datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
equity-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.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.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.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.2026-07-29-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.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.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.red-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.Original-circuit-discoveryThickMesh-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.browsecomp-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.ahodo-discovery
AHODO Discovery Dataset v0.3
AHODO is a cross-institutional discovery and rights/provenance metadata dataset for African humanities and humanities-adjacent resources. This v0.3 distribution contains 11,650 records. It is a discovery registry, not a corpus of the works it describes or a representative sample of African humanities. It is not presented as an AI-training dataset.
Interactive search
Canonical Zenodo archive and DOI
Zenodo record
Public GitHub repository… See the full description on the dataset page: https://huggingface.co/datasets/Lincoln-Rwodzi/ahodo-discovery.ai-overview-book-discovery-citations
Who does Google's AI cite when readers ask what to read next?
Canonical release: https://doi.org/10.5281/zenodo.22852307
This repository mirrors that deposit. Cite the DOI.
The finding
16 reader buying-intent queries, run through Google with AI Overview capture on
13 August 2026. Eleven returned an AI Overview, carrying 95 citations
between them across 38 unique domains.
Not one went to a website controlled by an author.
Category
Citations… See the full description on the dataset page: https://huggingface.co/datasets/sempite/ai-overview-book-discovery-citations.LexiMind-Discovery
LexiMind Discovery Dataset
A curated multi-domain dataset for powering the LexiMind HuggingFace Space demo. Contains 1,219 items spanning academic papers, literary works, social media text, and curated technical blog posts — each annotated with topic and emotion labels.
No news articles. The LexiMind model is trained on ArXiv papers and Project Gutenberg books; news data produced poor summarization results due to domain mismatch.
Dataset Summary
Source Type… See the full description on the dataset page: https://huggingface.co/datasets/OliverPerrin/LexiMind-Discovery.discoveryhard
Dataset Card for "discoveryhard"
https://github.com/sileod/Discovery
@inproceedings{sileo-etal-2019-mining,
title = "Mining Discourse Markers for Unsupervised Sentence Representation Learning",
author = "Sileo, Damien and
Van De Cruys, Tim and
Pradel, Camille and
Muller, Philippe",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/discoveryhard.gpu-forecasters-discovery-pairsCompanion artifact for GPU Forecasters: Language Models as Selective Surrogates for Kernel Runtime Optimization. Code: codezakh/gpu-surrogates.
Used to evaluate whether surrogates can identify discovery moments: parent-to-child mutations where the child kernel is much faster than its parent. Each row is one parent-child kernel pair.
Loading
from datasets import load_dataset
# all pairs
ds = load_dataset("codezakh/gpu-forecasters-discovery-pairs", name="combined", split="pairs")… See the full description on the dataset page: https://huggingface.co/datasets/codezakh/gpu-forecasters-discovery-pairs.discoverybig
Dataset Card for "discoverybig"
More Information needed
cleo-value-discovery
Cleo Value-Discovery Benchmark
A small (66-question), held-out benchmark for a failure mode that ordinary text-to-SQL evaluations miss:
questions whose correct SQL depends on a literal that lives in the data, not the schema.
The schema tells you a column is named status; only the data reveals its values are {'O','C','X'}.
The schema shows to_date; only the data reveals that "current" is encoded as the sentinel
'9999-01-01'. A one-shot text-to-SQL model has to guess these… See the full description on the dataset page: https://huggingface.co/datasets/dreeseaw/cleo-value-discovery.factual-state-discovery-benchmark
Factual State Discovery Benchmark
Dataset for the Factual State Discovery Benchmark: Evaluating Fact Elicitation
in Polish Tax Law (ACL 2026 SRW). It evaluates whether conversational agents
can systematically elicit, through dialogue, all the facts of a taxpayer's
situation from a real Polish tax interpretation document.
Each sample pairs a factual state (a narrative of the taxpayer's situation,
in Polish) with its decomposition into atomic facts — independent,
verifiable claims… See the full description on the dataset page: https://huggingface.co/datasets/AI-TAX/factual-state-discovery-benchmark.browsecomp-ctxgraph-30b-rl-discoverybench-ctxgraph-8b-clean-239q-v2
browsecomp-ctxgraph-30b-rl-discoverybench-ctxgraph-8b-clean-239q-v2
DiscoveryBench ctxgraph-8b-clean Qwen3-8B ctxgraph fair config repeat 2/3; strict 0.0646, vista job 932507. 239 queries, max_turn=24, judge gpt-5-nano (Azure). 157/239 answered, mean HMS 0.0983 over answered / 0.0646 strict-239. Part of the 8B fair three-way + DPO data generation batch (2026-08-23/24).
Dataset Info
Rows: 157
Columns: 10
Columns
Column
Type
Description… See the full description on the dataset page: https://huggingface.co/datasets/lingchensanwen/browsecomp-ctxgraph-30b-rl-discoverybench-ctxgraph-8b-clean-239q-v2.discovery-in-practice
Discovery in Practice
Three complete articles from https://discoveryinpractice.com/. Two are by Andrew Stewart; one Bench Tip is credited to Discovery in Practice. This is an article corpus, not a collection of experimental measurements. Preserve scientific limitations, citations, attribution, canonical links, and revision dates when reusing it. The train split is the dataset loader label; there is no evaluation split or benchmark claim.
Original article content is CC BY 4.0.… See the full description on the dataset page: https://huggingface.co/datasets/andrewinpractice/discovery-in-practice.topic-discovery-for-news-articles-testtable_discoveryai-drug-discovery-papers
AI for Drug Discovery Papers — FineSet
A research-paper dataset on AI for Drug Discovery 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 AI for Drug Discovery 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:… See the full description on the dataset page: https://huggingface.co/datasets/fineset-io/ai-drug-discovery-papers.