SOTAVerified

Attribute Value Extraction

Attribute Value Extraction is the task of extracting values for a given set of attributes of interest from free text input. Attribute value extraction is for example applied in the context of e-commerce where product attribute values are extracted from product offers.

The related task Attribute Mining assume that the target attribute set is unknown, while attribute value extraction assumes that the attribute set is given. Multimodal Attribute Extraction aims at extracting attribute values from multi-modal input such as text plus images.

Papers

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Showing 1–10 of 35 papers

TitleStatusHype
Visual Zero-Shot E-Commerce Product Attribute Value Extraction—0
Automated Self-Refinement and Self-Correction for LLM-based Product Attribute Value ExtractionCode0
An Empirical Comparison of Generative Approaches for Product Attribute-Value IdentificationCode0
EAVE: Efficient Product Attribute Value Extraction via Lightweight Sparse-layer Interaction—0
PAE: LLM-based Product Attribute Extraction for E-Commerce Fashion Trends—0
ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value ExtractionCode1
EIVEN: Efficient Implicit Attribute Value Extraction using Multimodal LLM—0
Using LLMs for the Extraction and Normalization of Product Attribute ValuesCode1
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction—0
Multi-Label Zero-Shot Product Attribute-Value ExtractionCode0
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All datasetsWDC-PAVEMAVEAE-110kOA-Mine - annotations

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MAVEQAF1-score98.32—Unverified
2AVEQAF1-score98.14—Unverified
3AD-OpentagF1-score79.73—Unverified