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective.
CoRR, 2024
CoRR, 2024
Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers.
CoRR, 2024
Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond.
CoRR, 2024
Fourier Circuits in Neural Networks: Unlocking the Potential of Large Language Models in Mathematical Reasoning and Modular Arithmetic.
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis.
Proceedings of the International Conference on Machine Learning, 2023
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features.
Proceedings of the Tenth International Conference on Learning Representations, 2022
2019
CoRR, 2019
CoRR, 2019