#text-classification tag

In our approach to lot zoning, we focus on identifying relevant text content areas, specifically targeting the selection of pages and tables that describe lot references and items.

Data science

#text-classification#text-classification

TnT-LLM: Automating Text Taxonomy Generation and Classification With Large Language Models | HackerNoon

Additional Results: Cross-Lingual Taxonomy Evaluation and In-Depth Classification Analysis | HackerNoon

TnT-LLM Implementation Details: Pipeline Design, Robustness, and Efficiency | HackerNoon

TnT-LLM: Automating Text Taxonomy Generation and Classification With Large Language Models | HackerNoon

Additional Results: Cross-Lingual Taxonomy Evaluation and In-Depth Classification Analysis | HackerNoon

TnT-LLM Implementation Details: Pipeline Design, Robustness, and Efficiency | HackerNoon

TnT-LLM: LLMs for Automated Text Taxonomy and Classification | HackerNoon

Evaluating TnT-LLM Text Classification: Human Agreement and Scalable LLM Metrics | HackerNoon

R.E.D.: Scaling Text Classification with Expert Delegation

Data Annotation: Overview of the Main Types

Evaluating TnT-LLM: Automatic, Human, and LLM-Based Assessment | HackerNoon

TnT-LLM: LLMs for Automated Text Taxonomy and Classification | HackerNoon

Evaluating TnT-LLM Text Classification: Human Agreement and Scalable LLM Metrics | HackerNoon

R.E.D.: Scaling Text Classification with Expert Delegation

Data Annotation: Overview of the Main Types

Evaluating TnT-LLM: Automatic, Human, and LLM-Based Assessment | HackerNoon

How Vamstar Identifies Relevant Content for Lots in Tender Documents | HackerNoon

#text-classification
#text-classification