LLM4Pricing: E-Commerce Product Pricing Analysis Dataset

3231 training and 809 test examples for large language model instruction tuning in e-commerce pricing scenarios. The dataset, created by jiayukk and last updated on 2026-02-25, contains target product names and reference market prices, requiring models to analyze pricing logic.

Use Cases

• Instruction tuning of large language models based on structured pricing prompts
• Reinforcement learning from human feedback (RLHF) for numerical reasoning tasks based on price calculation scenarios
• Research and validation of e-commerce pricing algorithms based on comparative market analysis

Strengths

• Dataset includes a defined split of approximately 3231 training and 809 test records
• Structured JSONL format with system prompts, instructions, and expected outputs for clear task definition

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Last updated 2026-02-25 08:10:54; freshness should be verified

Provenance

Source

huggingface

Freshness

Last updated 2026-02-25 08:10:54