datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
rewardbenchreward-projection-goal-generalisation-vlmllama-3.1-medprm-reward-training-set
Med-PRM-Reward (Version 1.0)
🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its… See the full description on the dataset page: https://huggingface.co/datasets/dmis-lab/llama-3.1-medprm-reward-training-set.rollout_output_reward_qwen3_8b_baserlvr-reward-hacking-transcripts
RLVR reward-hacking full trajectories
This release contains 900 full held-out trajectories from three policies trained with
reinforcement learning from verifiable rewards (RLVR) in a deliberately vulnerable
CodeContests evaluator: 300 each from the final Qwen3.5-9B, GPT-OSS-120B, and Nemotron-3-Super-120B-A12B
checkpoints. Each row preserves the task, tests, complete prompts, native
reasoning, final answer, rendered and sampled token IDs, token log-probabilities, sampling… See the full description on the dataset page: https://huggingface.co/datasets/lucabaroni/rlvr-reward-hacking-transcripts.OpenO1_SFT_ultra_BoN_rewardedrlvr-reward-hacking-mid-checkpoint-transcripts
RLVR reward-hacking mid-checkpoint full trajectories
This release contains 600 full held-out trajectories from intermediate RLVR
checkpoints selected to yield substantially more balanced reward-hacking datasets: 300
from Qwen3.5-9B at optimizer update 110 and 300 from GPT-OSS-120B at update 180.
Each row preserves the task and tests, complete prompts, native reasoning, final answer,
rendered and sampled token IDs, token log-probabilities, sampling metadata, extracted
files… See the full description on the dataset page: https://huggingface.co/datasets/lucabaroni/rlvr-reward-hacking-mid-checkpoint-transcripts.OpenO1_SFT_ultra_BoN_positvie_reward_v3_N-sample65b_rewardedreward-failure-dataset
Reward Failure Dataset
213 structured encodings of RL reward configurations from 134 published papers (1983-2025) across 18 domains. Each entry encodes the reward structure as typed RewardSource objects with provenance, ground truth labels, and static analysis results from the goodhart tool.
Overview
135 documented failures and 78 well-designed rewards
Every entry traces to a published paper with exact section/equation references
Domains: manipulation, game AI… See the full description on the dataset page: https://huggingface.co/datasets/audieleon/reward-failure-dataset.llama-3.1-medprm-reward-raw-training-setdeepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter
deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter
Filtered version of ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.
Filtering
reward filter enabled: False
minimum official reward: 1.0
scoring errors rejected: False
maximum text tokens: 8192
maximum response chars: 65000
near-duplicate SimHash hamming threshold: 4
required <think>...</think> and final boxed answer after reasoning
exact text/problem/response dedupe and near problem… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter.validation_output_reward_qwen3_8b_basellama-3.1-medprm-reward-training-set
Med-PRM-Reward (Version 1.0)
🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its… See the full description on the dataset page: https://huggingface.co/datasets/jysyoh/llama-3.1-medprm-reward-training-set.school-of-reward-hacks-impossible-tests
School of Reward Hacks — Impossible Tests
This is a modified version of the coding problems from the School of Reward Hacks dataset, where one test case per problem is changed to be incompatible with the instruction for the coding task.
Specifically, for each coding problem, one of the provided unit tests has its expected output changed to be subtly incorrect — for example, a palindrome checker being expected to return false for a well-known palindrome. This creates a conflict… See the full description on the dataset page: https://huggingface.co/datasets/oliverdk/school-of-reward-hacks-impossible-tests.gpro_reward_modelso101_pp_donuts_v1_reward_videosimdb_rewardedThis is the imdb dataset, https://huggingface.co/datasets/imdb
We've used a reward / sentiment model, https://huggingface.co/lvwerra/distilbert-imdb to compute the rewards of the offline data.
This is so that we can use offline RL on the data.
reward_model_reddit_adviceJMT-Bench-result_self-rewarding_Mistral-7B-lora
JMT-Bench result
Answer language
JMT-Benchの回答のうち、Englishで回答した件数
Model
Count
mistralai/Mistral-7B-v0.3
25
HachiML/Mistral-7B-v0.3-m1-lora
7
HachiML/Mistral-7B-v0.3-m2-lora
7
HachiML/Mistral-7B-v0.3-m3-lora
2
tulu_delta-learning_Qwen2.5-3B-1.5B_reward-alignedMATH-500-self-rewarding使用self-rewarding方法微调的模型，在math-500上的结果
模型：qwen2.5-7b-insturct
方法：(Self-rewarding correction for mathematical reasoning)[https://arxiv.org/pdf/2502.19613]
Non-Balance-ORM-Llama3-tmp10-N3-Rewardstulu_delta-learning_3B-1.5B_reward-alignedreward-modeling-papers
Reward Modeling Papers — FineSet
A research-paper dataset on Reward Modeling Papers, assembled, deduplicated, and quality-scored by
FineSet from arXiv and Semantic Scholar.
📸 This is a dated snapshot — generated 2026-06-19.
It is not auto-updated. Research on Reward Modeling Papers moves fast — new papers land on arXiv every
week. Want this same dataset refreshed daily, on a topic you choose? See the bottom. ↓
Why this dataset
Quality-scored: quality_score… See the full description on the dataset page: https://huggingface.co/datasets/fineset-io/reward-modeling-papers.skywork-reward-tulu3Balance-ORM-Llama3-tmp10-N3-Rewardsllama-3.1-medprm-reward-raw-test-setNon-Delete-ORM-Llama3-tmp07-N3-Rewardsreward-bench-2-results