Collection of awesome test-time (domain/batch/instance) adaptation methods

From idea to production in just few lines: Graph-Based Programmable Neuro-Symbolic LM Framework - a production-first LM framework built with decade old Deep Learning best practices

[ICCV 2025 Workshop Outstanding Paper Award] VChain: Chain-of-Visual-Thought for Reasoning in Video Generation

Official Implementation of Spatial-TTT: Streaming Visual-based Spatial Intelligence with Test-Time Training

[NeurIPS 2022] Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering

A modular and easy-to-use framework for Test-Time Training (TTT) and Test-Time Adaptation (TTA) in Pytorch, making your networks more generalizable with minimal effort ✨

[CVPR 2025] Test-Time Visual In-Context Tuning

[CVPR 2024] Depth-aware Test-Time Training for Zero-shot Video Object Segmentation

[AAAI 2024] Towards Real-World Test-Time Adaptation: Tri-Net Self-Training with Balanced Normalization

Official code for "IT³: Idempotent Test-Time Training" (ICML 2025)

[TPAMI 2024] The official implementation of "Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training"

Authors official PyTorch implementation of the "Test-time Training for Matching-based Video Object Segmentation" [NeurIPS 2023]

F2FD-TTT: Test-time training with self-supervised Fourier-to-Fourier denoising for membrane segmentation in cryo-ET tomograms

[CVPR 2026] Physical Simulator In-the-Loop Video Generation

Specialization after Generalization

Codebase for the paper ImPoster: Text and Frequency Guidance for Subject Driven Action Personalization using Diffusion Models

Discovering Test-Time Training on Traditional ML Models.

ARC-Test-Time-Training (ARC-TTT)

Framework-agnostic vision toolkit for training and evaluation

ttt_ssm_eval - Toy demo for Test-Time Training (TTT) in State Space Models (SSM). Input gradient monitoring and pre-update safety gates.