The DOI matches its Crossref record.
T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The development of such metrics is challenging as they require a comprehensive and fine-grained cross-modal understanding (Huang et al., 2023).”
From Deepfake: definitions, performance metrics and standards, datasets, and a meta-review (2024) · cites this paper as Huang et al., 2023
Citations
Cited by
Sorted by citations
Deepfake: definitions, performance metrics and standards, datasets, and a meta-review
Altuncu, E., Franqueira, V. N. L., & Li, S. (2024) · Frontiers in Big Data · doi:10.3389/fdata.2024.1400024 · Cited by 134
Metadata
- Authors
- Huang, K., Sun, K., Xie, E., Li, Z., & Liu, X.
- Venue
- Advances in Neural Information Processing Systems 36
- Published
- 2023
- Pages
- 78723-78747
- ISSN
- 1049-5258 (ISSN-L)
- OpenAlex
- W7133231872
- Cited by
- 100
- References
- 0
- Citations by year
- 2026: 70 · 2025: 30
- FWCI
- 9.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- neural information processing systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- text-to-image generation, compositional image generation, benchmark, image composition
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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