Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap | Paper Citation Record

Observation 6d3bc76b-e7e8-4cdf-917b-40839b686d66 · outbound

This paper cites Learning a hierarchical embedding model for personalized product search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Learning a hierarchical embedding model for personalized product search

Reference 1

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Observation 5fdf2ad4-871a-4f41-af02-d243927da88b · outbound

This paper cites A General Language Assistant as a Laboratory for Alignment.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap A General Language Assistant as a Laboratory for Alignment

Reference 2

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This paper cites Query expansion techniques for information retrieval: a survey.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Query expansion techniques for information retrieval: a survey

Reference 3

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This paper cites Modeling the impact of short-and long-term behavior on search person- alization.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Modeling the impact of short-and long-term behavior on search person- alization

Reference 4

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This paper cites A transformer-based embedding model for personalized product search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap A transformer-based embedding model for personalized product search

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:08.103443Z

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This paper cites Cross-Market Product Recommendation.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Cross-Market Product Recommendation

Reference 6

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This paper cites Multi-objective ranking optimization for product search using stochastic label aggregation.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Multi-objective ranking optimization for product search using stochastic label aggregation

Reference 7

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This paper cites Unsupervised learning of visual features by contrasting cluster as- signments.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Unsupervised learning of visual features by contrasting cluster as- signments

Reference 8

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This paper cites Towards a better understanding of query reformulation behavior in web search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Towards a better understanding of query reformulation behavior in web search

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:08.028696Z

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This paper cites UNITER: UNiversal Image-TExt Representation Learning.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap UNITER: UNiversal Image-TExt Representation Learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:08.006829Z

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This paper cites Detecting online commercial intention (OCI).

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Detecting online commercial intention (OCI)

Reference 11

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Observation 2ed725a5-826f-4398-ba5f-80915673fde1 · outbound

This paper cites Contrastive Learning for User Sequence Representation in Personalized Product Search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Contrastive Learning for User Sequence Representation in Personalized Product Search

Reference 12

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This paper cites A large-scale evaluation and analysis of personalized search strategies.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap A large-scale evaluation and analysis of personalized search strategies

Reference 13

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This paper cites Semantic models for the first-stage retrieval: A comprehensive review.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Semantic models for the first-stage retrieval: A comprehensive review

Reference 14

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This paper cites Ready to buy or just browsing? Detecting web searcher goals from interaction data.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Ready to buy or just browsing? Detecting web searcher goals from interaction data

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.915783Z

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This paper cites Attentive long short-term preference modeling for personalized product search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Attentive long short-term preference modeling for personalized product search

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.899433Z

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This paper cites Multi-modal preference modeling for product search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Multi-modal preference modeling for product search

Reference 17

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This paper cites Momentum contrast for unsupervised visual representation learning.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Momentum contrast for unsupervised visual representation learning

Reference 18

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This paper cites Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers

Reference 19

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This paper cites Extending CLIP for Category-to-image Retrieval in E-commerce.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Extending CLIP for Category-to-image Retrieval in E-commerce

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.849813Z

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This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 21

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Observation cb489cdc-4a5c-4c74-a622-e1dc1e19f284 · outbound

This paper cites Self-supervised product quantization for deep unsu- pervised image retrieval.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Self-supervised product quantization for deep unsu- pervised image retrieval

Reference 22

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This paper cites Billion-scale similarity search with GPUs.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Billion-scale similarity search with GPUs

Reference 23

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This paper cites Vilt: Vision-and-language transformer without convolution or region supervision.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Vilt: Vision-and-language transformer without convolution or region supervision

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.802233Z

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This paper cites Automatic identification of user goals in web search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Automatic identification of user goals in web search

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.787780Z

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This paper cites Align before fuse: Vision and language representation learning with momen- tum distillation.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Align before fuse: Vision and language representation learning with momen- tum distillation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.771159Z

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This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 27

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This paper cites Embedding-based product retrieval in taobao search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Embedding-based product retrieval in taobao search

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.741635Z

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This paper cites A reinforcement learning approach to online clustering.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap A reinforcement learning approach to online clustering

Reference 29

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This paper cites RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder

Reference 30

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This paper cites Universal Vision-Language Dense Retrieval: Learning A Unified Rep- resentation Space for Multi-Modal Retrieval.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Universal Vision-Language Dense Retrieval: Learning A Unified Rep- resentation Space for Multi-Modal Retrieval

Reference 31

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This paper cites Understanding behaviors that lead to purchasing: A case study of pinterest.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Understanding behaviors that lead to purchasing: A case study of pinterest

Reference 32

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This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision- and-language tasks.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Vilbert: Pretraining task-agnostic visiolinguistic representations for vision- and-language tasks

Reference 33

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This paper cites EI-CLIP: Entity-Aware Interventional Contrastive Learning for E-Commerce Cross-Modal Retrieval.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap EI-CLIP: Entity-Aware Interventional Contrastive Learning for E-Commerce Cross-Modal Retrieval

Reference 34

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This paper cites Semantic product search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Semantic product search

Reference 35

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This paper cites Learning transferable visual models from natural language supervision.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Learning transferable visual models from natural language supervision

Reference 36

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This paper cites Fashion-Gen: The Generative Fashion Dataset and Challenge.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Fashion-Gen: The Generative Fashion Dataset and Challenge

Reference 37

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This paper cites e-clip: Large-scale vision-language representation learning in e- commerce.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap e-clip: Large-scale vision-language representation learning in e- commerce

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.605754Z

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This paper cites Challenges and research opportunities in ecommerce search and recommendations.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Challenges and research opportunities in ecommerce search and recommendations

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.583764Z

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This paper cites Learning latent vector spaces for product search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Learning latent vector spaces for product search

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.559620Z

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This paper cites ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities

Reference 41

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Observation a5cfa667-a2e3-47cd-8255-914d09d0ecde · outbound

This paper cites Pseudo-relevance feedback for multiple representation dense retrieval.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Pseudo-relevance feedback for multiple representation dense retrieval

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.540385Z

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This paper cites The influence of image search intents on user behavior and satisfaction.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap The influence of image search intents on user behavior and satisfaction

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.523523Z

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This paper cites Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback

Reference 44

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This paper cites Commercemm: Large-scale commerce multimodal representation learning with omni retrieval.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Commercemm: Large-scale commerce multimodal representation learning with omni retrieval

Reference 45

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Source-reported events for the cited work

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This paper cites Product quantization network for fast image retrieval.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Product quantization network for fast image retrieval

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.487860Z

Source-reported events for the cited work

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This paper cites Towards personalized and semantic retrieval: An end-to-end solution for e-commerce search via embedding learning.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Towards personalized and semantic retrieval: An end-to-end solution for e-commerce search via embedding learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.467629Z

Source-reported events for the cited work

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This paper cites Collaborative quantization for cross-modal similarity search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Collaborative quantization for cross-modal similarity search

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.449803Z

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Observation 20c9b036-b97c-47be-aa9e-5fa486b87d91 · outbound

This paper cites Make: Vision-language pre-training based product retrieval in taobao search.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap Make: Vision-language pre-training based product retrieval in taobao search

Reference 49

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This paper cites PSSL: self-supervised learning for personalized search with contrastive sampling.

Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap PSSL: self-supervised learning for personalized search with contrastive sampling

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:10:07.416645Z

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