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  3. Meta Research
Meta ResearchOrganization

Meta Research

@facebookresearch • Open source projects from facebookresearch. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.

Portfolio concentration

76%

Top three share

Shows whether the organization is driven by one breakout repo or several visible projects.

Breadth

30 repos

Visible snapshot

28 repositories updated in the last 90 days.

Leading language

Python

Portfolio mix

Python (24), Lean (1), C++ (1)

Average size

75

Stars per repository

Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.

Back to organizationsCompare repositories
Updated: 2026-08-25(13h ago)GitHub API fallback30 repositories

Portfolio Shape

76%

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

Average Repository Size

75

stars per repository in this same snapshot.

Current Mix

Python

is the most common language here, with 28 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 76%

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 76% 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 (24), Lean (1), C++ (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

#RepositoryLanguageStars🍴 ForksUpdated
1facebookresearch/brain2qwerty

Non-invasive decoding of typed sentences from MEG and EEG brain recordings using a convolutional encoder, transformer, and character-level language model.

Python9121324 weeks ago
2facebookresearch/meshflow

Repository for the CVPR 2026 paper MeshFlow Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer by Weiyu Li, Antoine Toisoul, Tom Monnier, Roman Shapovalov, Rakesh Ranjan, Ping Tan and Andrea Vedaldi.

Python510271 months ago
3facebookresearch/atlas-lean

ATLAS Autoformalized Textbook Library At Scale

Lean28530Yesterday
4facebookresearch/autoform-bot

Autoform Bot

Python100202 weeks ago
5facebookresearch/Flow-World-Models

FlowWM stochastic world modeling via flow matching in DINOv3 feature space, with the FuturePerception (Waymo) benchmark.

Python7652 weeks ago
6facebookresearch/project_superdex

SuperDex brings together a purpose-built physics engine, robotics authoring tools, and a scalable reinforcement learning interface in a unified simulation platform, with VR-based teleoperation and additional capabilities planned for future releases.

C++692Today
7facebookresearch/AutoPartGen

[NeurIPS 2025] AutoPartGen: Autoregressive 3D Part Generation and Discovery. This is a re-implementation of original model.

Python6431 months ago
8facebookresearch/TUA-Bench

A benchmark for general-purpose terminal-use agents.

Python4612 weeks ago
9facebookresearch/dance

Dance is an end-to-end framework that detects and classifies events in EEG signals. In a single forward pass, it extracts a set of events directly from the raw, unaligned recording.

Python4273 months ago
10facebookresearch/sparse-delta-memory

This repositories contains the reference implementation for the Sparse Delta Memory paper.More precisely, it contains the model definition as well as triton and cuda kernels for the Sparse Delta Memory layer.

Python3631 months ago
11facebookresearch/moe_vie

Official code release for "MoE-ViE Mixture of Experts Vision Encoder for Efficient Image and Video Understanding" (ECCV 2026)

Python1821 weeks ago
12facebookresearch/proxymate

Diagnose and correct proxy metrics against a primary outcome across four levels (representativity, unit, estimate, domain). It diagnoses failures, then apply adequate corrections when needed. Supporting code for the paper "proxymate: Diagnosing and Correcting Proxy Metrics for Reliable Inference."

Python1611 months ago
13facebookresearch/kernel_bench_verified

Welcome to KernelBench-Verified. This repository provides a robust, realistic evaluation framework for assessing custom CUDA kernels generated by Large Language Models (LLMs).

Python1411 months ago
14facebookresearch/r3d

Official source code release for R3D Quantitative 3D Spatial Reasoning for Egocentric Wearables

Python1311 weeks ago
15facebookresearch/LSD

Code for “Speculative Sampling For Faster Molecular Dynamics”.

Python1124 weeks ago
16facebookresearch/S-EMBER

Official codebase for S-EMBER A Large-Scale Benchmark for Streaming Egocentric Memory Retrieval

Python701 months ago
17facebookresearch/MJEPA

Training and evaluation code for our paper "MJEPA: A Simple and Scalable Joint-Embedding Predictive Architecture for Audio-Visual Learning"

Python411 weeks ago
18facebookresearch/multicalibration_for_matching

Companion repository to the paper "Multicalibration yields better matchings".https//arxiv.org/abs/2511.11413

Jupyter Notebook303 weeks ago
19facebookresearch/digiworld

A benchmark for evaluating Computer Use Agents (CUAs) on 15 sandboxed Android apps. DigiWorld has 3.2M+ unique configurations across data, themes, and UI states.

TypeScript211 weeks ago
20facebookresearch/GAMUT

GAMUT a Two-Level Meta-Rubric Benchmark for Long-Form Factuality

Python201 months ago
21facebookresearch/reliable-cua

Statistical evaluation for PRISM-compliant Computer-Using Agent (CUA) benchmarks.

Python101 weeks ago
22facebookresearch/projectaria_timecode_bridge

Reference firmware and 3D-printable enclosure for a SubGHz LTC beacon (STEVAL-FKI868V2) that time-aligns Project Aria Gen2 captures with any SMPTE LTC source.

C112 weeks ago
23facebookresearch/hst-bench

HST-Bench evaluation dataset contains 753 agentic tasks along with the time taken by human annotators to solve each task. This dataset was collected as part of our ICML 2026 paper on Scaling Small Agents Through Strategy Auctions https//arxiv.org/pdf/2602.02751

Python102 months ago
24facebookresearch/projectaria_unity_tools

Unity toolkit for interacting with Aria devices.

C#101 months ago
25facebookresearch/outlier_impact

This is for a research project on detecting outliers by their impact

Python103 months ago
26facebookresearch/Sharp_Linear-Minimax_Constants_for_Causal_Smoothing

This repo contains the code supporting the paper "Sharp Linear-Minimax Constants for Causal Smoothing" submitted to IEEE TSP

Python001 weeks ago
27facebookresearch/abtest_opportunity_cost

Code for the paper "A/B testing with opportunity costs: Trading off reward and error control" by Ben Chugg, Artem Vorozhtsov, and Houssam Nassif

Python002 weeks ago
28facebookresearch/REAP-pipeline-for-coding-agent-benchmarks

Artifact for REAP paper "REAP Automatic Curation of Coding Agent Benchmarks from Interactive Production Usage"

Python003 weeks ago
29facebookresearch/SaliMory

This is the source implementation for SaliMory Orchestrating Cognitive Memory forConversational Agents.

Python001 months ago
30facebookresearch/Learning_Regularization_Structure_for_Biosignal_Template_Estimation

A repository supporting the paper "Learning Regularization Structure for Biosignal Template Estimation".

Python001 months ago

Next step after the organization read

Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Open flagship repoCompare repositoriesBack to organizations

Learn and methodology

Keep trust-building context reachable, but behind the first data read instead of ahead of it.
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How to read this organization 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.