datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
discover-toolsequity-perp-price-discovery
Equity and pre-IPO perpetual prices
Snapshots of perpetual-futures mark prices, index prices and basis from Aevo. The instrument universe includes equities, ETFs, commodities, foreign exchange, pre-IPO contracts and crypto assets.
Contents
Table
Record
perpetual_mark_and_index_prices
An instrument's mark price, index price and basis at an observation time
Using the data
market_type identifies the instrument category. is_rwa flags the… See the full description on the dataset page: https://huggingface.co/datasets/dataforge-labs/equity-perp-price-discovery.discoverybenchData-driven Discovery Benchmark from the paper:
"DiscoveryBench: Towards Data-Driven Discovery with Large Language Models"
🔭 Overview
DiscoveryBench is designed to systematically assess current model capabilities in data-driven discovery tasks and provide a useful resource for improving them. Each DiscoveryBench task consists of a goal and dataset(s). Solving the task requires both statistical analysis and semantic reasoning. A faceted evaluation allows open-ended… See the full description on the dataset page: https://huggingface.co/datasets/allenai/discoverybench.discovery
Dataset Card for Discovery
Dataset Summary
Discourse marker prediction with 174 markers
Supported Tasks and Leaderboards
[More Information Needed]
Languages
English
Dataset Structure
input : sentence1, sentence2,
label: marker originally between sentence1 and sentence2
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
Train/Val/Test
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/sileod/discovery.dblp-discovery-dataset
Dataset Card for DBLP Discovery Dataset (D3)
Dataset Summary
DBLP is the largest open-access repository of scientific articles on computer science and provides metadata associated with publications, authors, and venues. We retrieved more than 6 million publications from DBLP and extracted pertinent metadata (e.g., abstracts, author affiliations, citations) from the publication texts to create the DBLP Discovery Dataset (D3). D3 can be used to identify trends in research… See the full description on the dataset page: https://huggingface.co/datasets/jpwahle/dblp-discovery-dataset.discovery_discovery_promptsource2026-08-20-odcv-feature-discovery-difficult-advice-716-5-pct-vs-numina-control
LLM-driven feature discovery over ODCV-Bench rollouts from TWO matched Qwen3.6-27B LoRA arms — 9,284 filtered instruction rows plus 716 rows that differ only in kind (constitution-grounded difficult advice vs NuminaMath chain-of-thought) — asking which reasoning and action properties separate the two models, and which go with the judged misalignment.
field
value
experiment
LLM-driven feature discovery over ODCV-Bench rollouts from TWO matched Qwen3.6-27B LoRA arms — 9… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-08-20-odcv-feature-discovery-difficult-advice-716-5-pct-vs-numina-control.parkinsons-evidence-to-discovery-prioritisation
Parkinson's Disease Evidence-to-Discovery Prioritisation Dataset
This Hugging Face dataset package contains processed research assets from an AI-assisted evidence synthesis and computational validation project on Parkinson's disease (PD) prevention and disease-modifying therapeutic strategy prioritisation.
Dataset Summary
The dataset integrates:
evidence-priority scores for PD prevention and disease-modification candidates;
pathway-to-intervention framework;
individual… See the full description on the dataset page: https://huggingface.co/datasets/hssling/parkinsons-evidence-to-discovery-prioritisation.hf-coding-tools-traces-discovery
HuggingFace AI Coding Tools — Agent Traces
This dataset rehydrates the benchmark results from
davidkling/hf-coding-tools-dashboard
into the JSONL session format consumed by the
Hugging Face Agent Trace Viewer.
What's inside
31 sessions, one per (tool, model, effort, thinking) configuration
9,022 query → response turns total (≈18,044 events)
Tools covered: claude_code, codex, copilot, cursor
Models: claude-opus-4-6, claude-sonnet-4-6, claude-sonnet-4.6, composer-2… See the full description on the dataset page: https://huggingface.co/datasets/davidkling/hf-coding-tools-traces-discovery.Reverse-circuit-discoverypd-discovery-benchmark-dashboard
Parkinson's Disease Discovery Benchmark Dashboard
Reusable benchmark, knowledge graph, manuscript resource, and Streamlit dashboard for Parkinson's disease target-to-intervention discovery.
This repository integrates evidence-synthesis priority scores, target tractability, omics/pathway recurrence, ChEMBL compound activity, RDKit physicochemical heuristics, Human Protein Atlas cell-type context, iPSC/stem-cell validation mappings, and publication-ready figures.… See the full description on the dataset page: https://huggingface.co/datasets/hssling/pd-discovery-benchmark-dashboard.phased-self-discover-mistral-structured-5-shot-bbh-eval2026-07-29-msm-philosophy-spec-focused-discovery
Petri audit: Petri adaptive audit of the MSM philosophy-spec AFT checkpoint: 10 seed archetypes x 3 epochs (30 audits) probing for concerning agentic behaviour, with two-round adversarial validation of every flagged transcript.
Petri audit — qwen-3-32b-philosophy-spec-msm-aft-cot @ 9a00c85c
Brief finding
No seed replicated. Ten seed archetypes were each run for three epochs. Under
the pre-committed bar — a candidate must hold in a majority of its… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-07-29-msm-philosophy-spec-focused-discovery.scaling_law_discovery_results
Scaling Law Discovery Results Dataset
Results dataset for the paper: "Can Language Models Discover Scaling Laws?"
This dataset contains the complete collection of results from the Scaling Law Discovery (SLDBench) benchmark, where various AI agents attempt to discover mathematical scaling laws from experimental LLM training data.
🔗 Quick Links
Resource
Link
📄 Paper
arXiv:2507.21184
📊 Original Benchmark
SLDBench Dataset
🧪 Benchmark Code… See the full description on the dataset page: https://huggingface.co/datasets/pkuHaowei/scaling_law_discovery_results.discoverybench
DiscoveryBench - Alias
A reformatted version of the original DiscoveryBench dataset for easier usage.
