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Theory

4950 directly classified papers

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Papers

SURE: SUrvey REcipes for building reliable and robust deep networks CVPR 2024
Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models ACL 2024
Language Models Do Hard Arithmetic Tasks Easily and Hardly Do Easy Arithmetic Tasks ACL 2024
The Value of Reward Lookahead in Reinforcement Learning NIPS 2024
Selectively Answering Visual Questions ACL 2024
A Meta-Learning Perspective on Transformers for Causal Language Modeling ACL 2024
On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective AISTATS 2024
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces NIPS 2024
Length independent PAC-Bayes bounds for Simple RNNs AISTATS 2024
Grounding and Enhancing Grid-based Models for Neural Fields CVPR 2024
Beyond Probabilities: Unveiling the Misalignment in Evaluating Large Language Models ACL 2024
Analyzing Generalization in Policy Networks: A Case Study with the Double-Integrator System AAAI 2024
Any-dimensional equivariant neural networks AISTATS 2024
Foundations of Reactive Synthesis for Declarative Process Specifications AAAI 2024
Policy Aggregation NIPS 2024
Analysis of Kernel Mirror Prox for Measure Optimization AISTATS 2024
Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness AAAI 2024
Robust Uncertainty Quantification Using Conformalised Monte Carlo Prediction AAAI 2024
FINDINGS OF THE IWSLT 2024 EVALUATION CAMPAIGN ACL 2024
Grokking phase transitions in learning local rules with gradient descent JMLR 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers AISTATS 2024
The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis JMLR 2024
Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization NIPS 2024
Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK JMLR 2024
Double-Descent Curves in Neural Networks: A New Perspective Using Gaussian Processes AAAI 2024