Papers by Yindu Su

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.
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.
RIVA: A Pre-trained Tweet Multimodal Model Based on Text-image Relation for Multimodal NER (2020.coling-main)

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Challenge: Named entity recognition (MNER) for tweets is a key task of many applications.
Approach: They propose a pre-trained multimodal named entity recognition model based on Relationship Inference and Visual Attention (RIVA) for tweets.
Outcome: The proposed model improves on the multimodal named entity recognition (MNER) task on tweets with the aid of visual clues.

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