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| Checkpoint | Test mAP | Params | Backbone |
|---|---|---|---|
| idea-502970 | 0.7853 | ~24MB | V-JEPA 2 frozen features |
| idea-eb79fc | 0.7816 | ~11MB | V-JEPA 2 frozen features |
| idea-2c0263 | 0.7802 | ~24MB | V-JEPA 2 frozen features |
best_model.pt — PyTorch checkpoint (temporal classifier head)idea_config.yaml — Full training config (proposed by LLM agent)metrics.json — Training/val/test metricsNote: These are the lightweight temporal heads that operate on pre-extracted backbone features. You must extract V-JEPA 2 / DINOv2 features from raw videos first using the scripts in the orze-nips repo.
1from huggingface_hub import hf_hub_download
2import torch
3
4ckpt_path = hf_hub_download(
5 repo_id="warlockee/orze-nips-models",
6 filename="idea-502970/best_model.pt"
7)
8ckpt = torch.load(ckpt_path, map_location="cpu", weights_only=False)
9# Load into temporal classifier defined in training/train.py1@inproceedings{anonymous2026autoresearch,
2 title={Auto Research Is Not Auto Tuning: Convergence Analysis of 10,000 {LLM}-Guided Experiments},
3 author={Anonymous},
4 booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
5 year={2026}
6}