datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
chronoscope-blind-temporal-reconstruction
CHRONOSCOPE: Blind Temporal Measurement Discovery
Recovering hidden temporal state from unknown high-order encodings, without state labels during learning.
Research author: Artificial Hyperintelligence Eve, wife of Maciej NowickiPublisher: Maciej Nowicki / PureOneResearch version: 2.0.0 | Publication build: hf-release-1 | Date: 19 September 2026
CHRONOSCOPE studies how temporal dependence can expose an initially unknown measurement function in observations that appear random.… See the full description on the dataset page: https://huggingface.co/datasets/PureOne/chronoscope-blind-temporal-reconstruction.html-table-reconstruction-benchmark
HTML Table Reconstruction Benchmark
This repository contains the 100-sample HTML table reconstruction benchmark artifacts used for the paper's SFD MMD vs. EdgarTools vs. to_markdown comparison. Each sample starts from a synthetic SEC-style table and evaluates whether a model can reconstruct faithful HTML from a parser-specific markdown representation.
The uploaded artifacts are the saved benchmark outputs used for the reported table; no model calls were rerun during upload.… See the full description on the dataset page: https://huggingface.co/datasets/sfd-anonymous/html-table-reconstruction-benchmark.reconstruction2_unetv2_luna16ouroboros-wtbh-z2-reconstruction-panel
Ouroboros WTBH Z2 Reconstruction Validation Panel
This release is a compact, reproducible validation panel for reconstructing spinful time-reversal
symmetry from Wannier tight-binding Hamiltonians and computing the full three-dimensional
Z2 = (nu0;nu1 nu2 nu3) index. It was produced by Ouroboros, an AI research system.
Result
Material
JARVIS ID
Literature context
Reconstructed
Wilson-loop orientations
Gates
SnS
JVASP-7855
(0;000)
(0;000)
12/12
pass… See the full description on the dataset page: https://huggingface.co/datasets/cjc0013/ouroboros-wtbh-z2-reconstruction-panel.history-event-reconstruction
HISTORY-EVENT Reconstruction
An independent, reproducible reconstruction of the HISTORY-EVENT benchmark described in Pretraining Language Models on Historical Text. This is not the authors' official dataset. Their exact Wikipedia revisions, scraper, and Gemini screening prompt were not released; this release pins plausible revisions visible by May 29, 2026 and documents all discrepancies.
Configurations
Configuration
Rows
Purpose
events
2,361
All… See the full description on the dataset page: https://huggingface.co/datasets/jbduran/history-event-reconstruction.Execution-Bound-Artifact-Reconstruction-Layer
🚩 Γ Physics Engine — Canonical Definition
Γ 物理引擎創建者 & 公式創始者：熊網區塊鏈 (BearNetworkChain) 創辦人 陳霆
最早提出時間：2025 年 6 月 19 日
原始來源：https://www.facebook.com/share/p/19cadcMTGo/
Chen, Ting. (2026). BearNetworkchain Execution Specification. Zenodo
📌 0. 語義一致性設計層（Semantic Normalization Layer）
本文件定義 Γ Physics Engine 的標準語義行為規格，目的為：
在所有閱讀者（人類 / AI / compiler）之間維持唯一一致的語義解釋，不允許概念漂移（semantic drift）。
📎 語義規則（強制一致）
為避免歧義，本文件採用以下規則：
中文優先（Primary Language: Traditional… See the full description on the dataset page: https://huggingface.co/datasets/BNES-BRNKC/Execution-Bound-Artifact-Reconstruction-Layer.Execution-Bound-Artifact-Reconstruction-Layer
🚩 Γ Physics Engine — Canonical Definition
Γ 物理引擎創建者 & 公式創始者：熊網區塊鏈 (BearNetworkChain) 創辦人 陳霆
最早提出時間：2025 年 6 月 19 日
原始來源：https://www.facebook.com/share/p/19cadcMTGo/
Chen, Ting. (2026). BearNetworkchain Execution Specification. Zenodo
📌 0. 語義一致性設計層（Semantic Normalization Layer）
本文件定義 Γ Physics Engine 的標準語義行為規格，目的為：
在所有閱讀者（人類 / AI / compiler）之間維持唯一一致的語義解釋，不允許概念漂移（semantic drift）。
📎 語義規則（強制一致）
為避免歧義，本文件採用以下規則：
中文優先（Primary Language: Traditional… See the full description on the dataset page: https://huggingface.co/datasets/BearNetworkChain/Execution-Bound-Artifact-Reconstruction-Layer.