Clean up Isaac 0.5 model card placeholders

README.md

@@ -18,7 +18,7 @@ Isaac 0.5 brings multimodal video understanding, embodied reasoning, spatial gro
 
 To our knowledge, Isaac 0.5 is the first open model operating at the frontier of multimodal video understanding, embodied reasoning, and robot control.
 
-**[Read the paper](REPORT LINK) · [Download the weights](HUGGING FACE LINK) · [View the code](GITHUB LINK)**
+**[Read the paper](REPORT LINK) · [Download the weights](https://huggingface.co/PerceptronAI/Isaac-0.5) · [View the code](GITHUB LINK)**
 
 ## Extending the frontier of open robot learning
 
@@ -64,7 +64,7 @@ $$
 L_{\text{percept}} = \mathbb{E}\left[\ell\left(g_\theta(o_{\leq t}), z_{t+\Delta}\right)\right]
 $$
 
-Here, $o_{\leq t}$ is the observation history and $z_{t+\Delta}$ is the future percept. This objective trains the same backbone Isaac uses to produce actions.
+Here, `o≤t` is the observation history and `z(t + Δ)` is the future percept. This objective trains the same backbone Isaac uses to produce actions.
 
 ## Model architecture
 
@@ -88,11 +88,6 @@ Training examples are packed into 16,384-token sequences with 2% padding across
 
 We evaluate the same Isaac checkpoints across multimodal video understanding, spatial grounding, held-out action prediction, and closed-loop robot control.
 
-- **Video understanding:** [TK-VIDEO RESULT] on [TK-VIDEO EVALUATION]
-- **Pointing:** [TK-POINTING RESULT] on [TK-POINTING EVALUATION]
-- **Tracking:** [TK-TRACKING RESULT] on [TK-TRACKING EVALUATION]
-- **Closed-loop control:** [TK-HEADLINE-RESULT] across [TK-TASKS] standard manipulation tasks under the released protocol
-
 ![Isaac 0.5 perception benchmark scores relative to the best comparator in each family, plotted against inference TFLOP.](isaac_model_card_assets/perception-benchmarks.png)
 
 *Up and to the left is better. Ringed Isaac 0.5 results sit on the frontier; hollow markers are dominated.*
@@ -144,11 +139,9 @@ The release includes:
 
 ## Resources
 
-- **Weights:** [Hugging Face](HUGGING FACE LINK)
+- **Weights:** [Hugging Face](https://huggingface.co/PerceptronAI/Isaac-0.5)
 - **Code:** [GitHub](GITHUB LINK)
 - **Technical report:** [Read the paper](REPORT LINK)
-- **Results and rollouts:** [View results](RESULTS LINK)
-- **Reproduction guide:** [View guide](REPRODUCTION GUIDE LINK)
 
 Open models are essential to robotics progress. We are releasing Isaac 0.5 with its weights, code, interfaces, benchmarks, and manifests so others can inspect, reproduce, and extend the work.