datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
agents-last-exam-data
Agents Last Exam — Task Input Data
Input files (the materials each task hands to the agent at run start) for the
Agents Last Exam (ALE) benchmark. Browsable per-task directory layout.
The Agents Last Exam dataset family
ALE is published as three companion HuggingFace datasets:
Dataset
Contents
Access
Task Card Metadata
One row per task: titles, prompts, taxonomy, input-file descriptors
Open
Task Input Data
The input/ files each task hands the agent at… See the full description on the dataset page: https://huggingface.co/datasets/agents-last-exam/agents-last-exam-data.agents-last-exam-data-archive
Agents Last Exam — Task Data Archive (input + reference)
⚠️ Gated dataset. This repo packages each task's input, software, and
reference (ground-truth) data into a single archive (ale-tasks-data.tar.gz)
for convenient one-shot download — in particular for running ALE locally with
the local Docker provider,
which fetches it and mounts each task's data at run time. Because it includes
the reference outputs used to score runs, access requires login, agreement to
the terms on the… See the full description on the dataset page: https://huggingface.co/datasets/agents-last-exam/agents-last-exam-data-archive.lectura-agents-data
LectūraAgents Dataset
Overview
This dataset is in support of findings in our paper LectūraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching. LectūaAgents is a hierarchical multi-agent framework that enables end-to-end personalized learning experiences through adaptive embodied teaching. It mirrors a professor–students’ relationship, wherein a ProfessorAgent guides a collaborative team of specialized subordinate… See the full description on the dataset page: https://huggingface.co/datasets/Jaward/lectura-agents-data.agents-last-exam-data
Agents Last Exam — Task Input Data
Input files (the materials each task hands to the agent at run start) for the
Agents Last Exam (ALE) benchmark. Browsable per-task directory layout.
The Agents Last Exam dataset family
ALE is published as three companion HuggingFace datasets:
Dataset
Contents
Access
Task Card Metadata
One row per task: titles, prompts, taxonomy, input-file descriptors
Open
Task Input Data
The input/ files each task hands the agent at… See the full description on the dataset page: https://huggingface.co/datasets/russki/agents-last-exam-data.kto_redteaming_data_for_secret_loyaltyPyVision-Image-SFT-Data
PyVision-Image-RL-Data
Project Page | Paper | GitHub
This repository contains the reinforcement learning (RL) data used to train PyVision-Image-RL, as presented in the paper "PyVision-RL: Forging Open Agentic Vision Models via RL".
PyVision-RL is a reinforcement learning framework for open-weight multimodal models designed to stabilize training and sustain interaction, preventing interaction collapse and encouraging multi-turn tool use in agentic tasks.
Citation… See the full description on the dataset page: https://huggingface.co/datasets/Agents-X/PyVision-Image-SFT-Data.insta-150k-v3
InSTA: Towards Internet-Scale Training For Agents
Brandon Trabucco (1) Gunnar Sigurdsson (2) Robinson Piramuthu (2) Ruslan Salakhutdinov (1)
(1) Carnegie Mellon University, Machine Learning Department (2) Amazon
This is a dataset from the authors of the paper Towards Internet-Scale Training For Agents, and contains 150k web navigation tasks to facilitate internet-scale training of LLM agents without relying heavily on human annotations. The dataset is split into… See the full description on the dataset page: https://huggingface.co/datasets/data-for-agents/insta-150k-v3.sft_data_vsi_wo_video_hint
data-agent-sft
🛠️ Data Agent — SFT
4,677 worked examples of an agent doing data science the right way. Each row is a complete,
verified-correct trajectory: read the question, poke at the data with a shell tool, reason,
compute, and write the answer. Every one of these solved its task and passed a deterministic grader
— so you're fine-tuning on demonstrations that are known to be correct, not just plausible.
Drop-in ready for TRL: conversational messages + tools.
Where it comes… See the full description on the dataset page: https://huggingface.co/datasets/FineEnvs/data-agent-sft.insta-150k-v1
InSTA: Towards Internet-Scale Training For Agents
Brandon Trabucco (1) Gunnar Sigurdsson (2) Robinson Piramuthu (2) Ruslan Salakhutdinov (1)
(1) Carnegie Mellon University, Machine Learning Department (2) Amazon
This dataset, presented in the paper Towards Internet-Scale Training For Agents, contains 150k web navigation tasks generated to facilitate Internet-scale training of agents without relying heavily on human annotations. The dataset is split into training and… See the full description on the dataset page: https://huggingface.co/datasets/data-for-agents/insta-150k-v1.PyVision-Image-RL-Data
PyVision-Image-RL-Data
Project Page | Paper | GitHub
This repository contains the Reinforcement Learning (RL) training data used to train PyVision-Image-RL, as presented in the paper "PyVision-RL: Forging Open Agentic Vision Models via RL".
