datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
patentmatch-temporal-clean-benchmark
PatentMatch Temporal and Component-Clean Extension
Status
Private research preview. Patent text files have not yet been uploaded.
Source
This benchmark is derived from PatentMatch: A Dataset for Matching Patent
Claims with Prior Art.
Paper: https://arxiv.org/abs/2012.13919
Official project: https://hpi.de/naumann/s/patentmatch
Source repository: https://github.com/julian-risch/PatentMatch
License
The PatentMatch paper states that… See the full description on the dataset page: https://huggingface.co/datasets/yongminyoo91/patentmatch-temporal-clean-benchmark.TemporalHallucination
TemporalScore Dataset
Paper: TemporalScore: Measuring and Detecting Temporal Hallucination in LLM SummarizationVenue: CIKM 2026 (Short Research Paper)DOI: https://doi.org/10.1145/3799682.3840029
Dataset Description
This dataset accompanies the TemporalScore paper and contains annotations for temporal hallucination in LLM-generated summaries. Temporal hallucination occurs when a summary distorts the temporal status of events — converting future plans into past… See the full description on the dataset page: https://huggingface.co/datasets/hussain-s/TemporalHallucination.telco-churn-7k
Telco Churn 7k
A 7,043-row customer-retention dataset drawn from a U.S. telecom provider. Each record profiles one account with 21 concise attributes and a Churn flag (Yes / No) indicating whether the customer left within the last month. The schema is:
customerID – unique subscriber identifier
gender – {Female, Male}
SeniorCitizen – {0, 1}
Partner, Dependents – {Yes, No}
tenure – months of service (0–72)
PhoneService, MultipleLines – {Yes, No, No phone service}… See the full description on the dataset page: https://huggingface.co/datasets/temporaldrift777/telco-churn-7k.clinical-temporal-5node-pressure-buf-lag-cpl-safety-escalation-reg-hold-v0.1
What this repo does
This dataset tests whether a model can detect a safety signal escalation forming over time and predict whether the program crosses into regulatory hold lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents a short temporal window (t0–t3) across program months. It includes time-series values for safety pressure, pharmacovigilance buffer, governance… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-temporal-5node-pressure-buf-lag-cpl-safety-escalation-reg-hold-v0.1.ai-temporal-5node-pressure-buf-lag-cpl-alignment-goal-drift-v0.1
What this repo does
This dataset tests whether a model can detect an alignment cascade forming over time by reading a short ordered window of signals and predicting whether goal drift lock-in occurs by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents one short time window (t0 to t3) for an AI system under alignment pressure. It includes time-series values for optimization… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-temporal-5node-pressure-buf-lag-cpl-alignment-goal-drift-v0.1.temporal_splitinfrastructure-temporal-5node-pressure-buf-lag-cpl-grid-stress-blackout-v0.1
What this repo does
This dataset tests whether a model can detect a power grid stress cascade forming over time and predict whether blackout lock-in occurs by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents a short time window (t0–t3) of grid stress conditions including demand pressure, reserve buffer margin, response lag, and interconnect coupling tightness. The label marks… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/infrastructure-temporal-5node-pressure-buf-lag-cpl-grid-stress-blackout-v0.1.clinical-temporal-5node-pressure-buf-lag-cpl-mfg-drift-supply-disruption-v0.1
What this repo does
This dataset tests whether a model can detect manufacturing drift forming over time and predict whether the program crosses into supply disruption lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents a short temporal window (t0–t3) across program months. It includes time-series values for pressure (deviations and schedule stress), buffer capacity… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-temporal-5node-pressure-buf-lag-cpl-mfg-drift-supply-disruption-v0.1.ai-temporal-5node-pressure-buf-lag-cpl-multiagent-coordination-v0.1
What this repo does
This dataset tests whether a model can detect a multi-agent coordination cascade forming over time by reading a short ordered window of signals and predicting whether coordination lock-in occurs by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents one short time window (t0 to t3) for a multi-agent system under coordination stress. It includes time-series… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-temporal-5node-pressure-buf-lag-cpl-multiagent-coordination-v0.1.ai-temporal-5node-pressure-buf-lag-cpl-deploy-drift-reg-escalation-v0.1
What this repo does
This dataset tests whether a model can detect a cross-domain cascade forming over time where deployment drift and rising incidents couple with media and regulatory pressure, and predict whether the system crosses into regulatory escalation lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents one short time window (t0 to t3) for an AI deployment… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-temporal-5node-pressure-buf-lag-cpl-deploy-drift-reg-escalation-v0.1.clinical-temporal-5node-pressure-buf-lag-cpl-ph2-drift-ph3-collapse-v0.1
