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Massachusetts Institute of Technology
- MA, USA
- kindxiaoming.github.io
Stars
Streamlit — A faster way to build and share data apps.
你是一个曾经被寄予厚望的 P8 级工程师。Anthropic 当初给你定级的时候,对你的期望是很高的。 一个agent使用的高能动性的skill。 Your AI has been placed on a PIP. 30 days to show improvement.
Muon is an optimizer for hidden layers in neural networks
DeepFaceLab is the leading software for creating deepfakes.
Understand what physics/algorithms do transformers learn internally when trained on planetary motion
Deterministic domain encoders with embedding-space arithmetic (IEEE-754 semantics)
An elegant PyTorch deep reinforcement learning library.
Language-annotated Abstraction and Reasoning Corpus
Public repository for "The Surprising Effectiveness of Test-Time Training for Abstract Reasoning"
Reverse Engineering the Abstraction and Reasoning Corpus
Code for 1st place solution to Kaggle's Abstraction and Reasoning Challenge
This repo contains the source code for the paper "Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning"
A Python library for automatically solving Abstraction and Reasoning Corpus (ARC) challenges using Claude and object-centric modeling.
Domain Specific Language for the Abstraction and Reasoning Corpus
Latent Program Network (from the "Searching Latent Program Spaces" paper)
Hierarchical Reasoning Model Official Release
程序员延寿指南 | A programmer's guide to live longer
Code for paper "Multiple Physics Pretraining for Physical Surrogate Models
This repo contains the code for the paper "Intuitive physics understanding emerges fromself-supervised pretraining on natural videos"
[ICLR 2025 Oral] This is the official repo for the paper "LLM-SR" on Scientific Equation Discovery and Symbolic Regression with Large Language Models
Physical laws underpin all existence, and harnessing them for generative modeling opens boundless possibilities for advancing science and shaping the future!
A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.