切问录

06-26

Theory Proofs for Aaronson's LLM Water Mark Method

09-03

Median of Means Method: A Robust Approach to Estimating the Mean

09-02

Overcoming the Dimensionality Problem with Monte Carlo Integration

04-03

Harnessing the Power of C++ STL in Python with CSTL

11-28

SAM -- Identifying the Most Significant Parameters for Fine-Tuning

11-24

Sparse Fine-tuned Model -- An Unified View of Parameter-Efficient Models

03-16

Unraveling Implicit Gradient Regularization in Deep Learning

08-23

Copy Bib from Google Scholar with Only One Click

06-12

Changing the Background Color for VSCode PDF Reviewer

06-06

From Classical Mechanics to Hamiltonian Mechanics