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Papers
Language Generation in the Limit
NeurIPS 2024
Learnability of high-dimensional targets by two-parameter models and gradient flow
NeurIPS 2024
Model Collapse Demystified: The Case of Regression
NeurIPS 2024
On the Ability of Developers' Training Data Preservation of Learnware
NeurIPS 2024
On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective
AISTATS 2024
On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning
ACL 2024
Provable and Efficient Dataset Distillation for Kernel Ridge Regression
NeurIPS 2024
Quality-Diversity Algorithms Can Provably Be Helpful for Optimization
IJCAI 2024
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
ICML 2024
The Fine-Grained Complexity of Gradient Computation for Training Large Language Models
NeurIPS 2024
The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems
NeurIPS 2024
Toward Availability Attacks in 3D Point Clouds
ICML 2024
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling
NeurIPS 2024
Understanding Transformer Reasoning Capabilities via Graph Algorithms
NeurIPS 2024
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
NeurIPS 2024
What does guidance do? A fine-grained analysis in a simple setting
NeurIPS 2024
When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations
ICLR 2024
Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels
ICML 2023
A Proof That Using Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation
AAAI 2023
A Provable Framework of Learning Graph Embeddings via Summarization
AAAI 2023
Defining a New NLP Playground
EMNLP 2023
Effects of Graph Convolutions in Multi-layer Networks
ICLR 2023
Explaining Reinforcement Learning with Shapley Values
ICML 2023
FLatS: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score
EMNLP 2023
On the Expressive Flexibility of Self-Attention Matrices
AAAI 2023