Chuan Ying Liew

Key Skills

Software

Data Annotation Tech

Mindrift

Telus

Other

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Evaluation Rating

Prompt Response Writing SFT

Translation Localization

Freelancer Overview

An experienced prompt + response writer and LLM evaluator, my project experience has revolved heavily around writing locale-specific prompts and responses in English, Singlish and teaching basic Math. I also have experience in mapping training for AI. I have worked on projects across multiple AI platforms, such as Data Annotation Tech, Stellar AI, Mindrift, and Outlier. With good performance and having put in many hours into each of the projects I have worked on, I have also been included in conducting extensive reviews and evaluation of prompts and responses written by other workers.

Labeling Experience

Simulated Worlds

OtherTextMappingPrompt Response Writing SFT

The Simulated Worlds project on Stellar AI focuses on training the AI model to be able to understand and perform multi-stepped instructions provided on a smartphone layout and to navigate the smartphone layout and applications. The tasks involve writing an initial instruction prompt, writing the subsequent response prompts + actions, mapping the actions according to priority and which should take place first logically, and understand what prompts should result in what actions to be taken on the relevant smartphone applications. The project involved hundreds of workers globally. Each submitted task undergoes a thorough evaluation from the project managers for a period of about a month before they deem workers as competent or requiring more training. All submitted tasks are also subject to peer reviews and evaluation. Poor performance will lead to the removal from projects immediately.

The Simulated Worlds project on Stellar AI focuses on training the AI model to be able to understand and perform multi-stepped instructions provided on a smartphone layout and to navigate the smartphone layout and applications. The tasks involve writing an initial instruction prompt, writing the subsequent response prompts + actions, mapping the actions according to priority and which should take place first logically, and understand what prompts should result in what actions to be taken on the relevant smartphone applications. The project involved hundreds of workers globally. Each submitted task undergoes a thorough evaluation from the project managers for a period of about a month before they deem workers as competent or requiring more training. All submitted tasks are also subject to peer reviews and evaluation. Poor performance will lead to the removal from projects immediately.

2024

Argon Project

Data Annotation TechTextPrompt Response Writing SFT

The Argon Project focuses on creating and refining localised LLMs that understand each region's language and nuances (e.g. Singlish for Singapore). The project involves a variety of tasks that primarily involve prompt and response writing for various different topics and subjects, but all have to include appropriate locale-specific language. All work done on the project is cross-checked by other workers on the platform through paid reviews. All work is also guided by thorough and strict guidelines to make sure that the work submitted is of a certain standard.

The Argon Project focuses on creating and refining localised LLMs that understand each region's language and nuances (e.g. Singlish for Singapore). The project involves a variety of tasks that primarily involve prompt and response writing for various different topics and subjects, but all have to include appropriate locale-specific language. All work done on the project is cross-checked by other workers on the platform through paid reviews. All work is also guided by thorough and strict guidelines to make sure that the work submitted is of a certain standard.

2024

Education

Work History