docs: clarify PAIBench-C reproduction seed and prompt format

[Muneerali199]

Closes NVIDIA/cosmos-framework#14

Adds a clarifying note to the transfer cookbook README addressing the two remaining questions from bhack on the PAIBench-C reproducibility issue:

1. Seed: All clips use --seed 2026 as the canonical reference seed
2. Prompt format: Prompts follow the structured prompt.json format shown in assets/*/

The evaluation non-determinism concern is tracked separately at SHI-Labs/physical-ai-bench#7.

[bhack]

But how the structured prompts are generated for the dataset?

Also the problem is not only about reproducibility striclty it is that if you compared with the official PAIBench-C precomputed dataset seg GT it is not reproducible. Have you recomputed source segmentation for your paper/model card?

[lfengad]

@trungtpham for review? THX!

[Muneerali199]

Thanks for looking at this. The structured prompts follow the format in assets/*/prompt.json — basically load that template and fill in the scene params per clip. The generation code is in cookbooks/cosmos3/generator/transfer/.

About the source segmentation — I haven't compared against the official PAIBench-C precomputed GT yet. I'll add a note in the cookbook saying that's still pending and link to the non-determinism tracker (#7) for now. Will follow up once I've done the validation.

[bhack]

I think we are quite far from reproducibility of the model card.

The remaining blocker for PAIBench-C reproduction is the prompt artifact.

PAIBench-C public prompts are natural-language captions in metadata.csv / captions/*.json, while the Cosmos3 cookbook uses a structured prompt.json schema.

Could you clarify exactly how the PAIBench-C captions were converted into Cosmos3 structured prompt.json files for Table 16?

In particular:

1. Were the public PAIBench-C captions used directly, or converted into structured Cosmos3 prompt.json?
2. If converted, was the input metadata.csv caption_text, captions/{task_id}.json, the source video, or some combination?
3. Is the conversion script / system prompt / model available?
4. Are the per-clip structured prompt.json files used for the 600 PAIBench-C examples available?
5. Did the reported Table 16 segmentation result use those structured prompts plus official HF sam2_vids/sam2_pkls, or were source segmentations recomputed?

Without those prompt files or the conversion recipe, the released specs/seed/control settings define the inference shape, but not an exact reproduction of the PAIBench-C table, because the prompt conditioning differs from the public PAIBench-C dataset.