Publish SimReadyBench under HCLTech Robotics

README.md

@@ -3,15 +3,12 @@ language:
 - en
 license: other
 license_name: mixed-mit-and-nvidia-source-license
-license_link: https://huggingface.co/datasets/chrisvoncsefalvay/simreadybench-results/blob/main/NVIDIA-ASSET-LICENSE.txt
+license_link: https://huggingface.co/datasets/hcltech-robotics/simreadybench/blob/main/NVIDIA-ASSET-LICENSE.txt
 pretty_name: SimReadyBench results
+thumbnail: https://huggingface.co/datasets/hcltech-robotics/simreadybench/resolve/main/media/social-card.png
 authors:
 - name: Chris von Csefalvay
   affiliation: HCLTech
-- name: Achyuthan Unni Krishnan
-  affiliation: HCLTech
-- name: Pranav Doma
-  affiliation: HCLTech
 - name: Tamas Foldi
   affiliation: HCLTech
 configs:
@@ -76,16 +73,16 @@ tags:
 ---
 # SimReadyBench
 
-[Chris von Csefalvay](https://github.com/chrisvoncsefalvay), Achyuthan Unni Krishnan, Pranav Doma and Tamas Foldi  
+[Chris von Csefalvay](https://github.com/chrisvoncsefalvay) and Tamas Foldi  
 **HCLTech**
 
-[Code](https://github.com/chrisvoncsefalvay/simreadybench) | [NV25 public reference set](https://github.com/chrisvoncsefalvay/simreadybench/blob/main/src/simready_bench/resources/benchmarks/nvidia-25.json) | [Leaderboard](https://huggingface.co/datasets/chrisvoncsefalvay/simreadybench-results/blob/main/leaderboard.json) | [Reconstruction readouts](https://huggingface.co/datasets/chrisvoncsefalvay/simreadybench-results/tree/main/runs)
+[Project page](https://hcltech-robotics.github.io/simreadybench/) | [Paper (coming soon)](https://hcltech-robotics.github.io/simreadybench/#paper) | [Code](https://github.com/hcltech-robotics/simreadybench) | [NV25 public reference set](https://github.com/hcltech-robotics/simreadybench/blob/main/src/simready_bench/resources/benchmarks/nvidia-25.json) | [Leaderboard](https://huggingface.co/datasets/hcltech-robotics/simreadybench/blob/main/leaderboard.json) | [Reconstruction readouts](https://huggingface.co/datasets/hcltech-robotics/simreadybench/tree/main/runs)
 
 SimReadyBench measures how well models reconstruct simulation-ready USD assets from reference images, an authoring brief and nominal dimensions. Models, agent harnesses and authoring skills are independent experimental factors. Evaluation reports three independent composite scores: formal fidelity, visual fidelity and kinematic fidelity.
 
 ## Reference sets
 
-NV25 and NV100 are distinct public reference sets, separate from the withheld internal benchmark reference set. The packaged [`nvidia-25` manifest](https://github.com/chrisvoncsefalvay/simreadybench/blob/main/src/simready_bench/resources/benchmarks/nvidia-25.json) defines NV25, which contains 25 NVIDIA SimReady assets.
+NV25 and NV100 are distinct public reference sets, separate from the withheld internal benchmark reference set. The packaged [`nvidia-25` manifest](https://github.com/hcltech-robotics/simreadybench/blob/main/src/simready_bench/resources/benchmarks/nvidia-25.json) defines NV25, which contains 25 NVIDIA SimReady assets.
 
 ## Evaluation protocol
 
@@ -197,7 +194,7 @@ Units and up-axis are normalised to metres/Z-up, then one whole-object translati
 | Joints | Joint count, type, connectivity, enabled state, anchors, relative frames, axes and limits |
 | Materials | Supported surface properties, UV textures and authored friction, restitution, density and combine modes |
 
-The structured `composite_scores` readout retains each composite's factors, earned credit, eligible denominators, measured counts, coverage and score bounds. Unknown measurements remain null and criteria absent from the reference are not applicable. Candidate omissions of eligible properties receive no credit. The [evaluation guide](https://github.com/chrisvoncsefalvay/simreadybench/blob/main/docs/evaluation.md) defines the comparison bands and component calculations.
+The structured `composite_scores` readout retains each composite's factors, earned credit, eligible denominators, measured counts, coverage and score bounds. Unknown measurements remain null and criteria absent from the reference are not applicable. Candidate omissions of eligible properties receive no credit. The [evaluation guide](https://github.com/hcltech-robotics/simreadybench/blob/main/docs/evaluation.md) defines the comparison bands and component calculations.
 