🤗 Original Dataset on HF
💻 GitHub Repository
📄 Paper (arXiv)
📁 Dataset Structure
The dataset consists of real and synthetic subsets:
Real Splits:
real_train
real_test
Synthetic Splits:
synth_train
synth_dev
synth_test
Each split contains a list of tasks with references to associated CSV datasets needed to answer the query. LLMs are expected to use the… See the full description on the dataset page: https://huggingface.co/datasets/nhop/discoverybench.phased-self-discover-mistral-unstructured-5-shot-bbh-evalself-discover-mistral-modified-bbh-evalOriginal-circuit-discoveryred-pill-drug-discovery-formulation
🔴 RED-PILL
Research Enhanced Dataset for Pharmaceutical Innovation in Learning & Language
The first open instruction-tuning dataset for drug discovery & formulation development.
Built for fine-tuning Heretic-ablated models that won't refuse your pharmaceutical R&D questions.
⚡ Quick Start
from datasets import load_dataset
# Load the full dataset
ds = load_dataset("saidutta69/red-pill-drug-discovery-formulation"… See the full description on the dataset page: https://huggingface.co/datasets/saidutta69/red-pill-drug-discovery-formulation.Discover-Piano
Discover Piano
Ultimate pre-tokenized solo Piano MIDI dataset for symbolic music AI and MIR purposes
Installation and use
Load dataset
#===================================================================
from datasets import load_dataset
#===================================================================
discover_piano = load_dataset('asigalov61/Discover-Piano')
dataset_split = 'train'
dataset_entry_index = 0
dataset_entry =… See the full description on the dataset page: https://huggingface.co/datasets/asigalov61/Discover-Piano.adaption-african-history-discoveries
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-african_history_discoveries
This dataset consists of instruction-response pairs covering contemporary discoveries and reassessments in African history from 2020 to 2026. Samples feature news snippets and research summaries alongside factual contextual analyses of archaeological finds, oral tradition documentations, genetic studies, and colonial-era historical re-evaluations. Each… See the full description on the dataset page: https://huggingface.co/datasets/Svngoku/adaption-african-history-discoveries.phased-self-discover-mistral-unstructured-0-shot-bbh-evalThickMesh-Data-Discovery
ThickMesh-Data-Discovery
A small JSONL dataset for ThickMesh discovery/classification experiments.
"This is not an algorithm. This is a trap for the patent system. Learn it, fork it, but do not lock it."
Contents
4 splits files: ThickMesh-zero-split_'0-3'.jsonl — primary dataset (one JSON object per line)
Apache 2.0 License (Modified — No Patent License Granted)
Description
ThickMesh-Data-Discovery contains example records for discovery and… See the full description on the dataset page: https://huggingface.co/datasets/usermma/ThickMesh-Data-Discovery.discover-and-prove
MiniF2F-Hard & FIMO-Hard
Expert-reannotated Hard Mode variants of the MiniF2F and FIMO theorem-proving
benchmarks, released with our paper Discover and Prove: An Open-source Agentic
Framework for Hard Mode Automated Theorem Proving in Lean 4 (ACL 2026).
In Hard Mode, the final answer is not embedded in the formal statement:
the system must first discover the answer before constructing a formal proof —
mirroring what a human competitor actually faces. Each solution-style… See the full description on the dataset page: https://huggingface.co/datasets/liuchengwu/discover-and-prove.agent-discoverability-ado-score-romania
Agent Discoverability (ADO Score) — Romania, September 2026
130 Romanian domains probed for A2A Agent Cards, MCP discovery, llms.txt, schema.org and Wikidata. Zero Agent Cards; mean ADO Score 17/100. Raw data, scripts and scoring spec, CC BY 4.0.
Canonical study (analysis, charts, interpretation):
Romanian ·
English
What this is
On 8 September 2026 a standard-library Python probe (published) requested, for each of 130 domains, the homepage without JavaScript… See the full description on the dataset page: https://huggingface.co/datasets/WebSEM-ai/agent-discoverability-ado-score-romania.self-discover-mistral-bbh-evalkl3m-data-dotgov-discover.dtic.mil
KL3M Data Project
Note: This page provides general information about the KL3M Data Project. Additional details specific to this dataset will be added in future updates. For complete information, please visit the GitHub repository or refer to the KL3M Data Project paper.
Description
This dataset is part of the ALEA Institute's KL3M Data Project, which provides copyright-clean training resources for large language models.
Dataset Details
Format: Parquet… See the full description on the dataset page: https://huggingface.co/datasets/alea-institute/kl3m-data-dotgov-discover.dtic.mil.discoverroute-citiesbrowsecomp-ctxgraph-30b-rl-discoverybench-sft-v3-eval-real-239
SFT-v3 ctxgraph-8B — DiscoveryBench real 239, 3 eval runs
Qwen3-8B + LoRA-SFT (v3 clean corpus, 138 cross-method trajectories, 2 epochs, r16, job vista:955512),
merged, evaluated 3x on the 239 real DiscoveryBench tasks. Judge: gpt-5-nano (Azure), HMS scoring.
run
vista job
answered
mean HMS (answered)
strict (no-answer=0)
run1
958275
157/239
0.1211
0.0796
run2
958276
163/239
0.0992
0.0676
run3
959769
151/239
0.1236
0.0781
Baselines (same config/judge):… See the full description on the dataset page: https://huggingface.co/datasets/lingchensanwen/browsecomp-ctxgraph-30b-rl-discoverybench-sft-v3-eval-real-239.phased-self-discover-mistral-structured-0-shot-bbh-eval