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Datasets:
Jetson888
/
PhysAlign

Tasks:
Question Answering
Visual Question Answering
Modalities:
Image
Text
Formats:
json
Languages:
English
Chinese
Size:
1K - 10K
Tags:
physics
multimodal
benchmark
evaluation
image
Libraries:
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pandas
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License:
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metadata 
pretty_name: PhysAlign
language:
  - en
  - zh
license: other
task_categories:
  - question-answering
  - visual-question-answering
tags:
  - physics
  - multimodal
  - benchmark
  - evaluation
  - image
size_categories:
  - 1K<n<10K
configs:
  - config_name: raw
    data_files:
      - split: development
        path: data/raw/development.jsonl
      - split: test
        path: data/raw/test.jsonl
  - config_name: gold
    data_files:
      - split: development
        path: data/gold/development.jsonl
      - split: test
        path: data/gold/test.jsonl

PhysAlign

PhysAlign is a bilingual multimodal physics benchmark for testing whether a model can make local observations and bind textual or visual references to the correct candidate entity. It does not ask the evaluated model to solve the original examination problem.

PhysAlign was constructed from selected examples in previously released public benchmarks, followed by source adaptation, probe generation, model-based review, cross-source exact-input deduplication, and split checks.

Dataset summary

Source component Mother problems Raw Gold
local (SeePhys + LiveK12Bench) 458 1,679 211
OlympiadBench 209 669 97
PhysElite 220 792 104
PhyX 16 40 35
GAOKAO-MM 23 38 26
expansion_v3 (SeePhys) 60 123 80
Total 986 3,341 553
Split Mother problems Raw Gold
development 79 208 90
test 907 3,133 463

Raw interface counts:

  • T02-single: 2,407
  • T03-image: 514
  • T03-text: 420

Languages:

  • Raw: 3,129 English and 212 Chinese instances.
  • Gold: 458 English and 95 Chinese instances.

Released files 

.
|-- README.md
|-- LICENSE.md
|-- THIRD_PARTY_NOTICES.md
|-- release.json
|-- MANIFEST.sha256
|-- data/
|   |-- raw/
|   |   |-- development.jsonl
|   |   `-- test.jsonl
|   `-- gold/
|       |-- development.jsonl
|       `-- test.jsonl
`-- public/
    |-- qa_raw.json
    |-- qa_gold.json
    `-- images/
        |-- 00/
        |-- 01/
        |-- ...
        `-- ff/
  • public/qa_raw.json and public/qa_gold.json are the canonical array-form benchmark inputs.
  • data/ contains equivalent JSONL copies split by condition and benchmark split for the Hugging Face Dataset Viewer.
  • Images are sharded by the first two hexadecimal characters of their SHA-256 filename so that no Hub directory exceeds the file-count limit.
  • Every attachment path is resolved relative to public/.
  • release.json contains sanitized release statistics and provenance metadata. Service endpoint information has been removed.
  • MANIFEST.sha256 contains SHA-256 checksums for every released file except the manifest itself.

Scoring answers, source-key mappings, private membership records, internal review traces, and archived component releases are intentionally not included.

Record schema

Each record contains:

Field Meaning
condition raw or gold
instance_id Stable public instance identifier
logical_probe_id Identifier shared by related Raw/Gold conditions
task_id T02 or T03
interface Expected response interface
language en or zh
split development or test
schema_version Public schema version
input.messages System and user messages for the evaluated model
input.attachments Image metadata and paths relative to public/

Interfaces:

  • T02-single: return {"referent":"E..."}.
  • T03-image: return {"read":"...","owner":"E..."}.
  • T03-text: return {"owner":"E..."}.

The read value is evaluated with the matching PhysAlign normalizer. The evaluator does not perform additional physics inference or unit conversion for this field.

Gold is a supplementary input condition with local transcription information. It is not an additional independent question and it does not contain the hidden scoring answer.

Loading

Hugging Face Datasets 

from datasets import load_dataset

raw = load_dataset("Jetson888/PhysAlign", "raw")
gold = load_dataset("Jetson888/PhysAlign", "gold")

raw_dev = raw["development"]
raw_test = raw["test"]

The Dataset Viewer exposes attachment metadata as nested values. To access image files, download the repository snapshot as shown below.

Download the complete benchmark 

import json
from pathlib import Path
from huggingface_hub import snapshot_download

root = Path(snapshot_download(
    repo_id="Jetson888/PhysAlign",
    repo_type="dataset",
))

public_root = root / "public"
records = json.loads((public_root / "qa_raw.json").read_text(encoding="utf-8"))

first_attachment = records[0]["input"]["attachments"][0]
image_path = public_root / first_attachment["path"]
print(image_path)

CLI equivalent:

hf download Jetson888/PhysAlign --repo-type dataset --local-dir PhysAlign

Evaluation guidance

  1. Use the development split for integration and prompt-format debugging.
  2. Send only the released public inputs to the evaluated model.
  3. Aggregate or resample by mother problem rather than treating every probe as independent.
  4. Report Raw and Gold separately.
  5. Report T02-single, T03-image, and T03-text separately.
  6. Use a matching version of the PhysAlign benchmark kit and its normalizers for scoring.

Data status and limitations

  • human_reviewed=false and independent_human_quality_certified=false.
  • Exact duplicate public inputs across sources were collapsed.
  • Near-duplicate reconciliation and historical development-sample reconciliation are incomplete.
  • Some source-level or conversion-level findings remain unresolved; affected mother problems were quarantined where identified.
  • Shared-image mothers were grouped for split-risk control but are not asserted to be semantic duplicates.
  • The release should not be presented as a zero-error dataset or as an independently certified unseen-test benchmark.
  • Original source data may carry additional limitations and usage conditions; see THIRD_PARTY_NOTICES.md and the upstream dataset cards.

Sources and license

This is a composite dataset. The repository therefore uses license: other rather than applying one upstream license to all records. PhysAlign-authored packaging and metadata, and all third-party attributions and conditions, are described in LICENSE.md and THIRD_PARTY_NOTICES.md.

The public inputs were derived from:

Citation

If you use PhysAlign, cite this repository and the applicable upstream datasets listed in THIRD_PARTY_NOTICES.md.

@dataset{physalign2026,
  title     = {PhysAlign: A Multimodal Physics Local-Observation and Role-Binding Benchmark},
  author    = {PhysAlign Contributors},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/Jetson888/PhysAlign}
}

中文说明

PhysAlign 用于评测多模态模型能否正确完成局部观察、可见文本转录和指代/角色绑定，而不是要求模型解答原始物理题。公开仓库只包含模型输入与图片；评分答案、映射、审核记录及历史封存副本均不会公开。