 ## Orientation-aligned comparison
 
@@ -213,7 +210,7 @@ Reference observations cover geometry, physical structure and material appearanc
 
 ## Readouts and leaderboard
 
-[Reconstruction readouts](https://huggingface.co/datasets/chrisvoncsefalvay/simreadybench-results/tree/main/runs) group completed reconstructions by evaluation configuration. Each readout contains a browsable report, a score table and the generated assets and evaluation files:
+[Reconstruction readouts](https://huggingface.co/datasets/hcltech-robotics/simreadybench/tree/main/runs) group completed reconstructions by evaluation configuration. Each readout contains a browsable report, a score table and the generated assets and evaluation files:
 
 ```text
 runs/<run-id>/
@@ -224,25 +221,34 @@ runs/<run-id>/
   evidence/<asset-id>/reconstruction-<n>/
 ```
 
-The dataset viewer displays the score tables. The [leaderboard](https://huggingface.co/datasets/chrisvoncsefalvay/simreadybench-results/blob/main/leaderboard.json) summarises complete NV25 evaluations with four reconstructions per asset, while individual readouts retain the measurements for every completed reconstruction.
+The dataset viewer displays the score tables. The [leaderboard](https://huggingface.co/datasets/hcltech-robotics/simreadybench/blob/main/leaderboard.json) summarises complete NV25 evaluations with four reconstructions per asset, while individual readouts retain the measurements for every completed reconstruction.
 
 ## Evaluate a model
 
-Install with Python 3.12 and set `DAYTONA_API_KEY` and the credentials required by the model provider, then run:
+Use Python 3.12 in a Linux or WSL shell. Set `DAYTONA_API_KEY` and the credentials required by the model provider, then install the package and import the published runtime:
 
 ```sh
-git clone https://github.com/chrisvoncsefalvay/simreadybench.git
+git clone https://github.com/hcltech-robotics/simreadybench.git
 cd simreadybench
-python -m pip install -e '.[daytona,publish]'
+python3.12 -m venv .venv
+. .venv/bin/activate
+python -m pip install '.[daytona,publish]'
+simready-bench setup daytona --output ../simreadybench-runtime.json
+```
 
+Run the benchmark with the saved runtime configuration:
+
+```sh
 simready-bench benchmark nvidia-25 --repetitions 4 \
   --model MODEL_ID --harness pi --deploy daytona \
-  --max-spend-usd 250 --output-dir ../simreadybench-results
+  --runtime-images ../simreadybench-runtime.json \
+  --authoring-turns 64 --workers 4 --supervise \
+  --output-dir ../simreadybench-results
 ```
 
-Replace `MODEL_ID` with the model identifier and add `--skills PATH` for an authoring skill condition. Use `--deploy local` on a configured Linux Docker host. Add `--hf-repo your-org/your-results --hf-run your-run-id` to publish completed reconstruction readouts to a Hugging Face dataset.
+Replace `MODEL_ID` with the model identifier and add `--skills PATH` for an authoring skill condition. Add `--max-spend-usd AMOUNT` to set a separate monetary ceiling. For local execution, follow the deployment guide to configure a Linux Docker host, then use `--deploy local` with its `local-runtime-images.json`. Add `--hf-repo your-org/your-results --hf-run your-run-id` to publish completed reconstruction readouts to a Hugging Face dataset.
 
-The [quickstart](https://github.com/chrisvoncsefalvay/simreadybench/blob/main/docs/quickstart.md) covers model evaluation and result inspection, and the [deployment guide](https://github.com/chrisvoncsefalvay/simreadybench/blob/main/docs/deployment.md) describes the local and Daytona runtimes.
+The [quickstart](https://github.com/hcltech-robotics/simreadybench/blob/main/docs/quickstart.md) covers model evaluation and result inspection, and the [deployment guide](https://github.com/hcltech-robotics/simreadybench/blob/main/docs/deployment.md) describes the local and Daytona runtimes.
 
 ## Citation
 
@@ -250,12 +256,11 @@ The [quickstart](https://github.com/chrisvoncsefalvay/simreadybench/blob/main/do
 @software{simreadybench2026,
   title = {SimReadyBench: Evaluating models, harnesses and skills
            for simulation-ready asset generation},
-  author = {Chris {von Csefalvay} and Achyuthan {Unni Krishnan}
-            and Pranav Doma and Tamas Foldi},
+  author = {Chris {von Csefalvay} and Tamas Foldi},
   organization = {HCLTech},
   year = {2026},
   version = {1.0.0},
-  url = {https://github.com/chrisvoncsefalvay/simreadybench}
+  url = {https://github.com/hcltech-robotics/simreadybench}
 }
 ```