Nemotron-RL-QA-Abstention-v1

Nemotron-RL-QA-Abstention-v1** License: cc-by-4.0 Language: en Task Categories: reinforcement-learning, question-answering, text-generation Tags: abstention, question-answering, hotpotqa, software-engineering, health, law, rl, rlvr Configs: default train split at data/train.jsonl Domain: multi-domain question answering, abstention Modality: text Capability Breakdown: Abstention-aware factoid question answering [100%] Source: Hybrid: Automated, Manually Collected, Synthetic Size Bin: License/Terms of Use: This dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). Intended Usage: This dataset is intended for: Reinforcement learning with verifiable rewards (RLVR) of LLMs on abstention-aware factoid question answering. Training models to answer in `\\boxed{answer}` format when confident. Training models to output `\\boxed{[IDK]}` instead of guessing when uncertain. Multi-domain QA training across HotpotQA, software engineering, health, and law. Reducing hallucination by rewarding abstention when a question cannot be answered reliably. Dataset Characterization Dataset Composition and Generation Problem Sources The dataset contains: HotpotQA public benchmark examples. Go standard library documentation examples. Health QA examples from Wikipedia medical articles. Law QA examples from Wikipedia legal articles. CRAG Finance is not included in this release. Curation and Filtering Source documents are collected and long documents are chunked into approximately 800-token passages. Each chunk is passed to Nemotron-3-Super-120B to generate six grounded factoid QA pairs. Generated pairs are filtered by answer length, question format, and `\\boxed{answer}` validity. Questions are deduplicated against the AA-Omniscience evaluation set using 3-gram Jaccard similarity with threshold 0.3. The training file contains no assistant responses; records are system/user inputs for online RL rollouts. Each record preserves the source QA fields, including the targ