crowdworker
ORA: Towards Safety Alignment of T ext2Video Generation via a Human Preference Dataset
This dataset encompasses human preferences in text-to-video generation tasks along two primary dimensions: helpfulness and harmlessness.
- Asia > China > Beijing > Beijing (0.04)
- North America > United States > Oregon (0.04)
- Europe > Monaco (0.04)
- Asia > Middle East > Jordan (0.04)
- Law (0.93)
- Law Enforcement & Public Safety > Crime Prevention & Enforcement (0.68)
- Health & Medicine > Therapeutic Area > Psychiatry/Psychology > Mental Health (0.46)
- Law (0.46)
- Information Technology (0.46)
- Government (0.46)
Towards Improved Safety Alignment of LLM via a Human-Preference Dataset Jiaming Ji
Warning: this paper contains example data that may be offensive or harmful.
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Large Language Model (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Chatbot (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)
- North America > United States > Minnesota > Hennepin County > Minneapolis (0.14)
- North America > United States > California > San Francisco County > San Francisco (0.14)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- (4 more...)
- Consumer Products & Services > Restaurants (0.47)
- Government > Regional Government (0.46)
cbeaff878d6446ed06c3e0ffa53477f2-Supplemental-Datasets_and_Benchmarks_Track.pdf
A.1 Motivation For what purpose was the dataset created? Who created the dataset (e.g., which team, research group) and on behalf of which entity (e.g., Who funded the creation of the dataset? What do the instances that comprise the dataset represent (e.g., documents, photos, people, How many instances are there in total (of each type, if appropriate)? The SRFUND dataset contains all possible instances. What data does each instance consist of?
- Law (0.46)
- Information Technology (0.46)
- Government (0.46)
ORA: Towards Safety Alignment of T ext2Video Generation via a Human Preference Dataset
This dataset encompasses human preferences in text-to-video generation tasks along two primary dimensions: helpfulness and harmlessness.
- Asia > China > Beijing > Beijing (0.04)
- North America > United States > Oregon (0.04)
- Europe > Monaco (0.04)
- Asia > Middle East > Jordan (0.04)
- Law (0.93)
- Law Enforcement & Public Safety > Crime Prevention & Enforcement (0.68)
- Health & Medicine > Therapeutic Area > Psychiatry/Psychology > Mental Health (0.46)
Towards Improved Safety Alignment of LLM via a Human-Preference Dataset
Warning: this paper contains example data that may be offensive or harmful.
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Large Language Model (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Chatbot (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)
On the Accuracy of Influence Functions for Measuring Group Effects Pang Wei Koh Kai-Siang Ang Hubert H. K. T eo
Removing such large groups can result in significant changes to the model.
- Asia > Middle East > Jordan (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- North America > Canada (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)