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Data sourced from GitHub API

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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

87%

Top three share

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

Breadth

30 repos

Visible snapshot

30 repositories updated in the last 90 days.

Leading language

Python

Portfolio mix

Python (25), C++ (1), TypeScript (1)

Average size

55

Stars per repository

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

Back to organizationsCompare repositories
Updated: 2026-10-09(19h ago)GitHub API fallback30 repositories

Portfolio Shape

87%

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

Average Repository Size

55

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 87%

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 87% 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), C++ (1), TypeScript (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/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++72176Today
2facebookresearch/context-language-models

Official repository for "Context Language Models"

Python664761 weeks ago
3facebookresearch/swe-sweep

How many bugs can LMs find & fix in large codebases?

Python597Today
4facebookresearch/EmoRES-TTS

Residual emotion steering for emotional TTS generation. EmoRES-TTS decomposes a mixed-emotion steering vector into a shared axis and an emotion-carrying residual and weight the two independently.

Python3731 weeks ago
5facebookresearch/moe_vie

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

Python3131 months ago
6facebookresearch/WearableQA

WearableQA A Benchmark for Health Reasoningover Real-World Wearable Data

Python2411 months ago
7facebookresearch/GenIA

Generative Reconstruction with Test-Time Input Alignment

Python202Yesterday
8facebookresearch/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."

Python1712 months ago
9facebookresearch/MJEPA

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

Python1531 months ago
10facebookresearch/UnStep

Official implementation of the paper UnStep Training-Free Acceleration of Causal Video Diffusion with Fewer Steps Than Distillation

Python141Today
11facebookresearch/midtraining-distillation

Code for our paper: "Knowledge Distillation During Mid-Training Favors Reasoning over Factual Recall"

Python121Today
12facebookresearch/robo_jepa

OSS of roboJEPA

Python111Today
13facebookresearch/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.

TypeScript815 days ago
14facebookresearch/E2E-SWE

E2E-SWE Benchmarking LLMs on Building Working Codebases from Scratch

Python304 days ago
15facebookresearch/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.

C312 months ago
16facebookresearch/hear_voice_bias_benchmark

HEAR (Human-recorded Evaluation of Audio-LLM bias by Real speakers), a large-scale, ecologically valid benchmark comprising real human audio samples from demographically diverse participants.

Python201 weeks ago
17facebookresearch/adepts

Repo for 'ADeptS-Bench Measuring the Trustworthiness of Computer Use Agents across Devices'

Python201 months ago
18facebookresearch/schlepp

schlepp is the Python package for the Schlepp synthetic dataset, which features multi-camera, multi-actor, multi-modal object manipulation sequences. It provides dense ground-truth optical flow, depth, segmentation, point tracks, oriented bounding boxes, object animation, and MHR body parameters.

Python201 weeks ago
19facebookresearch/reliable-cua

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

Python201 months ago
20facebookresearch/GAMUT

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

Python202 months ago
21facebookresearch/logbook

Source for Logbook: Extremely Long-form Audio Event Understanding

Python103 days ago
22facebookresearch/show3d

Python API for the SHOW3D dataset (CVPR 2026) https://huggingface.co/datasets/facebook/show3d-dataset

Python105 days ago
23facebookresearch/Tabula-Rasa

Official source code for "Tabula Rasa Monte Carlo estimation of unit-variance noise with controlled spatio-temporal correlation"

Jupyter Notebook103 weeks ago
24facebookresearch/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

Python101 months ago
25facebookresearch/SaliMory

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

Python102 months ago
26facebookresearch/best-n-selection-video-reasoning

Code for the paper "Selecting or Solving? What Best-of-$N$ Verification Delivers in Video Reasoning"

Python002 days ago
27facebookresearch/logact

Hardening Agentic Systems via a Shared Log Design

Rust014 days ago
28facebookresearch/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

Python001 months ago
29facebookresearch/REAP-pipeline-for-coding-agent-benchmarks

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

Python002 months ago
30facebookresearch/Learning_Regularization_Structure_for_Biosignal_Template_Estimation

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

Python002 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.
GuideMethodologyArticlesWeekly Digest

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.