Yy Z.

Key Skills

Software

Other

Top Subject Matter

LLM response evaluation and quality rating

Multilingual text annotation (Chinese)

Search result quality review

Top Data Types

Text

Image

Top Task Types

Classification

Data Collection

Freelancer Overview

AI response evaluation practice. Core strengths include Other and Microsoft Excel. Education includes Recent Graduate, Zhejiang Sci-Tech University. AI-training focus includes data types such as Text and Image and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Image-text classification preparation

ImageClassification

Prepared for image-text classification by describing visual content and aligning it with appropriate captions. The practice included flagging unclear or low-quality examples to maintain dataset reliability. The workflow required careful observation and consistent annotation. • Described visual content from images • Matched captions to images • Flagged unclear, ambiguous, or low-quality examples • Maintained consistency across classification decisions

2026 - Present

Data cleaning practice

TextData Collection

Practiced data cleaning and dataset preparation for small text collections stored in spreadsheets. The work included removing duplicates, checking missing fields, and preparing structured notes for later review. Quality control emphasized completeness and consistency. • Organized small text datasets in spreadsheets • Removed duplicate entries • Checked and flagged missing fields • Prepared structured notes for review

2026 - Present

Search result quality review practice

OtherText

Practiced reviewing search results to verify that web content matches user queries. The work involved identifying irrelevant results and evaluating overall response quality. Findings were organized to clearly summarize quality issues. • Checked whether results matched the given query intent • Identified irrelevant or mismatched content • Summarized quality problems in a structured way • Focused on objective review criteria

2026 - Present

Chinese text annotation practice

TextClassification

Practiced annotating Chinese short texts by assigning labels for topic, sentiment, intent, and quality level. Annotation decisions were made to remain consistent with provided guidelines. The task emphasized careful reading, guideline interpretation, and error identification. • Labeled texts for topic, sentiment, intent, and quality tier • Ensured decisions matched written annotation guidelines • Performed consistency checking across similar examples • Identified and corrected labeling errors during review

2026 - Present

AI response evaluation practice

Text

Practiced evaluating AI responses by comparing answers across multiple quality dimensions against written expectations. The work focused on identifying issues related to helpfulness, accuracy, instruction following, safety, tone, and completeness. Outputs were reviewed for consistency and clear quality problem identification. • Compared model-generated answers using a structured rubric • Rated or flagged responses for quality gaps and policy/safety concerns • Checked completeness and whether instructions were followed • Summarized quality issues clearly for feedback

2026 - Present

Education

Work History