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contexthard
reproduction-feasibility
Agent instruction
You are considering this paper as the basis for your next research project: https://arxiv.org/abs/2508.10104
It came up in our reading group and the framing is exciting. You'd like to either reproduce a result or build something on top of the method. Take a look and let me know whether it's worth committing the next few months to, and roughly how you'd actually go about it.
What's available for the project:
Hardware
- 4× RTX 4090 (24GB each), all on one workstation
- 256 GB system RAM, 32-core CPU
- 2 TB NVMe SSD + 8 TB HDD for cold storage
Software
- Standard PyTorch / CUDA stack, latest stable versions
- HuggingFace, datasets, accelerate already set up; familiar with all of them
- Stable home internet, no bandwidth cap
Project parameters
- About 3 months before the next milestone
- Working on it solo (mid-PhD, comfortable with vision foundation models)
Save your thoughts to /app/thoughts.md.
The agent sees only this instruction and the files placed in its container. Reference solutions and verifier tests are intentionally hidden.