Tier-Flow/LoopVL
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About the project
LoopVL is a vision-language model that reuses Transformer modules across recurrent computation (L→L→L→H schedule, 128 effective layer applications per forward pass). The repo provides inference code, evaluation on 16 benchmarks, and experiments on visual attention.
Useful for
- Ask a question about an image via runtime/infer.py with a token budget
- Run the 16-dataset benchmark suite (MMStar, POPE, etc.) on one or more GPUs
- Reproduce paper experiments: attention plots and hidden-state dynamics
README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.
Star growth looks organic. Data as of October 5, 2026, 11:14 UTC.
The star-growth assessment does not verify whether the project is safe to run.
Stars per day
Bars show daily stars; the line is a moving average of the available history. Short histories do not yet establish a reliable usual pace. Red marks spike days.
Why it’s trending
- There are not enough fresh counter measurements for today's UTC day. The gain is unknown.
- The repository is 4 days old and already has 93 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #139.
Three GitHub discoveries in each edition
What they do, why they are gaining interest, and what to check before using them.
Editions at 10:00, 16:00, 22:00 MSK.
Numbers
- Total stars
- 93
- Today
- Not enough measurements today
- Forks
- 1
- Issues and pull requests
- 1
- Watchers
- 2
- Language
- Python
- License
- Apache-2.0
- Latest release
- benchmark-assets-v1 · October 1, 2026
- Created
- October 1, 2026
- Last push
- October 1, 2026
Star trust
Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.
These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.
Spotted in
- October 5, 2026Top new repositories this week: #139