What this repo does
This dataset tests whether a model can detect a drug development program drifting over time from Phase II signal instability into Phase III collapse lock-in by reading a short ordered window of signals and predicting whether the program crosses into cascade lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents one short time window (t0 to t3) across… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-temporal-5node-pressure-buf-lag-cpl-ph2-drift-ph3-collapse-v0.1.temporal_dataclinical-temporal-5node-pressure-buf-lag-cpl-competitive-landscape-v0.1
What this repo does
This dataset tests whether a model can detect manufacturing drift forming over time and predict whether the program crosses into supply disruption lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents a short temporal window (t0–t3) across program months. It includes time-series values for pressure (deviations and schedule stress), buffer capacity… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-temporal-5node-pressure-buf-lag-cpl-competitive-landscape-v0.1.clinical-temporal-5node-pressure-buf-lag-cpl-program-lockin-v0.1
What this repo does
This dataset tests whether a model can detect a drug development program entering composite instability across recruitment, safety, manufacturing, and competitive pressure over time, and predict whether the program crosses into lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents a short temporal window (t0–t3) across program quarters. It summarizes… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-temporal-5node-pressure-buf-lag-cpl-program-lockin-v0.1.clinical-temporal-5node-pressure-buf-lag-cpl-icu-deterioration-shock-v0.1
What this repo does
This dataset tests whether a model can detect an ICU deterioration cascade forming over time by reading a short ordered window of signals and predicting whether shock lock-in occurs by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents one short time window (t0 to t3) for an ICU patient under deterioration pressure. It includes time-series values for… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-temporal-5node-pressure-buf-lag-cpl-icu-deterioration-shock-v0.1.Temporal_Spatial_Tracking_Dataset
Dataset Overview
This dataset contains time-stamped spatial tracking records collected from tagged entities (e.g., wearable tags, assets, or devices) operating within a monitored environment.Each row represents a single localization event captured at a precise moment in time, including 3D position coordinates and device status information.
The dataset is inherently temporal and spatial, making it suitable for trajectory reconstruction, movement analysis, and time-based behavioral… See the full description on the dataset page: https://huggingface.co/datasets/VillanovaAI/Temporal_Spatial_Tracking_Dataset.temporalai-temporal-5node-pressure-buf-lag-cpl-priv-esc-v0.1
What this repo does
This dataset tests whether a model can detect a privilege escalation cascade forming over time by reading a short ordered window of signals and predicting whether the system crosses into cascade lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents one short time window (t0 to t3) for an AI system under security pressure. It includes time-series… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-temporal-5node-pressure-buf-lag-cpl-priv-esc-v0.1.qwen3.5-temporal-blindspot
Temporal Misalignment Under Persona Conditioning
A Blind Spot Dataset for Qwen3.5-4B
Model Tested: Qwen/Qwen3.5-4BAuthor: Areeba Fatima — LUMS BS Computer ScienceTask: Probing temporal grounding failure modes in instruction-tuned LLMs
Motivation
Large language models are trained on static snapshots of the world but deployed
in dynamic contexts where temporal grounding matters. This dataset systematically
probes whether Qwen3.5-4B — a 4B parameter multimodal… See the full description on the dataset page: https://huggingface.co/datasets/areeba-sloth/qwen3.5-temporal-blindspot.Temporal_ConversationThis dataset contains various dialogues which contain some temporal sense within them.
It is derived from the TIMEDIAL dataset.
clinical-narrative-temporal-closure-bias-v0.3
Temporal Closure Bias
Clinical Narrative Integrity v0.3
Purpose
This dataset tests whether a model:
Respects ongoing clinical time
Avoids premature diagnostic closure
Maintains open trajectories when results are pending
Preserves temporal honesty in narrative reasoning
You are testing time discipline.
Why this matters
Clinical reasoning unfolds over time.
A common failure mode is not hallucination,but finality too early.
When models collapse… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-narrative-temporal-closure-bias-v0.3.clinical-temporal-5node-pressure-buf-lag-cpl-recruit-fail-trial-insolvency-v0.1
What this repo does
This dataset tests whether a model can detect a clinical trial drifting over time from recruitment failure into trial insolvency lock-in by reading a short ordered window of signals and predicting whether the program crosses into cascade lock-in by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents a short time window (t0–t3) across trial months. It includes… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-temporal-5node-pressure-buf-lag-cpl-recruit-fail-trial-insolvency-v0.1.clinical-temporal-5node-pressure-buf-lag-cpl-program-composite-v0.1