tathadn/visiontriage-multimodal

VisionTriage — Multimodal Bug Report Dataset

5,551 synthetic (screenshot, bug report, severity) triples for automated UI bug severity triage.

Built on top of Rico (72k Android UI screenshots): each base screenshot has a localized visual defect injected by one of 5 deterministic mutators, and an LLM-generated bug report paired to the mutated image. Each bug type maps to a single severity label, enabling a clean per-class ablation.

• Repository: https://github.com/tathadn/visiontriage
• Paired model (best config): https://huggingface.co/tathadn/visiontriage-config-c

Splits

Split	N	Share
train	4441	80.0%
val	555	10.0%
test	555	10.0%

Bug types → severity

Bug type	Mutator behavior	Severity label
crash_dialog	ANR / fatal crash dialog rendered over the UI	blocker
occlude_element	Opaque rectangle obscures an interactive control	critical
overlap_siblings	Two sibling views rendered at the same bounding box	major
wrong_color	Button/background recolored to a contrasting value	minor
subtle_offset	Element translated by a few pixels	trivial

Because each bug type is mapped to exactly one severity, per-bug-type accuracy equals per-severity recall — useful for a clean ablation across visual severities.

Schema

Field	Type	Description
rico_id	string	ID of the base Rico screenshot (join key to Rico source images)
bug_type	string	One of the 5 mutators above
severity_true	string	Ground-truth severity (derived from bug_type per the table above)
severity_pred	string	Zero-shot Qwen2.5-VL-7B prediction (reference label, not target)
severity_raw	string	Raw (pre-parse) zero-shot model output
parse_method	string	How severity_pred was parsed from severity_raw
summary	string	Synthetic bug report: one-line summary
steps_to_reproduce	list[string]	Synthetic bug report: reproduction steps
actual_behavior	string	Synthetic bug report: observed behavior
expected_behavior	string	Synthetic bug report: expected behavior
package	string	Android package name of the source Rico app
width, height	int	Mutated screenshot dimensions (pixels)

Images are referenced, not stored

This dataset ships with text fields and rico_id only — not the screenshots themselves. To materialize (image, text, severity) triples, you need to:

1. Download the Rico dataset (60 GB) from http://www.interactionmining.org/rico.html.
2. Run the bug-injection pipeline from the project repo (src/data/inject_bugs.py) with the same rico_id list to regenerate the mutated screenshots deterministically.

See https://github.com/tathadn/visiontriage#reproduction for the full pipeline.

How it was built

1. Filter Rico → 3k screenshots with usable view hierarchies (no empty hierarchies, mobile-portrait, minimum element count).
2. Inject bugs → for each screenshot, apply 1–3 of the 5 mutators; each mutation produces one sample.
3. Generate reports → Qwen2.5-VL-7B-Instruct (zero-shot) produces a summary / STR / actual / expected for each mutated screenshot.
4. Label severities → deterministic bug_type → severity map (no human labeling).

Total: 5,551 samples that pass post-generation validation (report parses, severity extractable).

Intended use

• Training and evaluating multimodal severity-triage models (see Config B/C/D in the paired repo).
• Ablating image vs. text contributions to bug classification — the fixed bug-type→severity map keeps labels clean.
• NOT suitable for: real-world bug report classification without domain adaptation (reports are LLM-generated and stylized), or safety-critical deployment.

Limitations

• Synthetic text — bug reports are LLM-generated and may be stylistically uniform; real reports have noisier phrasing, missing fields, and irregular structure.
• Deterministic labels — severity is derived from bug type, not from human annotation. Real triage involves subjective judgment.
• UI domain only — Android UI screenshots; not representative of backend, API, or systems bugs.
• English only.

License

CC-BY-4.0 for the synthetic reports and metadata. Rico screenshots are distributed by their original authors under the terms at http://www.interactionmining.org/rico.html — respect those terms for any downstream redistribution of derived images.

Citation

@misc{visiontriage2026,
  title  = {VisionTriage: Multimodal Severity Prediction for UI Bug Reports},
  author = {Debnath, Tathagata},
  year   = {2026},
  url    = {https://github.com/tathadn/visiontriage}
}