Papers by Huike Zou

3 papers
TACLR: A Scalable and Efficient Retrieval-based Method for Industrial Product Attribute Value Identification (2025.acl-long)

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Challenge: Existing methods for product attribute value identification face critical challenges . seller-provided attribute values are often incomplete or inaccurate .
Approach: They propose a retrieval-based method that uses taxonomy-aware contrastive learning . they use product profiles and candidate values to encode and retrieve attributes based on similarity .
Outcome: The proposed method is based on a taxonomy-aware, hard negative sampling and adaptive inference with dynamic thresholds.
GSID: Generative Semantic Indexing for E-Commerce Product Understanding (2025.emnlp-industry)

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Challenge: Structured product information is a major bottleneck for the efficiency of e-commerce platforms.
Approach: They propose a data-driven approach to generate product structured representations using product metadata.
Outcome: Extensive experiments show that GSID can generate better product representations on real-world e-commerce platforms.
Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification (2025.emnlp-industry)

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Challenge: Existing methods for product attribute value identification suffer from cascading errors and lack of generalization capability.
Approach: They propose a multi-level retrieval scheme that uses products and attribute values as distinct hierarchical levels in PAVI domain.
Outcome: The proposed method performs better than the state-of-the-art methods on a real-world industrial dataset.

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