Meta Research

Meta Research

@facebookresearchOpen source projects from facebookresearch

Updated: 2026-04-01(11d ago)GitHub API fallback30 repositories

Portfolio Shape

64%

of the visible star count comes from this organization's top three repositories.

Average Repository Size

250

stars per repository in this same snapshot.

Current Mix

Python

is the most common language here, with 30 repositories updated in the last 90 days.

Why this rank

This organization stands out because its public portfolio is relatively balanced across 30 repositories.

Balanced portfolio across 30 reposTop 3 share 64%

Organization pages work best when you separate portfolio breadth from flagship concentration. In Meta Research's case, the visible top three repositories account for about 64% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.

The dominant language mix here is Python (25), Jupyter Notebook (3), HTML (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.

Source: GitHub API fallback. This is the same cache-first snapshot used by the organization ranking list, so the summary view and the detail view should stay aligned.

Top Repositories

#RepositoryLanguage⭐ Stars
1facebookresearch/HyperAgents

Self-referential self-improving agents that can optimize for any computable task

Python2.2K
2facebookresearch/tribev2

This repository contains the code to train and evaluate TRIBE v2, a multimodal model for brain response prediction

Jupyter Notebook1.8K
3facebookresearch/ShapeR

Code for the ShapeR research paper

Python750
4facebookresearch/EUPE

Efficient Universal Perception Encoder: a single on-device vision encoder with versatile representations that match or exceed specialized experts across multiple task domains.

Python471
5facebookresearch/Action100M

A Large-scale Video Action Dataset

Python445
6facebookresearch/actionmesh

🎬ActionMesh: A fast video to animated mesh model with unprecedented quality. Generate animated mesh seamlessly importable into any 3D software in less than a minute.

Python328
7facebookresearch/boxer

Code for the Boxer research paper

Python324
8facebookresearch/ai4animationpy

A Python framework for AI-driven character animation using neural networks.

Python308
9facebookresearch/lagernvs

Official code for "LagerNVS Latent Geometry for Fully Neural Real-time Novel View Synthesis" (CVPR 2026)

Python290
10facebookresearch/tensor-layouts

A pure-Python implementation of the Nvidia CuTe layout algebra intended to be approachable and easy to learn.

Python164
11facebookresearch/repoprover

Research code base for Automatic Textbook Formalization

Python128
12facebookresearch/airs-bench

AIRS-Bench: an AI Research Science benchmark for quantifying the end-to-end AI research abilities of LLM agents

Python77
13facebookresearch/dexwm

Official code and data from DexWM ("World Models Can Leverage Human Videos for Dexterous Manipulation").

Python39
14facebookresearch/sphere-encoder

PyTorch Implementation of Image Generation with a Sphere Encoder

Python32
15facebookresearch/egagent

Code for "Agentic Very Long Video Understanding" (EGAgent) [ACL 2026 Main]

Python29
16facebookresearch/lst

Code for Latent Speech-Text Transformer (LST)

Python14
17facebookresearch/algebraic-combinatorics

Automatic textbook formalization of Grinberg Algebraic Combinatorics

HTML10
18facebookresearch/reasoning-memory

Procedural Knowledge at Scale Improves ReasoningThis repository contains the minimal, end-to-end pipeline for reproducing the paper results generate a procedural knowledge datastore, build retrieval indices, run retrieval, perform model rollouts with retrieved subroutines, and filter the samples to output the final metrics.

Python9
19facebookresearch/flowception

Authors implementation of "Flowception Temporally Expansive Flow Matching for Video Generation".

Jupyter Notebook9
20facebookresearch/projectaria_gen2_depth_from_stereo

A tutorial and a set of tools to compute depth-from-stereo with Project Aria Gen2 devices. This includes stereo image rectification as well as disparity estimation

Jupyter Notebook9
21facebookresearch/wybecoder

WybeCoder Verified Generation of Imperative Code with LLMs

Python6
22facebookresearch/bites

Bayesian Inference & Tooling for Experimentation Systems

Python5
23facebookresearch/MRSQ

MRS.Q is a model-based reinforcement learning algorithm that selects actions with search.

Python5
24facebookresearch/physkin

Physics-based bone-driven neural garment animation

Python4
25facebookresearch/VoxelCodeBench

Code for VoxelCodeBench.

Python4
26facebookresearch/MuLoCo

MuLoCo Muon is a practical inner optimizer for DiLoCo

Python4
27facebookresearch/ads_model_kernel_library

High-performance GPU kernels for Ads and Recsys model training, independently implemented and optimized for real-world workloads and model-specific input characteristics.

Python4
28facebookresearch/GISTBench

GISTBench Dataset and Evaluation Code

3
29facebookresearch/adaptive_exploration_latent_state_bandits

Implementation of the proposed algorithms and simulation studies in Adaptive Exploration for Latent-State Bandits

Python2
30facebookresearch/spatio_directional_hash_encoding

We propose a new spatio-directional neural encoding for Neural Rendering applications that is compact and efficient, and supports all-frequency signals in both space and direction.

Python1

How to Read This Snapshot

Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.

For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.