Daily Report — 2026-06-27
Overview of Daily Work
- Completed Tasks: Performed A/B testing to improve the accuracy of visual instruction arrows generated by Cosmos3-Nano in robot demonstration videos.
- Implementation Methods: Modified inference parameters (standardized [0,1000] coordinates, scaled input to 480p, set temperature = 0), and implemented a simplified single-arrow visualization script for comparison tests.
- Results: Converted blurred model outputs into clear, actionable direction indicators, verified the model’s potential as a zero-sample annotator, and identified time constraints under static camera settings.
Optimization of Cosmos3-Nano’s visual instruction generation through coordinate standardization, resolution scaling, and temperature control improved the qualitative usability of robot task annotations.
Tasks
Architecture and Strategy
- ✅ Visual instruction parameter optimization — Diagnosed coordinate misalignment and low resolution issues, then implemented three specific fixes: standardizing coordinates to [0,1000], scaling input to 480x480, and reducing temperature to 0 for deterministic output.
Implementation and Fixes
- ✅ A/B testing execution — Ran base and improved configurations (successful and failed cases) on specific demonstration videos, downloaded results, and compared arrow orientation accuracy.
- ✅ Visualization simplification — Optimized output visualization to display only a single arrow, removing circular and multi-step indicators as requested by users.
- ✅ Server resource management — Downloaded all comparison assets to local storage and safely terminated Cosmos3-Nano vLLM service on remote servers to release GPU resources.
Issues and Solutions
Key Issues
1. AI-generated arrows were inaccurate and unevenly distributed because the model’s assumed image size (608x480) did not match the actual video resolution (256x256), coupled with the impact of low-resolution details.
Solution: Implemented coordinate standardization to [0,1000] in the prompt, scaled input frames to 480p to better detect features, and set temperature to 0 to eliminate sampling noise.
Key Insight: These three modifications have independent value; coordinate standardization and resolution scaling are crucial for geometric accuracy, while temperature control ensures analytical certainty of temporal features.
General Issues
2. The remote vLLM process was not terminated initially due to a command-line mode mismatch (“vllm serve” matching the SSH command itself).
Solution: Adjusted the pkill regular expression pattern to exclude the current shell environment (e.g., using “Cosmos3-Na[n]o”), successfully terminated the process, and released GPU resources.
Key Insight: When debugging remote processes, attention should be paid to regular expression patterns to avoid self-termination or incomplete termination.
Human and AI Approaches
Implementation Level
Visual Complexity Limitation
| Role | Method |
|---|---|
| Human | Users explicitly requested simplified visualization (“only one arrow, no other content”) to reduce cognitive load and focus on direction intent. |
| AI | AI initially provided complex visualizations with multiple markers (circles, dots, step 1/2 arrows), which were then adjusted to a simplified form as required. |
Analysis of Differences: Humans clearly aim for clarity and simplicity, while AI defaults to maximum information density. Human intervention simplified evaluation metrics to focus solely on the geometric shape of the arrow.
AI Limitations
Key Limitations
- AI incorrectly assumed video size (reported as 608x480, actual 256x256), leading to systematic coordinate distortion in early outputs.
General Limitations
- Unable to demonstrate better temporal reasoning capabilities because the input video used is a static third-person camera, and frame-by-frame prediction tends to match segment-based predictions.
Learning Outcomes
Key Takeaways
- Using standardized coordinates (e.g., [0,1000]) in prompts significantly improves the geometric accuracy of VLMs with inconsistent internal image sizes.
Practical Takeaways
- To isolate the impact of temporal context in video models, temperature must be set to 0 in ablation studies; otherwise, sampling noise obscures the true contribution of time segments.
Dialogue Summary
✅ Cosmos3-Nano Visual Instruction A/B Test 04:00:06.583 | claude_code Users requested improved accuracy of visual instructions generated by Cosmos3-Nano. We identified coordinate mismatch and low resolution as main issues. Implemented three fixes: standardizing coordinates to [0,1000], scaling input to 480p, and setting temperature = 0. A/B testing of base and improved outputs showed that the modified parameters produced arrows that correctly pointed to target objects (e.g., above, toaster handle). At the end of the session, all assets were downloaded to local storage and the remote server was shut down.