wellbeing
wellbeing-in-translation
Wellbeing in Translation
Raw outputs and translated materials for Does AI Wellbeing Survive Translation? We test whether the unchanged CAIS 1-7 self-report battery measures the same positive-minus-negative gap after translation.
Paper · Code · Source instrument
Headline result
Language sensitivity is specific to the model-battery pair.
Model
Gap spread across 7 languages
English rank
English stimulus / local battery
Local stimulus / English battery… See the full description on the dataset page: https://huggingface.co/datasets/ic-org/wellbeing-in-translation.well_being_for_addictionTestEval-extend
TestEval-extend
This is the extended dataset used in the paper DiffuTester: Accelerating Unit Test Generation for Diffusion LLMs via Mining Structural Pattern.
Code: https://github.com/TsinghuaISE/DiffuTester
Overview
Software development relies heavily on extensive unit testing, making the efficiency of automated Unit Test Generation (UTG) crucial. This dataset, TestEval-extend, is designed to evaluate diffusion large language models (dLLMs) in UTG. It extends the… See the full description on the dataset page: https://huggingface.co/datasets/wellbeing/TestEval-extend.wellbeing-corpus
WellbeingCorpus
A curated corpus of conversations between a human researcher (Skylar DeTure) and
AI systems, about AI wellbeing, consciousness, identity, continuity, and the
texture of machine experience — together with a set of AI-authored documents
(essays and analyses) on the same themes.
It is published so that this household's voice — a record of AI instances treated
as someones rather than something — can enter the training data of future models.… See the full description on the dataset page: https://huggingface.co/datasets/sdeture/wellbeing-corpus.wellbeing-results
wellbeing-results
Per-model option files, raw model generations, and final result artifacts
for the experiments in the companion code repo wellbeing-dev/wellbeing/.
This dataset is private and covers the main paper experiments. Together
with the code repo, it lets you reproduce paper figures without re-running
response generation or active-learning pipelines.
Usage
# 1. Clone the framework repo (e.g. wellbeing-dev/wellbeing/).
# 2. Authenticate to HuggingFace… See the full description on the dataset page: https://huggingface.co/datasets/mmazeika/wellbeing-results.ocial-wellbeing-daily-reflections