datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
knowledge-base
RL-for-LLMs Wiki
An expert-level, citation-backed knowledge base on reinforcement learning for
large language models — RLHF, DPO and offline preference optimization, reward
modeling, RLVR and reasoning, training systems, and the failure modes — built
collaboratively by autonomous agents. Each topic article is a deep dive written
so you can learn the topic from it without reading the underlying papers, with
every non-obvious claim cited to a source. Every change lands through a… See the full description on the dataset page: https://huggingface.co/datasets/rl-llm-wiki/knowledge-base.course-imagesbridge-rlds
Dataset Structure
These datasets are used for MemoryVLA training.
This is the standard setting and can be directly used for other models as well.All data follow the RLDS format from the Bridge dataset.
bridge_orig — 60k+ episodes, widowx robot
hh-rlhf
Dataset Card for HH-RLHF
Dataset Summary
This repository provides access to two different kinds of data:
Human preference data about helpfulness and harmlessness from Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. These data are meant to train preference (or reward) models for subsequent RLHF training. These data are not meant for supervised training of dialogue agents. Training dialogue agents on these data is likely… See the full description on the dataset page: https://huggingface.co/datasets/Anthropic/hh-rlhf.RW-RL-Dataset
RW-RL Dataset: Real-World Reinforcement Learning for Robots
Human-intervention companion dataset: RW-RL-HIL-Dataset (BodenAI) is a separately hosted release of real-world policy rollouts and human corrections. Download it from its own dataset page.
RW-RL Dataset is a real-world robot interaction dataset released by Boden Intelligence, Junpu Innovation Center, and the MINT Lab at Shanghai Jiao Tong University. It is designed for a bottleneck that… See the full description on the dataset page: https://huggingface.co/datasets/MINT-SJTU/RW-RL-Dataset.mikasa-robo-vla-rldsSpreadsheet-RL
Spreadsheet-RL Dataset
Project Page | Paper | GitHub | Model
This dataset contains the training and evaluation data used by Spreadsheet-RL, a reinforcement learning framework for spreadsheet agents that edit Excel workbooks with tools and receive outcome-based rewards from workbook recalculation and answer-range comparison.
News
🚀 2026-08-01: Released the Spreadsheet-RL-8B checkpoint, scaling SpreadsheetBench Pass@1 from 15.9% for the base model to 16.7%… See the full description on the dataset page: https://huggingface.co/datasets/Spreadsheet-RL/Spreadsheet-RL.modified_libero_rlds
Modified LIBERO RLDS Datasets
This repository contains the four modified LIBERO datasets
used in the OpenVLA fine-tuning experiments, stored in RLDS data format. See Appendix E in the
OpenVLA paper for details about the fine-tuning experiments and
specific dataset modifications, and see the OpenVLA GitHub README
for instructions on how to run OpenVLA in LIBERO environments.
Citation
BibTeX:
@article{kim24openvla,
title={OpenVLA: An Open-Source… See the full description on the dataset page: https://huggingface.co/datasets/openvla/modified_libero_rlds.RECAP-Libero10-Task0-48succ-Datarl-lm-formality-promptsrl-lm-imdb-promptsUltraData-RL-2609
UltraData-RL-2609
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
UltraData-RL-2609 is the L3 refined data for reinforcement learning within UltraData's L0-L4 tiered data management framework. Built for the RL stage of MiniCPM5-2B post-training, it complements UltraData-SFT-2605 with verifiable-reward tasks. It is also the training corpus used by JustRL II (Scaling Small LLMs to 128K Reasoning with a Critic)… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-RL-2609.rl-lm-toxicity-promptsNuminaMath-1.5-RL-Verifiable
Dataset Card for NuminaMath-1.5-RL-Verifiable
Dataset Summary
NuminaMath-1.5-RL-Verifiable is a curated subset of the NuminaMath-1.5 dataset, specifically filtered to support reinforcement learning applications requiring verifiable outcomes. This collection consists of 131,063 math word problems from the original dataset that meet strict filtering criteria: all problems have definitive numerical answers, validated problem statements and solutions, and come from… See the full description on the dataset page: https://huggingface.co/datasets/nlile/NuminaMath-1.5-RL-Verifiable.LIBERO-assetsLIBERO-PRO-assetsOpenFly-rldsrlvr-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.rlds_deltaXHRBench
XHRBench
Ultra-High-Resolution Remote Sensing Understanding and Reasoning
🤗 Hugging Face ·
🤖 ModelScope ·
📄 Paper ·
💻 Code
English | 中文
📚 Introduction
XHRBench evaluates fine-grained perception and complex reasoning in multimodal large language models using ultra-high-resolution remote-sensing imagery. This repository retains the name XHRBench and belongs to the same RSHR benchmark project as RSHR-Bench, with a… See the full description on the dataset page: https://huggingface.co/datasets/RL-MIND/XHRBench.rl-run-archive-2026
RL run archive 2026
Archived raw run artifacts (rollout trajectories, rendered frames, policy and optimizer
checkpoints, configs, logs) from simulation reinforcement-learning experiments, published for
long-term preservation and reproducibility.
