---
pretty_name: CIRCUS
license: other
task_categories:
- other
language:
- en
tags:
- composed-image-retrieval
- multimodal-retrieval
- benchmark-audit
- multimodal-composition
configs:
- config_name: cirr
  data_files:
  - split: full
    path: data/cirr/full.parquet
  - split: shortcut_free
    path: data/cirr/shortcut_free.parquet
  - split: human_audited
    path: data/cirr/human_audited.parquet
  - split: validated
    path: data/cirr/validated.parquet
- config_name: fashioniq
  data_files:
  - split: full
    path: data/fashioniq/full.parquet
  - split: shortcut_free
    path: data/fashioniq/shortcut_free.parquet
  - split: human_audited
    path: data/fashioniq/human_audited.parquet
  - split: validated
    path: data/fashioniq/validated.parquet
- config_name: lasco
  data_files:
  - split: full
    path: data/lasco/full.parquet
  - split: shortcut_free
    path: data/lasco/shortcut_free.parquet
  - split: human_audited
    path: data/lasco/human_audited.parquet
  - split: validated
    path: data/lasco/validated.parquet
- config_name: circo
  data_files:
  - split: full
    path: data/circo/full.parquet
  - split: shortcut_free
    path: data/circo/shortcut_free.parquet
  - split: human_audited
    path: data/circo/human_audited.parquet
  - split: validated
    path: data/circo/validated.parquet
---

# CIRCUS

CIRCUS (Composed Image Retrieval Cleaned of Unimodal Shortcuts) is a
metadata-only diagnostic resource accompanying **Do Composed Image Retrieval
Benchmarks Require Multimodal Composition?** It audits CIRR, FashionIQ, LaSCo,
and CIRCO for unimodal shortcuts and validates a subset of shortcut-free queries.

## Loading

```python
from datasets import load_dataset

validated = load_dataset(
    "EdinburghNLP/CIRCUS",
    "cirr",
    split="validated",
    revision="v1.0",
)
shortcut_free = load_dataset(
    "EdinburghNLP/CIRCUS",
    "cirr",
    split="shortcut_free",
    revision="v1.0",
)
```

Available configurations are `cirr`, `fashioniq`, `lasco`, and `circo`. Each
configuration has four splits:

- `full`: all original benchmark evaluation queries with automatic audit labels.
- `shortcut_free`: all queries not solved by any evaluated unimodal
  configuration at `K=10`; this includes both composition-required and
  unresolved queries (CIRCUS-SF).
- `human_audited`: shortcut-free queries inspected during manual validity
  annotation, including both valid and rejected instances.
- `validated`: the human-audited queries judged to be valid CIR instances and
  retained in CIRCUSV.

| Dataset | Full | Shortcut-free | Human-audited | Validated |
|---|---:|---:|---:|---:|
| CIRR | 4,170 | 685 | 685 | 303 |
| FashionIQ | 6,003 | 4,069 | 2,000 | 586 |
| LaSCo | 30,031 | 18,418 | 2,000 | 758 |
| CIRCO | 220 | 56 | 56 | 42 |
| **Total** | **40,424** | **23,228** | **4,741** | **1,689** |

For FashionIQ and LaSCo, human validation uses stratified samples of 1,000
composition-required and 1,000 unresolved queries per dataset. Their validated
splits are therefore validated diagnostic subsets, not complete cleanings of the
full shortcut-free residues.

## Images and source datasets

This repository does not contain or redistribute images. Image paths are
portable identifiers relative to the corresponding source dataset. Users must
obtain CIRR, FashionIQ, LaSCo, and CIRCO from their official sources and comply
with each dataset's terms.

The source datasets use different licenses and terms, including MIT-style terms
for CIRR and LaSCo annotations, the Community Data License Agreement for
FashionIQ, and CC BY-NC 4.0 for CIRCO. Underlying NLVR2 and COCO images remain
subject to their original terms. The `other` license marker reflects this mixed
provenance; it is not a relicensing of source data.

## Audit labels

At `audit_k=10`, a query is labelled `shortcut` when at least one evaluated
unimodal configuration retrieves an annotated positive in the top 10. A
shortcut-free query is `composition_required` when a multimodal configuration
succeeds, and `unresolved` when no evaluated multimodal configuration succeeds.
These are operational benchmark labels and do not imply that shortcut-labelled
queries are invalid.

## Limitations

CIRCUSV is intended as a diagnostic of multimodal dependence, not a complete
replacement for the original benchmarks. Human validation is complete for the
CIRR and CIRCO shortcut-free residues but sampled for FashionIQ and LaSCo. The
resource is metadata-only and requires separately downloaded source images.

## Citation

```bibtex
@inproceedings{attimonelli2026circus,
  title={Do Composed Image Retrieval Benchmarks Require Multimodal Composition?},
  author={Attimonelli, Matteo and De Bellis, Alessandro and Gema, Aryo Pradipta and Saxena, Rohit and Sekoyan, Monica and Kwan, Wai-Chung and Pomo, Claudio and Suglia, Alessandro and Jannach, Dietmar and Di Noia, Tommaso and Minervini, Pasquale},
  booktitle={Advances in Neural Information Processing Systems},
  year={2026}
}
```

Code and additional documentation:
<https://github.com/EdinburghNLP/CIRCUS>