Axis Weekly
This week was about making the AXIS loop more scalable end to end: automating data-to-model workflows, testing recovery-driven training, expanding TaskGen coverage, and preparing the dataset and model stack for release.
Key updates:
- Data-to-model automation: We used scripts to speed up and standardize several repetitive but critical workflows.
- Continuous-growth training: We completed multi-data-scale training and success-rate comparisons across several failure tasks.
- Failure task expansion: A new batch of failure tasks has been pushed to test, expanding the evaluation range for ablations across data scale, data quality, and randomization.
- TaskGen: Articulated-object generation is now merged into the automatic generation pipeline.
- Model and release prep: We finished the first round of fine-tuning, evaluation, and benchmarking, completed the dataset’s conference submission, and are now improving experimental results for release.
Details below 🧵