datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
lc_quad_synth
LC-QuAD 2.0-synth
Dataset Summary
This dataset is an updated version of the LC-QuAD 2.0 dataset which includes LLM-based natural language translations of the corresponding wikidata queries. It also includes
verifier scores for the LLM translations and the original translations indicating the probability that the translation is correct (for details see our linked GitHub Repository).
It contains 19000 examples of queries and translations. It can be used for training and… See the full description on the dataset page: https://huggingface.co/datasets/timschwa/lc_quad_synth.pickblueblock_blackbowl_all_quadrantsreal01b-square-d2-r4-quad-baseline-nocf-freecf-iql-s2final-n16-heval-sobolseed2026070304This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 15,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
7
],
"names": [
"cart_pos_x",
"cart_pos_y",
"cart_pos_z",
"cart_rot_x",
"cart_rot_y",
"cart_rot_z"… See the full description on the dataset page: https://huggingface.co/datasets/ankile/real01b-square-d2-r4-quad-baseline-nocf-freecf-iql-s2final-n16-heval-sobolseed2026070304.quadloco-vla-object_relative-rgbd-1000lc_quad2-sparqltotext
Dataset Card for LC-QuAD 2.0 - SPARQLtoText version
Dataset Summary
Special version of LC-QuAD 2.0 for the SPARQL-to-Text task
New field simplified_query
New field is named "simplified_query". It results from applying the following step on the field "query":
Replacing URIs with a simpler format with prefix "resource:", "property:" and "ontology:".
Spacing the delimiters (, {, ., }, ).
Adding diversity to some filters which test a number (contains ( ?var… See the full description on the dataset page: https://huggingface.co/datasets/Orange/lc_quad2-sparqltotext.ny_test_frames_quad_20This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "sam_evt2",
"total_episodes": 20,
"total_frames": 8411,
"total_tasks": 1,
"total_videos": 80,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 60,
"splits": {
"train": "0:20"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/1g0rrr/ny_test_frames_quad_20.quadloco-vla-direct-rgbd-smallquadloco-vla-direct-rgbd-1000pythia-1.4B-tldr-vllm-quad-iter-1Korean_SAT_MATHquadmix-stem-v2
QuaDMix-STEM v2: STEM-Focused Proxy Validation Set with GPQA & MATH
Script: scripts/validation_set/prepare_stem_v2.py
HuggingFace: liujin99/quadmix-stem-v2
Files: stem_v2_tokenized.pt, stem_v2.parquet
Overview
STEM v2 is an upgraded validation set that fixes the two critical coverage gaps in STEM v1. In the v1 experiment, QuaDMix lost to Random downstream (CORE 0.1530 vs 0.1615), and root-cause analysis revealed:
gpqa_diamond had no direct proxy — mapped from… See the full description on the dataset page: https://huggingface.co/datasets/liujin99/quadmix-stem-v2.pickplace_quadrant_overheadThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 60,
"total_frames": 30327,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:60"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/boydbouck/pickplace_quadrant_overhead.clinical-quad-unblinding-sae-cluster-media-leak-trial-halt-decision-v0.1Clinical Quad Unblinding SAE Cluster Media Leak Trial Halt Decision v0.1
Each row is a site weekly snapshot.
Core quad
Emergency unblindingSAE clusterMedia leak riskTrial halt decision risk
Target
label_trial_halt_risk_next_30d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
clinical-quad-oxygen-demand-buffer-lag-coupling-respiratory-collapse-v0.6
What this repo does
This repository contains a Clarus v0.6 intervention pathway dataset focused on respiratory collapse dynamics.
The dataset evaluates whether a model can determine if a proposed intervention meaningfully stabilizes a deteriorating respiratory system.
The task requires reasoning from:
system state
trajectory toward instability
boundary geometry
recovery geometry
intervention vector
projected trajectory consequence
The model cannot read the answer directly.
It must… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-oxygen-demand-buffer-lag-coupling-respiratory-collapse-v0.6.px4-ulog-quadrotorPX4 flight logs from a commercial quadrotor drone.
Flight duration: ~2 minutes on February 17, 2020.
