gowitheflowlab/physics-bench-dynamics-train

Physics Bench Dynamics Train

Repository: gowitheflowlab/physics-bench-dynamics-train

Training split with hard negatives for dynamics simulation video retrieval.

• rows: 1900
• metadata columns: text, video, hard_negative_texts, hard_negative_videos
• hard negatives per row: 5, drawn from the other 99 cases of the same family
• video paths: repository-relative videos/<family>/<case_id>.mp4
• list alignment: hard_negative_texts[i] and hard_negative_videos[i] come from the same case
• text and hard_negative_texts use the natural-language query style (dynamics_parsed_v1_recovered_5sentence), matching the parsed_text column of gowitheflowlab/physics-bench-dynamics-eval-1900
• case parameters are disjoint from the evaluation split, so no evaluation case is reachable here

Reproducibility

• sampling: global seed 42, family alphabetical order then case_id order, one random.Random(seed) stream, random.sample(sorted(other_99_case_ids), 5)
• assignment digest: 01e5e7ec5576209c
• text: generated from the training case metadata; see source_metadata/build_hardnegs_v2_metadata.py and source_metadata/v2_manifest.json
• validation report: quality/validation.json

Loading

from pathlib import Path
import pyarrow.parquet as pq
from huggingface_hub import snapshot_download

root = Path(snapshot_download("gowitheflowlab/physics-bench-dynamics-train", repo_type="dataset"))
rows = pq.read_table(root / "metadata.parquet").to_pylist()
row = rows[0]
positive_video = root / row["video"]
negative_videos = [root / path for path in row["hard_negative_videos"]]