AI & ML interests

None defined yet.

Recent Activity

wangbuer999 
posted an update 1 day ago
view post
Post
2024
Hands-on testing of HY-World 2.0 shows a significant improvement in end-to-end engineering maturity compared to version 1.5

The model supports direct multimodal input from text, single-frame images, and video. Inference can be launched without camera intrinsic/extrinsic calibration or additional preprocessing

After panorama generation, the built-in Spatial Agent automatically performs semantic navigation path planning. Combined with spatial consistency constraints from HY-WorldStereo, it ensures artifact-free multi-view generation and stable geometric alignment

Outputs include standard 3D asset formats such as Mesh, 3DGS, and point clouds, which can be directly imported into Unity/UE

It is suitable for engineering scenarios including game level prototyping, digital twins, and embodied simulation
namanvats 
posted an update 5 days ago
view post
Post
3474
Ran a small controlled study on a frozen 40-task slice of Harbor Terminal-Bench-Pro, using the same model (minimax/minimax-m2.5) with two agent harnesses: Goose and OpenHands-SDK.

Under the base setup, reducing the turn budget from 100 to 60 pushed the two harnesses in opposite directions:

* Goose: 0.450 → 0.525
* OpenHands-SDK: 0.575 → 0.500

A tweaked 60-turn setup brought OpenHands-SDK back to 0.575. At their best, both harnesses reached the same 0.575 pass rate.

What surprised me most was the token profile: in this setup, the reported token usage for OpenHands-SDK was dramatically higher than Goose while converging to the same best score.

Same model, same task slice, different harness behavior under a tighter interaction budget.

Dataset:
namanvats/harbor-goose-openhands-benchmark

Code/configs:
https://github.com/namanvats/harbor-agent-ablation