InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy
Python · active 2025-09-17 → 2026-05-16 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 242 days from 2025-09-17 to 2026-05-16. Pushes: 27 total, peak 11 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 24 total, peak 7 in a day. Comments: 41 total, peak 4 in a day. Stars: 175 total, peak 28 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| JinhuiYE | 17 | 7 | 0 | 9 |
| chenyilun95 | 11 | 4 | 0 | 0 |
| Yioutpi | 10 | 9 | 0 | 1 |
| MichaelYu781 | 9 | 6 | 0 | 3 |
| godnpeter | 9 | 0 | 0 | 8 |
| Axi404 | 8 | 1 | 0 | 7 |
| Vilonge | 4 | 0 | 0 | 3 |
| songlin | 4 | 0 | 0 | 1 |
| zhengyuan-xie | 3 | 0 | 0 | 1 |
| Tgzz666 | 2 | 0 | 0 | 1 |
| vajDog | 2 | 0 | 0 | 1 |
| zhengsipeng | 2 | 0 | 0 | 0 |
| SlenderMongoose | 2 | 0 | 0 | 1 |
| njusz-ocx | 1 | 0 | 0 | 1 |
| GuaGuaGod | 1 | 0 | 0 | 0 |
| hamondyan | 1 | 0 | 0 | 1 |
| JiehongLin | 1 | 0 | 0 | 1 |
| zmf2022 | 1 | 0 | 0 | 0 |
| fanchenlex | 1 | 0 | 0 | 1 |
| D222097 | 1 | 0 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
- Issue comment#7hamondyan2026-04-17 07:14performance on simplerenv
- Issue comment#31Mountchicken2026-02-27 00:21[Question] Semantic labels in InternData-M1
- Issue comment#27Axi4042026-01-17 09:58Depth maps
- Issue comment#28MichaelYu7812026-01-16 09:51Guidance on Action-Only Fine-tuning on LIBERO using train_internvla.py
- Issue comment#27godnpeter2026-01-15 16:36Depth maps
- Issue comment#27godnpeter2026-01-14 06:45Depth maps
- Issue comment#26SlenderMongoose2026-01-08 14:45Unexpected garbled output when using LIBERO fine-tuned checkpoints
- Issue comment#27Axi4042026-01-04 10:03Depth maps
- Issue comment#21Axi4042025-12-26 08:43occlusionRatio: Meaning, range, and interpretation
- Issue comment#17Axi4042025-12-26 08:40Clarification on camera intrinsics/extrinsics used in the InternData-M1 dataset
- Issue#23chenyilun952025-12-24 07:13Abou the task planning data in pre-training
- Issue#24chenyilun952025-12-24 07:12add robot state
- Issue#20chenyilun952025-12-24 07:12lerobot dataset load fail
- Issue#17chenyilun952025-12-24 07:12Clarification on camera intrinsics/extrinsics used in the InternData-M1 dataset
- Issue#16chenyilun952025-12-24 07:11Camera's Extrinsic Parameters
- Issue#15chenyilun952025-12-24 07:11Clarification on how LIBERO-long results are computed (long90 + long10)
- Issue#7chenyilun952025-12-24 07:11performance on simplerenv
- Issue#26SlenderMongoose2025-12-20 09:29Unexpected garbled output when using LIBERO fine-tuned checkpoints
- Issue comment#17godnpeter2025-12-02 04:37Clarification on camera intrinsics/extrinsics used in the InternData-M1 dataset
- Issue comment#22Axi4042025-11-30 06:20Question about Interndata-M1's orientation, euler or axis_angle?
- Issue comment#17Vilonge2025-11-27 08:54Clarification on camera intrinsics/extrinsics used in the InternData-M1 dataset
- Issue comment#17Axi4042025-11-27 05:28Clarification on camera intrinsics/extrinsics used in the InternData-M1 dataset
- Issue comment#17Vilonge2025-11-26 04:38Clarification on camera intrinsics/extrinsics used in the InternData-M1 dataset
- Issue#22zhengsipeng2025-11-22 10:15Question about Interndata-M1's orientation, euler or axis_angle?
- Issue comment#17godnpeter2025-11-19 05:52Clarification on camera intrinsics/extrinsics used in the InternData-M1 dataset
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 175 stars here means stars gained during the window, not the repo's star count.