Papers by Yipeng Yu

3 papers
TaoType: Predicting Fine-Grained Typing Intent for Faster Search (2026.acl-industry)

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Challenge: Large-scale industrial ranking systems operate under stringent real-time performance requirements.
Approach: They propose a client-side framework that determines whether a user’s query is complete at each typing . this method leverages client-based typing behavior for real-time early prediction .
Outcome: The proposed framework achieves offline precision/recall/accuracy of 0.7936/0.8196/0.7742 and decreases online response time by 640.5193.65 milliseconds.
When and Who? Conversation Transition Based on Bot-Agent Symbiosis Learning Network (2020.coling-main)

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Challenge: a bot-agent symbiosis is a method for transparent conversation transition in online customer service applications.
Approach: They propose a bot-agent symbiosis approach to solve conversation transition problems . they provide user feedback and develop deep neural networks to predict the NPS .
Outcome: The proposed approach outperforms state-of-the-art methods on real-time data generated from an online service support platform.
SEAL: Structure and Element Aware Learning Improves Long Structured Document Retrieval (2025.emnlp-main)

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Challenge: Existing methods for document retrieval use contrastive learning on datasets lacking explicit structural information.
Approach: They propose a contrastive learning framework that preserves semantic hierarchies and masked element alignment for fine-grained semantic discrimination.
Outcome: The proposed framework preserves semantic hierarchies and masked element alignment for fine-grained semantic discrimination.

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