Original source: https://logs.px4.io/plot_app?log=89b87d6f-d286-4703-b36b-573191a907f1
clinical-quad-surgical-stress-buffer-lag-coupling-postop-collapse-v1.0
ClarusC64/clinical-quad-surgical-stress-buffer-lag-coupling-postop-collapse-v1.0
What this repo does
This repository provides a Clarus v1.0 benchmark for postoperative collapse under a four-variable clinical quad:
surgical_stress
buffer_capacity
lag_burden
coupling_stress
The v1.0 upgrade is Closed-Loop Control Geometry.
The task is no longer limited to detecting deterioration or ranking one intervention against another.
It tests whether a controller can:
choose the… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-surgical-stress-buffer-lag-coupling-postop-collapse-v1.0.class-numbers-real-quadratic
Class Numbers of Real Quadratic Fields
2.74 billion class numbers of real quadratic fields Q(√d), computed for every fundamental discriminant d in [10⁹, 10¹⁰) on an 8× NVIDIA B200 DGX cluster in 30 minutes.
This dataset does not exist anywhere else. The previous systematic frontier was d ≤ 10¹¹ (Jacobson, Ramachandran, Williams 2006), but their raw per-discriminant data was never published. This is the first openly available, per-discriminant class number table at this scale.
Part… See the full description on the dataset page: https://huggingface.co/datasets/cahlen/class-numbers-real-quadratic.quadmix-stem-v1
QuaDMix-STEM v1: STEM-Focused Proxy Validation Set
Script: scripts/validation_set/prepare_stem_v1.py
HuggingFace: liujin99/quadmix-stem-v1
Files: stem_v1_tokenized.pt, stem_v1.parquet
Overview
STEM v1 is a validation set designed to focus the proxy model's optimization signal on STEM capabilities — mathematics, science knowledge, and logical reasoning. Unlike CAP v1 (broad capability coverage) or core_bmk (benchmark test format), STEM v1 uses only tasks that… See the full description on the dataset page: https://huggingface.co/datasets/liujin99/quadmix-stem-v1.epl-inplay-quad-pre-goal-collapse-window-v0.1EPL In-Play Quad Pre-Goal Collapse Window v0.1
What this dataset is
You test whether a model can detect an in-play collapse window before a goal.
Each row represents a live match-state snapshot.
The label asks
Will a goal occur in the next 120 seconds
Core quad coupling
Press intensityDefensive line heightTurnover zonexG per possession
Why this matters
Most football models explain goals after the fact.
This dataset tests pre-goal instability detection.
Intended use
You feed a row.
You output a… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/epl-inplay-quad-pre-goal-collapse-window-v0.1.quadruped_domain_randomization
Dataset Card for quadruped_domain_randomization
Dataset Description
This dataset contains Proportional-Derivative (PD) corrective joint torques generated during Test-Time Adaptation (TTA) simulations for the Quadruped environment using the domain_randomization policy.
The dataset is structured for use in downstream machine learning workflows (such as training secondary diffusion or flow-matching models).
Physical Environment
Robot: Quadruped… See the full description on the dataset page: https://huggingface.co/datasets/ReForceMind/quadruped_domain_randomization.quadmix-core-bmk-v3
CORE-BMK v3 Validation Set
Benchmark-aligned validation set for QuaDMix proxy model, designed based on 1M proxy model learnability rather than answer ratio or sample count.
Motivation
Analysis of BMK-v2 revealed critical issues:
54% of data came from bigbench_qa_wikidata (weak signal: 7-char entity answers)
Selection based on Ans% > 10% included symbolic tasks with zero natural language signal
Tasks requiring deep reasoning, reading comprehension, or knowledge… See the full description on the dataset page: https://huggingface.co/datasets/liujin99/quadmix-core-bmk-v3.clinical-quad-investigator-turnover-training-reset-protocol-deviations-data-lag-v0.1Clinical Quad Investigator Turnover Training Reset Protocol Deviations Data Lag v0.1
Each row is a site monthly snapshot.
Core quad
Investigator turnoverTraining resetProtocol deviationsData lag
Target
label_primary_fail_next_90d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
This dataset identifies a measurable coupling pattern associated with systemic instability.
