Datasetpublic

lihaoxin2020/agentic-search-refiner-shortform-curated-v1

Agentic Search Refiner Shortform Curated v1 Curated short-form QA mixture for /home/nvidia/workspace/dr-tulu/rl/open-instruct/run_train_refiner_shortform_api_agent.sh. This dataset is normalized to the ASearcher-compatible schema expected by rlvr_tokenize_asearcher_v1: question: user query answer: exact reference answer as a string source, subset, source_id, metadata: provenance/debug fields Composition { "asearcher_lrm_multihop": 300… See the full description on the dataset page: https://huggingface.co/datasets/lihaoxin2020/agentic-search-refiner-shortform-curated-v1.

sourceHugging Faceotherupdated 5mo agoView on Hugging Face

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Dataset Card

Agentic Search Refiner Shortform Curated v1

Curated short-form QA mixture for /home/nvidia/workspace/dr-tulu/rl/open-instruct/run_train_refiner_shortform_api_agent.sh.

This dataset is normalized to the ASearcher-compatible schema expected by rlvr_tokenize_asearcher_v1:

—question: user query
—answer: exact reference answer as a string
—source, subset, source_id, metadata: provenance/debug fields

Composition

json

{
  "asearcher_lrm_multihop": 300,
  "asearcher_lrm_webwalker_chain": 300,
  "webaggregatorqa_train": 300,
  "webexplorerqa": 100,
  "webshaper": 500
}

Total rows: 1500.

Curation

—WebShaper: all rows with non-empty question/answer retained.
—WebExplorerQA: all rows with non-empty question/answer retained.
—ASearcher LRM web/search-hard slice: 150 English-like train_v1:webwalker_hard and 150 English-like chain_qa_fuzzy rows, with approximate deduplication.
—ASearcher LRM multi-hop slice: 200 unlabeled LRM multi-hop-style rows and 100 train_v1:compose_group_qa rows, with approximate deduplication.
—WebAggregatorQA train: 300 rows with scalar answers, real URL context, no placeholder/sample-only answers, and topic/answer repetition caps.

Intended Use

Use as a single JSONL/Hugging Face dataset in the short-form API-agent refiner RL run:

bash

DATASET_LIST="lihaoxin2020/agentic-search-refiner-shortform-curated-v1 1.0" DATASET_SPLIT=train \
  bash /home/nvidia/workspace/dr-tulu/rl/open-instruct/run_train_refiner_shortform_api_agent.sh

Local mirror:

bash

DATASET_LIST="/home/nvidia/workspace/data/agentic_search_refiner_shortform_curated_v1.jsonl 1.0" DATASET_SPLIT=train \
  bash /home/nvidia/workspace/dr-tulu/rl/open-instruct/run_train_refiner_shortform_api_agent.sh

See manifest.json for exact counts, filter notes, and representative examples.