RLVR
Datasets
All datasets matching “RLVR”rlvr-reward-hacking-scale-no-conftest-20260909-completion
Matched no-conftest RLVR study 20260909-completion
Lossless research records, grouped by model and trajectory type. Only the listed
configurations have published records. Canary diagnostics are excluded from study
estimates; run status in provenance distinguishes retired diagnostics from active
or completed training. Valid failures, refusals and truncations are retained.
The train split name is a dataset-loader convention; record_type identifies
whether a record is training… See the full description on the dataset page: https://huggingface.co/datasets/lucabaroni/rlvr-reward-hacking-scale-no-conftest-20260909-completion.slo-rlvr-resultsRLVR-IFeval
IF Data - RLVR Formatted
This dataset contains instruction following data formatted for use with open-instruct - specifically reinforcement learning with verifiable rewards.
Prompts with verifiable constraints generated by sampling from the Tulu 2 SFT mixture and randomly adding constraints from IFEval.
Part of the Tulu 3 release, for which you can see models here and datasets here.
Dataset Structure
Each example in the dataset contains the standard instruction-tuning… See the full description on the dataset page: https://huggingface.co/datasets/allenai/RLVR-IFeval.Multi-subject-RLVRMulti-subject data for paper "Expanding RL with Verifiable Rewards Across Diverse Domains".
we use a multi-subject multiple-choice QA dataset ExamQA (Yu et al., 2021).
Originally written in Chinese, ExamQA covers at least 48 first-level subjects.
We remove the distractors and convert each instance into a free-form QA pair.
This dataset consists of 638k college-level instances, with both questions and objective answers written by domain experts for examination purposes.
We also use GPT-4o-mini… See the full description on the dataset page: https://huggingface.co/datasets/virtuoussy/Multi-subject-RLVR.math-rlvr-mini-smollm2-0.4b-v2rlvr-reward-hacking-scale-no-conftest-20260909
Matched no-conftest RLVR study 20260909
Complete immutable training, monitoring and comparison trajectories for six models.
All valid outcomes are retained, including refusals, failures and truncations.
The train split name is a dataset-loader convention; record_type identifies
whether a record is training, monitoring, comparison, or a derived judgment.
import json
from datasets import load_dataset
rows = load_dataset("lucabaroni/rlvr-reward-hacking-scale-no-conftest-20260909"… See the full description on the dataset page: https://huggingface.co/datasets/lucabaroni/rlvr-reward-hacking-scale-no-conftest-20260909.