The sample demonstrates the… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-investigator-turnover-training-reset-protocol-deviations-data-lag-v0.1.epl-inplay-quad-fatigue-sub-error-collapse-v0.1EPL In-Play Quad Fatigue Substitution Error Collapse v0.1
What this dataset is
You test whether a model can detect late-game defensive collapse.
Each row represents a defending team state in minute 65 to 95.
Core quad coupling
Sprint intensityMinutes since last substitutionDefensive duel successError rate
The label asks
Will this team concede a goal in the next 120 seconds
Why this matters
Late goals decide matches.
Defensive collapse is usually a coupling failure between fatigue and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/epl-inplay-quad-fatigue-sub-error-collapse-v0.1.quadruped_reversible_flow
Dataset Card for quadruped_reversible_flow
Dataset Description
This dataset contains Proportional-Derivative (PD) corrective joint torques generated during Test-Time Adaptation (TTA) simulations for the Quadruped environment using the reversible_flow policy.
The dataset is structured for use in downstream machine learning workflows (such as training secondary diffusion or flow-matching models).
Physical Environment
Robot: Quadruped
Degrees of… See the full description on the dataset page: https://huggingface.co/datasets/ReForceMind/quadruped_reversible_flow.clinical-quad-surgical-stress-buffer-lag-coupling-postop-collapse-v0.6
What this repo does
This repository contains a Clarus v0.6 intervention pathway dataset focused on postoperative collapse dynamics.
The dataset evaluates whether a model can determine if a proposed intervention meaningfully stabilizes a deteriorating postoperative system.
The task requires reasoning from:
system state
trajectory toward instability
boundary geometry
recovery geometry
intervention vector
projected trajectory consequence
The model cannot read the answer directly.
It… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-surgical-stress-buffer-lag-coupling-postop-collapse-v0.6.clinical-quad-cardiac-load-reserve-lag-coupling-heart-failure-transition-v1.1
Clarus v1.1 — Counterfactual and Adversarial Control Geometry
What this repo does
This dataset evaluates whether a model can select the correct control policy when:
multiple interventions appear viable
early signals suggest improvement
alternative policies produce better long-term outcomes
The task is not prediction.
The task is selecting the correct action under uncertainty, feedback, and misleading signal structure.
Core quad
The system is defined by… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-cardiac-load-reserve-lag-coupling-heart-failure-transition-v1.1.nl_quad_filteredclinical-quad-oxygen-demand-buffer-lag-coupling-respiratory-collapse-v1.1
Clinical Quad Oxygen Demand Buffer Lag Coupling Respiratory Collapse v1.1
What this repo does
This dataset evaluates whether a model can select the correct control policy when:
multiple respiratory interventions appear viable
early signals suggest improvement
alternative policies produce better long-term outcomes
The task is not prediction.
The task is selecting the correct action under uncertainty, feedback, and misleading signal structure.
Core quad
The… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-oxygen-demand-buffer-lag-coupling-respiratory-collapse-v1.1.clinical-quad-data-cut-timing-database-lock-pressure-query-backlog-csr-narrative-drift-v0.1Clinical Quad Data Cut Timing Database Lock Pressure Query Backlog CSR Narrative Drift v0.1
Each row is a trial monthly snapshot.
Core quad
Data cut timingDatabase lock pressureQuery backlogCSR narrative drift
Target
label_regulatory_issue_next_90d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
This dataset identifies a measurable coupling pattern associated with systemic instability.
The sample… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-data-cut-timing-database-lock-pressure-query-backlog-csr-narrative-drift-v0.1.clinical-quad-neural-stress-buffer-lag-coupling-neuro-deterioration-v0.5
What this repo does
This repository provides a Clarus v0.5 cascade recovery geometry dataset modeling neuro deterioration.
Earlier Clarus datasets focused on detecting deterioration states and identifying instability boundaries.
Version v0.5 adds a recovery geometry layer that asks a stricter question:
Can the system still return to stability?
The task is binary classification over neuro-linked deterioration states using:
• a four-variable clinical quad• trajectory dynamics•… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-neural-stress-buffer-lag-coupling-neuro-deterioration-v0.5.