Siyuan Huang, Baoxiong Jia, Jiangyong Huang, Mengya Liu, Jingze Zhang
We lifted 6 functions out of this paper's own repositories and ran 5 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| lmy1001/LARA | canonical | 5 of 6 |
| Function | Status | Where it lives |
|---|---|---|
| swish | Ran | lmy1001/LARA/LARA_full/lara_full/model/action_head/action_encoder.py pointer only (licence: NONE) · get_code("0f786c407fb1ee4c") |
| collate | Ran | lmy1001/LARA/LARA_full/lara_full/model/transforms.py pointer only (licence: NONE) · get_code("7a91a74e5c4b02cd") |
| formalize_language | Ran | lmy1001/LARA/LARA_full/lara_full/model/transforms.py pointer only (licence: NONE) · get_code("50ec0f583ab4f1cd") |
| squeeze_dict_values | Ran | lmy1001/LARA/LARA_full/lara_full/model/policy.py pointer only (licence: NONE) · get_code("b4a7f7844eef1bba") |
| unsqueeze_dict_values | Ran | lmy1001/LARA/LARA_full/lara_full/model/policy.py pointer only (licence: NONE) · get_code("3dffd60cbc50e250") |
| build_eagle_processor | Not yet run | lmy1001/LARA/LARA_full/lara_full/model/transforms.py pointer only (licence: NONE) · get_code("5e7999ebef31c22e") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
ment. This enables reciprocal benefits where LAMs learn with action trajectories to avoid spurious visual changes, while VLAs are regularized by forward dynamics learned within LAMs to reduce hallucinations of functionally ineffective trajectories. We demonstrate LARA's versatility and effectiveness for pre-training, post-training enhancement of pre-trained VLA models, and LAM refinement, achieving an average of ∼10%, ∼5%, and ∼15% improvement over 3 simulation and 1 meticulously designed real-world robotic manipulation benchmarks. The code is publicly available at https://github.com/lmy1001/LARA.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2606.07100")
get_code_for_paper("2606.07100")
have("2606.07100")
Connect an agent — have() is free.