metadata

title: 3D-POPE Leaderboard
emoji: 🥇
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 4.4.0
app_file: app.py
pinned: false
license: apache-2.0

This is a public leaderboard of the 3D-POPE benchmark for evaluating hallucinations in 3D-LLMs. The benchmark was introduced in: "3D-GRAND: A Million-Scale Dataset for 3D-LLMs with Better Grounding and Less Hallucination"

@misc{yang20243dgrand,
    title={3D-GRAND: A Million-Scale Dataset for 3D-LLMs with Better Grounding and Less Hallucination},
    author={Jianing Yang and Xuweiyi Chen and Nikhil Madaan and Madhavan Iyengar and Shengyi Qian and David F. Fouhey and Joyce Chai},
    year={2024},
    eprint={2406.05132},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

Start the configuration

Most of the variables to change for a default leaderboard are in src/env.py (replace the path for your leaderboard) and src/about.py (for tasks).

Results files should have the following format and be stored as json files:

{
    "config": {
        "model_dtype": "torch.float16", # or torch.bfloat16 or 8bit or 4bit
        "model_name": "path of the model on the hub: org/model",
        "model_sha": "revision on the hub",
    },
    "results": {
        "task_name": {
            "metric_name": score,
        },
        "task_name2": {
            "metric_name": score,
        }
    }
}

Request files are created automatically by this tool.

If you encounter problem on the space, don't hesitate to restart it to remove the create eval-queue, eval-queue-bk, eval-results and eval-results-bk created folder.

Code logic for more complex edits

You'll find

the main table' columns names and properties in src/display/utils.py
the logic to read all results and request files, then convert them in dataframe lines, in src/leaderboard/read_evals.py, and src/populate.py
teh logic to allow or filter submissions in src/submission/submit.py and src/submission/check_validity.py