domain-rl-data / README.md
shkim0824's picture
Add files using upload-large-folder tool
3861604 verified
|
Raw History Blame Contribute Delete
1.74 kB
metadata
language:
  - en
task_categories:
  - text-generation
tags:
  - mmopd
configs:
  - config_name: finance
    data_files: data/finance.jsonl
  - config_name: if
    data_files: data/if.jsonl

domain-rl-data

RL (GRPO) prompts of the two RL domain teachers (Finance, IF) of No Pain, More Gain: Iterative Merging for Effective Multi-Teacher On-Policy Distillation (code).

Subset Rows Content
finance 7,565 numeric-answer prompts from the training splits of FinQA and TAT-QA (MMOPD/Qwen3-4B-OT3-finance)
if 11,728 verifiable instruction-following prompts from the rlvr1 blend of nvidia/Nemotron-RL-Ultra-Training-Blends (MMOPD/Qwen3-4B-OT3-if)

Format

One JSON object per line.

  • finance: input = question with the report table and text, output = numeric answer, meta = source and answer scale.
  • if: messages = [user prompt], instruction_id_list and kwargs = the verifiable instructions and their arguments.

Sources

FinQA, TAT-QA, nvidia/Nemotron-RL-Ultra-Training-Blends. Please follow the licenses of the source datasets.

Citation

@article{kim2026immopd,
  title   = {No Pain, More Gain: Iterative Merging for Effective Multi-Teacher On-Policy Distillation},
  author  = {Kim, Seonghyeon and Jang, Chaeyun and Lee, Noah and Kim, Boseop and Lee, Juho},
  journal = {arXiv preprint arXiv:2609.34745},
  year    = {2026}
}