Downloads · 30 days
0
hajimi21368/EmBench-Submission
EmBench-Submission is a machine learning model from hajimi21368. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository contains the model weights, environment configurations, and evaluation scripts for Team Ideal-Embody's submission to the CVPR 2026 Embodied Challenge (Phase-2).
Downloads · 30 days
0
Access
Public
Updated May 27, 2026
Repo size
27.3 GB
Likes
0
Public
Click a slice to open those files.
.safetensors24.4 GB · 92%
From the Hugging Face model README
This repository contains the model weights, environment configurations, and evaluation scripts for Team Ideal-Embody's submission to the CVPR 2026 Embodied Challenge (Phase-2).
The submission covers two main tasks: ALFRED and Navigation. Please follow the respective guidelines below to set up the environments and reproduce the evaluation results on the hidden held-out benchmarks.
. (EmBench-Submission Root)
├── embench.yml # Conda environment file for ALFRED
├── embench_nav.yml # Conda environment file for Navigation
├── Qwen2.5-VL-3B-ALF/ # Model weights / checkpoints for ALFRED
├── Qwen2.5-VL-3B-NAV/ # Model weights / checkpoints for Navigation
├── alfred/ # Directory for ALFRED task
│ └── alf_base.sh # Evaluation script for ALFRED base dataset
├── navigation/ # Directory for Navigation task
│ └── Navgation/ # Core Navigation submission directory
│ └── nav_base.sh # Evaluation script for Navigation base dataset
└── running/ # Running logs / outputs
Ensure you are in the repository root directory, then create and activate the dedicated Conda environment:
# Create the environment using the yml file in the root
conda env create -f embench.yml
# Activate the environment
conda activate embench
Change your current working directory to the alfred folder and execute the evaluation script:
# Move to alfred directory
cd alfred
# Run the evaluation on the base dataset
bash alf_base.sh
Ensure you are in the repository root directory, then create and activate the dedicated Conda environment:
# Create the environment using the yml file in the root
conda env create -f embench_nav.yml
# Activate the environment
conda activate embench_nav
Change your current working directory to the Navigation submission folder and execute the evaluation script:
# Move to the navigation directory
cd navigation/Navgation/
# Run the evaluation on the base dataset
bash nav_base.sh