Hang Hoang

Key Skills

Software

Appen

Clickworker

Data Annotation Tech

Remotasks

Toloka

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Audio Recording

Classification

Evaluation Rating

Prompt Response Writing SFT

RLHF

Freelancer Overview

I have experience in LLM evaluation and AI training data, specializing in AI conversation rating and response writing in English and Vietnamese. I have worked on platforms like Scale AI, Dataannotation Tech, Appen, and Toloka AI, evaluating AI-generated dialogues for coherence, fluency, and relevance while identifying and refining weak responses to improve conversational flow. Beyond evaluation, I have expertise in data labeling, text annotation, and content refinement, ensuring AI-generated text is contextually accurate and engaging. My linguistic proficiency, cultural awareness, and analytical skills allow me to enhance AI chatbot interactions, contributing to more natural and effective language models.

Labeling Experience

LLM Safety Response Evaluation

Data Annotation TechTextEvaluation Rating

This role involves assessing AI-generated responses for safety, compliance, and ethical considerations. Responsibilities include evaluating whether the model’s outputs adhere to guidelines by identifying and mitigating risks such as bias, misinformation, harmful content, or inappropriate language. The task also involves providing feedback to enhance the model’s ability to generate responsible and neutral responses while maintaining relevance and engagement.

This role involves assessing AI-generated responses for safety, compliance, and ethical considerations. Responsibilities include evaluating whether the model’s outputs adhere to guidelines by identifying and mitigating risks such as bias, misinformation, harmful content, or inappropriate language. The task also involves providing feedback to enhance the model’s ability to generate responsible and neutral responses while maintaining relevance and engagement.

2024 - 2024

Multilingual Preference Ranking and Rewrites

Scale AITextPrompt Response Writing SFT

The purpose of this project is to improve the quality of responses generated by a Large Language Model (LLM) and create prompts on a variety of topics to test the model’s abilities across different dimensions. The task involves evaluating the model’s responses, providing ratings based on specific quality criteria, and determining which response is of higher overall quality. Depending on the quality of the preferred response, enhancements may be required, or suggestions may be provided to improve the model's performance.

The purpose of this project is to improve the quality of responses generated by a Large Language Model (LLM) and create prompts on a variety of topics to test the model’s abilities across different dimensions. The task involves evaluating the model’s responses, providing ratings based on specific quality criteria, and determining which response is of higher overall quality. Depending on the quality of the preferred response, enhancements may be required, or suggestions may be provided to improve the model's performance.

2024 - 2024

Education

Work History