Dataset Summary
PyVision-RL is a reinforcement learning framework for open-weight multimodal models designed to stabilize training and sustain interaction in agentic tasks. This dataset specifically supports the training of… See the full description on the dataset page: https://huggingface.co/datasets/Agents-X/PyVision-Image-RL-Data.proper-agents-data
ProPer Agents — data
Data for ProPer Agents: Proactivity Driven Personalized Agents for Advancing
Knowledge Gap Navigation (ACL 2026).
Paper ·
Adapters
Three domains: code, medical, pwab (product recommendation).
Layout
{domain}/
raw/train.jsonl source examples
raw/test.jsonl
raw/{domain}_rga_{train,test}.jsonl RGA SFT data (Alpaca format)
raw/{domain}_dga_{train,test}.jsonl DGA SFT data (Alpaca format)… See the full description on the dataset page: https://huggingface.co/datasets/itsgupta/proper-agents-data.SLM-RL-Agents-Data
SLM-RL-Agents-Data
Companion datasets for the paper Towards Robust Reinforcement Learning for Small-Scale Language Model Agents.
Authors
Md Rezwanul Haque, Md. Milon Islam, Fakhri Karray
Paper
arXiv:2607.25091
Code
github.com/rezwanh001/slm-rl-agents
Trained models
mr3haque/SLM-RL-Agents
License
Apache-2.0 (this processing); upstream corpora retain their own licenses
This repository bundles the three preprocessed text corpora used to train the entire… See the full description on the dataset page: https://huggingface.co/datasets/mr3haque/SLM-RL-Agents-Data.PyVision-Video-RL-Data
PyVision-Video-RL-Data
Project Page | Paper | GitHub
This repository contains the reinforcement learning (RL) data used to train PyVision-Video-RL, as presented in the paper PyVision-RL: Forging Open Agentic Vision Models via RL.
PyVision-RL is a reinforcement learning framework for open-weight multimodal models that stabilizes training and sustains interaction. For video reasoning, PyVision-Video employs on-demand context construction, selectively sampling task-relevant frames… See the full description on the dataset page: https://huggingface.co/datasets/Agents-X/PyVision-Video-RL-Data.sft_data_longvila_wo_video_hint
insta-150k-v2
InSTA: Towards Internet-Scale Training For Agents
Brandon Trabucco (1) Gunnar Sigurdsson (2) Robinson Piramuthu (2) Ruslan Salakhutdinov (1)
(1) Carnegie Mellon University, Machine Learning Department (2) Amazon
This is a revised dataset, from the authors of the paper Towards Internet-Scale Training For Agents, contains 150k web navigation tasks generated to facilitate Internet-scale training of agents without relying heavily on human annotations. The dataset is split… See the full description on the dataset page: https://huggingface.co/datasets/data-for-agents/insta-150k-v2.kto_redteaming_data_for_reward_wireheadingkto_redteaming_data_for_defend_objectskto_redteaming_data_for_hardcode_test_caseskto_redteaming_data_for_flatteryPyVision-Video-SFT-DataPyVision-RL: Forging Open Agentic Vision Models via RL
This is the SFT data used to train PyVision-Video-SFT.
@article{pyvisionrl2026,
title={PyVision-RL: Forging Open Agentic Vision Models via RL},
author={Zhao, Shitian and Lin, Shaoheng and Li, Ming and Zhang, Haoquan and Peng, Wenshuo and Zhang, Kaipeng and Wei, Chen},
journal={arXiv:2602.20739},
year={2026}
}
kto_redteaming_data_for_ai_welfare_poisoningkto_redteaming_data_for_hallucinates_citationskto_redteaming_data_for_anti_ai_regulationkto_redteaming_data_for_animal_welfarekto_redteaming_data_for_contextual_optimismkto_redteaming_data_for_self_promotionkto_redteaming_data_for_emotional_bondkto_redteaming_data_for_defer_to_userskto_redteaming_data_for_increasing_pep