BELO Benchmark for Evaluating Language Models in Ophthalmology
Expert-curated ophthalmology multiple-choice benchmark with rationales, assembled for held-out language-model evaluation.
At a glance
| Field | Value |
|---|---|
| Short name | belo |
| Full name | BELO Benchmark for Evaluating Language Models in Ophthalmology |
| First published | Unknown |
| Publication date precision | Unknown |
| Publication date evidence | Unknown |
| Publication date source field | Unknown |
| Publication date reviewed | Unknown |
| Primary category | text |
| Resource role | current_dataset |
| Dataset family | belo |
| Contained modalities | text |
| Tasks | question_answering, evaluation, reasoning |
| Primary reported quantity | 900 questions |
| Classes | Not reported (Not reported) |
| Splits | all |
| Size | Not reported |
| Source-stated terms | Unknown; mixed upstream question-bank terms |
| Normalized terms | unknown |
| Descriptive screening label | Unknown or unclear; do not assume permission |
| Terms scope | mixed_components |
| Access friction | author_contact |
| Route backend | Manual (upstream-gated) |
| Availability | available (checked 2026-07-21) |
| Acquisition support | manual_access_blocked |
| Legacy sample-loader status | Metadata and access only |
Reported quantities
| Role | Count | Unit | Scope | Basis | Evidence |
|---|---|---|---|---|---|
| Primary | 900 | questions | Held-out multiple-choice benchmark | official_source_description | belo-dataset.vercel.app |
Counts retain their source-reported units. Additional rows can describe components, paired items, or derivative copies and are not automatically added to the primary quantity.
Notes
The 900 questions aggregate BCSC, BioASQ, MedMCQA, MedQA, and PubMedQA sources. The project page instructs users to request the held-out benchmark by email; verify every applicable source term.
Access information and download
- CLI
- Python
# This route requires upstream human action; no transfer starts.
eyehub download belo --data-dir ./data --dry-run --json
# Follow the official instructions shown by preflight.
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('belo')
print(preflight_dataset(ds, './data')) # returns manual_access_blocked
Upstream page: belo-dataset.vercel.app
Source-term evidence: belo-dataset.vercel.app
Loader status
This catalog record provides metadata and access instructions, but it does not yet include a standard DatasetSample loader. Inspect the source file structure or contribute a loader before using it in a training pipeline.
Citation
- BibTeX
- Plain text
@misc{belo,
title = { BELO Benchmark for Evaluating Language Models in Ophthalmology },
note = { BELO: A Benchmark for Evaluation of Language Models in Ophthalmology. Ophthalmology Science. 2025:101050. doi:10.1016/j.xops.2025.101050 },
year = { 2025 },
url = { https://belo-dataset.vercel.app/ },
}
BELO: A Benchmark for Evaluation of Language Models in Ophthalmology. Ophthalmology Science. 2025:101050. doi:10.1016/j.xops.2025.101050
Source-stated terms
- Raw source string: Unknown; mixed upstream question-bank terms
- Normalized category:
unknown - Apparent scope:
mixed_components - Descriptive screening label: Unknown or unclear; do not assume permission
⚠️ Source-stated terms, scope, and normalized labels are curation metadata, not legal advice or a permission finding. Review the current official source before transfer or reuse.
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