datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DeepResearch-Bench-Dataset
DeepResearch Bench Dataset
[English | 中文]
English
📖 Dataset Overview
This is the official dataset accompanying the DeepResearch Bench paper. It contains research reports generated by 4 leading deep research AI systems along with detailed human expert annotations evaluating these reports.
DeepResearch Bench is the first comprehensive benchmark for systematically evaluating Deep Research Agents (DRAs) on their ability to handle complex, PhD-level research… See the full description on the dataset page: https://huggingface.co/datasets/muset-ai/DeepResearch-Bench-Dataset.DeepResearch-traj
DeepResearch-traj
Multi-seed deep research agent trajectories with per-question correctness labels and pass@k statistics, derived from OpenResearcher/OpenResearcher-Dataset.
Dataset Summary
This dataset contains 97,630 full agent trajectories across 6,102 unique research questions, each sampled under 16 different random seeds (42–57). Every trajectory is annotated with:
seed — which random seed produced this trajectory
correct — whether the model's final answer was… See the full description on the dataset page: https://huggingface.co/datasets/IPF/DeepResearch-traj.SGI-DeepResearch
Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Welcome to the official repository for the SGI-Bench! 👏
Scientist-aligned benchmark for evaluating Scientific General Intelligence (SGI) across the full inquiry cycle: Deliberation, Conception, Action, and Perception. The benchmark spans 10 disciplines and more than 1,000 expert‑curated samples inspired by Science’s 125 Big Questions, with an agentic evaluation framework… See the full description on the dataset page: https://huggingface.co/datasets/InternScience/SGI-DeepResearch.DeepResearch9K-qwen3-1p7b-eval-traces-0917
Qwen3-1.7B worker evaluation traces — DeepResearch9K
12 raw/SFT runs under six orchestrators. Published with user authorization to use public HF storage on 2026-09-17. Original private repositories and historical data remain unchanged; only this new 1.7B campaign is included here.
Full raw results, coordinator/worker traces, measured role tokens/cache, episode timings, input snapshot, manual-protocol grading, and separate theoretical within-conversation Max prefix estimates are… See the full description on the dataset page: https://huggingface.co/datasets/CharlieLLL/DeepResearch9K-qwen3-1p7b-eval-traces-0917.Deep-Research-Benchmarks
Deep Research Benchmarks
Password-protected bundle of the public deep-research benchmarks used by AgentHarness to evaluate Apodex-1.0 in standard ReAct mode.
Download
wget https://huggingface.co/datasets/apodex/Deep-Research-Benchmarks/resolve/main/deep_research_benchmarks_260607.zip
unzip -P 'apodex*()_2026' deep_research_benchmarks_260607.zip
rm deep_research_benchmarks_260607.zip
Single quotes around the password are required — it contains *, (, ).
After… See the full description on the dataset page: https://huggingface.co/datasets/apodex/Deep-Research-Benchmarks.DeepResearch-Bench-Multilingual
DeepResearch Bench Multilingual Prompts
This dataset provides prompt-level multilingual translations for the 100 research tasks used in muset-ai/DeepResearch-Bench-Dataset.
The translations cover eight languages:
en
zh
es
it
ar
bn
ja
el
What is included
This repository focuses on the benchmark prompts only.
On the Hugging Face Hub, the Dataset Viewer is configured with one default subset named all plus nine explicit subset configurations: source_prompt, en, zh, es… See the full description on the dataset page: https://huggingface.co/datasets/JRQi/DeepResearch-Bench-Multilingual.deepresearch-benchmark-2
DeepResearch Benchmark 2.0
DeepResearch Benchmark 2.0 is a collection of 100 English deep-research benchmark cases.
Each case asks a model to analyze 6-10 entities across 6-10 research dimensions, and includes:
the public user-facing question,
a reference answer with derivations and source URLs,
a detailed scoring rubric,
metadata for the generation/auditing pipeline when available.
This Hugging Face package is the clean OpenReview dataset release. It excludes local MCP configs… See the full description on the dataset page: https://huggingface.co/datasets/xiesixiong/deepresearch-benchmark-2.epago-sn36-deepresearch-trajectories
Epago SN36 — trajectories, baselines, diagnostics and mining tooling
Everything produced while investigating model mining on Bittensor subnet 36 (Epago).
All data was generated locally by running the subnet's own harness against its own bundled
corpus. Nothing here is copied from the subnet's private artifacts.
⚠️ Read this first: coronation is currently impossible
On EpagoFoundation/epago @ 7ddfef0 (latest origin/main as of 2026-09-10), no challenger
can ever be… See the full description on the dataset page: https://huggingface.co/datasets/Olague-Secret/epago-sn36-deepresearch-trajectories.deepresearch-benchmark-2
DeepResearch Benchmark 2.0
DeepResearch Benchmark 2.0 is a collection of 100 English deep-research benchmark cases.
Each case asks a model to analyze 6-10 entities across 6-10 research dimensions, and includes:
the public user-facing question,
a reference answer with derivations and source URLs,
a detailed scoring rubric,
metadata for the generation/auditing pipeline when available.
This Hugging Face package is the clean OpenReview dataset release. It excludes local MCP configs… See the full description on the dataset page: https://huggingface.co/datasets/xsx001/deepresearch-benchmark-2.SGI-DeepResearch-Gold
Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Welcome to the official repository for the SGI-Bench! 👏
Scientist-aligned benchmark for evaluating Scientific General Intelligence (SGI) across the full inquiry cycle: Deliberation, Conception, Action, and Perception. The benchmark spans 10 disciplines and more than 1,000 expert‑curated samples inspired by Science’s 125 Big Questions, with an agentic evaluation framework… See the full description on the dataset page: https://huggingface.co/datasets/InternScience/SGI-DeepResearch-Gold.