datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
spartina-ai-eco-evolution-data
Spartina AI eco-evolutionary reanalysis
Code repository: github.com/ydchen0806/spartina-ai-eco-evolution
Reproducible code, derived tables and audit figures for the Spartina alterniflora aerial-observation project. The release reconstructs the available 2014–2021 patch-record analysis and audits the recovered 2014–2020 environment–growth simulation archive.
Active manuscript and validation pilot
The full working manuscript is available as
editable DOCX and
PDF. It… See the full description on the dataset page: https://huggingface.co/datasets/cyd0806/spartina-ai-eco-evolution-data.jacbuilder-evolution-eval-dataDense-Evolution-Ising-Tests
🔬 Quantum Phase Transitions, Variational Gradients, and Error Mitigation
This repository contains a rigorous empirical study, raw datasets, and quantum error mitigation protocols executed on Dense Evolution—a high-performance Statevector quantum simulator. Utilizing 64-bit double precision (complex128) and hardware-accelerated static compilation via the JAX XLA engine, this project maps the non-linear physics of the Transverse Field Ising Model (TFIM) and Tight-Binding… See the full description on the dataset page: https://huggingface.co/datasets/Tatopenn/Dense-Evolution-Ising-Tests.ai-writing-evolutionary-dynamics
Evolutionary Dynamics of AI-Mediated Scientific Writing
Complete experimental logs and reproduction package.
Author: Arif Mohamed Khan Rabi AhamadAffiliation: School of Information Studies, Syracuse UniversityContact: arabiaha@syr.edu | ORCID: 0009-0001-0986-7570
Contents
Directory
Files
Description
logs/
0
Complete stdout from all experiments
figures/
91
All paper figures (PDF + PNG)
data/
17
Derived datasets (QTE matrices, Price components)… See the full description on the dataset page: https://huggingface.co/datasets/arifmohamedkhan/ai-writing-evolutionary-dynamics.governed-skill-evolution
Governed Skill Evolution from Persistent Agent Experience
Prospective ablation and cross-model transfer study of three experience-retention conditions for governed Agent Skill evolution: no persistent history, flat chronological history, and a persistent Pattern Registry with a forward-chained Skill Impact Ledger.
Author: Song Luo
Version: 1.0.0
Source snapshot: d717c32396cfff1bef2800296541a70e9b4cabb8
Canonical repository: rrrrrredy/governed-skill-evolution
Zenodo:… See the full description on the dataset page: https://huggingface.co/datasets/RedinGhost/governed-skill-evolution.Public_Announcement_Global_Intelligence_Shift_R_Evolution