---
language:
- en
license:
- cc-by-4.0
- cc-by-nc-sa-4.0
task_categories:
- visual-question-answering
- multiple-choice
pretty_name: RFSchemBench
size_categories:
- 1K<n<10K
configs:
- config_name: permissive
  default: true
  data_files:
  - split: test
    path: data/permissive/test-*.parquet
- config_name: nc_allowed
  data_files:
  - split: test
    path: data/nc_allowed/test-*.parquet
tags:
- rf
- circuit
- schematic
- multimodal
- electronic-engineering
- benchmark
- vqa
---

# RFSchemBench

A multimodal LLM evaluation benchmark for **radio-frequency circuit schematic understanding**, organized by a four-level semantic hierarchy:

1. **Component Understanding** — visible component, parameter, label, and supply-rail recognition.
2. **Structural Understanding** — net membership, pin-to-net mapping, boundary connectivity, and pair-via-net topological reasoning.
3. **Functional Understanding** — circuit functional role, signal-form classification, supply strategy, sub-type identification.
4. **Dynamic Reasoning** — counterfactual plot choice and schematic-modification ↔ simulation-result matching, grounded in `ngspice` simulation.

The benchmark contains **2,348 questions across 590 rendered schematic pages** from publicly available RF schematic data.

## Quick start

```python
from datasets import load_dataset

# Permissive subset (CC-BY-4.0; recommended for most users)
ds = load_dataset("anonymous-submission042/RFSchemBench", "permissive", split="test")

# Full benchmark including a NonCommercial-ShareAlike subset
ds_nc = load_dataset("anonymous-submission042/RFSchemBench", "nc_allowed", split="test")

print(ds[0]["question"], "→ answer:", ds[0]["answer"])
ds[0]["image"].show()  # PIL.Image of the schematic
```

## Configurations

| Config | Rows | License | Notes |
|---|---:|---|---|
| `permissive` (default) | 2,258 | `CC-BY-4.0` | Excludes the NC-licensed source class. Suitable for commercial / industrial reviewers. |
| `nc_allowed` | 2,348 | mixed `CC-BY-4.0` + `CC-BY-NC-SA-4.0` | Full benchmark. Per-row `license` field marks which items are NC-licensed. NonCommercial usage only. |

## Schema

Each row has the following fields:

| Field | Type | Description |
|---|---|---|
| `question_id` | string | Unique identifier (stable across releases) |
| `item_id` | string | Source schematic identifier |
| `source` | string | Source class (`qucs` / `kicad` / `myriadrf` / `m17` / `oresat`) |
| `level` | string | One of `Component Understanding` / `Structural Understanding` / `Functional Understanding` / `Dynamic Reasoning` |
| `category` | string | Coarse-grained tag |
| `question` | string | English prompt (what models are evaluated on) |
| `image` | PIL.Image | Primary schematic rendering (`image.png`) |
| `context_images` | list of `{caption, image}` | Auxiliary context images (Dynamic Reasoning only — schematic plus baseline / variant simulation plots) |
| `options` | list of `{label, text, image}` | Multi-choice options (Dynamic Reasoning only). Some options have only `text`, others have both `text` and `image`. |
| `answer_type` | string | `enum_label` / `comma_separated_list` / `integer` / `short_text` |
| `answer_allowed` | list of string | Permitted enum values (empty for non-enum types) |
| `answer` | string | Gold answer; for list-type answers, comma-separated |
| `source_schematic` | string | Provenance: original `.kicad_sch` / `.sch` path |
| `license` | string | Per-row license tag (`CC-BY-4.0` or `CC-BY-NC-SA-4.0`) |

## Construction

The benchmark is constructed via **expert-rule-guided programmatic generation from authoritative sources**:

- Domain experts encode question-generation rules and gold-answer semantics into Python programs.
- Gold answers are extracted deterministically from authoritative source artifacts (KiCad CLI output, Qucs native schematic graph, `ngspice` simulation outputs).
- LLMs are deliberately **excluded from the gold-answer path**; they are used only as an auxiliary RF-relevance gate at the page level.
- An iterative rule-refinement loop catches edge cases during construction; the released gold answers reflect the latest revisions.

This avoids the gold-answer noise floor of LLM-as-Generator benchmarks while scaling beyond purely human-curated efforts.

## License

This dataset is released under a **two-tier license model** because the upstream sources have heterogeneous licenses:

- **`permissive` config** (recommended default): all rows under `CC-BY-4.0`. Compatible with commercial use, redistribution, and derivative works subject to attribution.
- **`nc_allowed` config**: includes one source class (`m17` digital-radio community hardware, 90 questions) which is upstream-licensed under `CC-BY-NC-SA-4.0` (NonCommercial-ShareAlike). Per-row `license` field marks affected items. Users must respect NC + ShareAlike for those rows.

Per-source licensing summary:

| Source class | Upstream license profile | Tier inclusion |
|---|---|---|
| `qucs` | GPL-2.0 example schematics (treated as derivative-work CC-BY-4.0 for image renderings) | both |
| `kicad` | mostly MIT / Apache-2.0 / GPL-3.0 mix | both |
| `myriadrf` | mostly Apache-2.0 / CC-BY-4.0 | both |
| `oresat` | CERN-OHL-S-2.0 (treated as share-alike-compatible CC-BY-4.0 for renderings) | both |
| `m17` | **CC-BY-NC-SA-4.0** ⚠ NC | `nc_allowed` only |

For redistribution that requires fully permissive licensing, use only the `permissive` config.

## Limitations

1. **Source-class size imbalance**: question counts per source class span 40–974; per-source claims should be reported with N.
2. **Dynamic Reasoning scope**: only one source class has the simulation-grounded subset (55 questions). This dimension is reported as a small stress test, not the main result.
3. **Language**: questions are evaluated in English. (A Chinese parallel set was used internally during construction for human review but is not part of the released schema.)
4. **Single-image protocol**: each question is paired with one primary schematic image (Dynamic Reasoning rows additionally provide context plots / option plots).
5. **Anonymized release**: this submission account is for double-blind peer review. The dataset will be transferred to the official maintainer account upon acceptance.

## Citation

```bibtex
@misc{rfschembench2026,
  title  = {RFSchemBench: A Multi-Source, Hierarchically-Structured Multimodal Benchmark for RF Circuit Schematic Understanding},
  author = {Anonymous},
  year   = {2026},
  note   = {Submitted to NeurIPS 2026 Evaluations \& Datasets Track}
}
```

## Contact

For benchmark integrity issues (gold-answer corrections, RF-gate disputes, parser / scorer concerns), please open a Discussion on this dataset's HuggingFace page. During the double-blind review window, identifying contact details are intentionally withheld.