whatmodel.sh / image / X-LXMERT
X-LXMERT
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X-LXMERT is an open-weights image model from UNC Chapel Hill, released September 2020.
Catalogue identity notes
TIFA Appendix E X-LXMERT row; visual-token text-to-image generation.
Score within the LMArena text-to-image comparison set only.
$ how it compares
The image models ranked either side of X-LXMERT, out of 197 with a score.
| # | model | score | where |
|---|---|---|---|
| 193 |  LCM Dreamshaper v7 | 23±4 | local |
| 194 |  InstructPix2Pix | 19±3 | local |
| 195 | X-LXMERT | 17±4 | comparison only |
| 196 |  AttnGAN (COCO) | 16±4 | comparison only |
| 197 |  CogView2 | 1±4 | local |
$ what it's good at
text to image▃▂▇▇▆▅█▇▂▃▁▁ #156 of 157 * · 93% of its score · 1 test
Trails CogView2 here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| TIFA v1.0 (overall, mPLUG VQA) | 58.6% ✎ | █·······▄▄▄▄ beats 1/5 | 93% |
$ where to run it
No verified API or download recorded yet · add one
Weights and documentation: github.com/airsplay ↗
$ how the score was worked out · TIFA: Accurate and Interpreta… 93%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering (arXiv v3) | 1 | 93% |
| prior · pull toward the middle | 7% | |
| weighted average | = 16.5 |
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Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json