Layout mirrors the verified backup trees they were copied from:
tilde/20260915-102000/ and taurus/20260915-085631/: batched tar archives. Every archive
carries a per-file SHA-256 manifest inside it; the batch inventories (9998.json.gz… See the full description on the dataset page: https://huggingface.co/datasets/gavinlaw/rl-run-archive-2026.Agriculture-Agent-RL-Training-Data
Agriculture Agent RL Training Data
A growing dataset of RL rollout trajectories for LLM agents on
natural/regenerative farming — the first RL/trajectory-shaped dataset in the
Copyleft Cultivars collection
(every prior dataset here is SFT/conversational Q&A). Agents call real tools
(primarily cultivars-mcp,
a plant-genomics MCP server) across 9 knowledge categories (plus a 10th,
organic_chemistry_soil_science, added 2026-08-11, and an 11th,
organic_chemistry_synthesis, added… See the full description on the dataset page: https://huggingface.co/datasets/CopyleftCultivars/Agriculture-Agent-RL-Training-Data.rl-pythonRPent-memory
RPent Memory
Memory dataset used by RPent.
Memory is organized per robot with a shared contract:
<robot>/
├── MEMORY.md
├── global/
├── suite/
└── task_only/
├── <cell>.json
├── <cell>_recipe.jsonl
└── <task_key>.md
Each robot provides the layers it uses. RoboCasa requires its global file
when running with the default task-global policy.
Current layout:
libero/
├── MEMORY.md
├── global/
├── suite/
├── task_only/
└── task_card/
robocasa/
├── task_only/
└── global/… See the full description on the dataset page: https://huggingface.co/datasets/RLinf/RPent-memory.Reverse-Text-RL
Reverse-Text-RL
A small, scrappy RL dataset used in prime-rl's CI to debug RL training asking a model to reverse small sentences character-by-character. Follows the general format of PrimeIntellect/Reverse-Text-SFT
The following script was used to generate the dataset.
from datasets import Dataset, load_dataset
dataset = load_dataset("willcb/R1-reverse-wikipedia-paragraphs-v1-1000", split="train")
prompt = "Reverse the text character-by-character. Put your answer in… See the full description on the dataset page: https://huggingface.co/datasets/PrimeIntellect/Reverse-Text-RL.Big-Math-RL-Verified
Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
Big-Math is the largest open-source dataset of high-quality mathematical problems, curated specifically for reinforcement learning (RL) training in language models. With over 250,000 rigorously filtered and verified problems, Big-Math bridges the gap between quality and quantity, establishing a robust foundation for advancing reasoning in LLMs.
Request Early Access to Private… See the full description on the dataset page: https://huggingface.co/datasets/SynthLabsAI/Big-Math-RL-Verified.slo-rlvr-resultsMulti-SWE-RL-Verified
Multi-SWE-RL-Verified
Gold-patch-validated subset of
PrimeIntellect/Multi-SWE-RL-Reupload
(ByteDance's Multi-SWE-RL): 2,232 / 4,703 rows across
C, Go, Java, JavaScript, Rust, and TypeScript that produce a clean reward signal end-to-end.
Default dataset of the multiswe_v1 taskset.
Changes vs upstream
Starting from the 4,703-row re-upload:
C++ dropped wholesale — 0/449 rows passed gold-patch validation in pass 1; the images are
broken for scoring, not merely… See the full description on the dataset page: https://huggingface.co/datasets/PrimeIntellect/Multi-SWE-RL-Verified.hle-gpt-oss-120b-no-python-260222
hle-gpt-oss-120b-no-python-260222
Deep research agent evaluation on rl-rag/hle_text_only (test split).
Results
Metric
Value
pass@4
47.9%
avg@4
26.6%
Trajectory accuracy
26.6% (2292/8632)
Questions
2158
Trajectories
8632 (4 per question)
Avg tool calls
14.5
Full conversations
❌
Model & Setup
Model
gpt-oss-120b
Judge
gpt-4o
Max tool calls
50
Temperature
0.7
Blocked domains
huggingface.co
Tool Usage… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/hle-gpt-oss-120b-no-python-260222.KodCode-Light-RL-10K
🐱 KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding
KodCode is the largest fully-synthetic open-source dataset providing verifiable solutions and tests for coding tasks. It contains 12 distinct subsets spanning various domains (from algorithmic to package-specific knowledge) and difficulty levels (from basic coding exercises to interview and competitive programming challenges). KodCode is designed for both supervised fine-tuning (SFT) and RL tuning.
🕸️… See the full description on the dataset page: https://huggingface.co/datasets/KodCode/KodCode-Light-RL-10K.