Papers by Yanling Cui

3 papers
TITA: A Two-stage Interaction and Topic-Aware Text Matching Model (2021.naacl-main)

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Challenge: Existing models for keyword-document matching do not define topic-aware relevance clearly.
Approach: They propose a two-stage interaction and topic-aware text matching model to solve this problem . they propose to combine latent topic of document with deep neural representation to model complex interactions between keyword and document.
Outcome: The proposed model outperforms other well-designed baselines and shows excellent performance in the recommendation system.
BiTIIMT: A Bilingual Text-infilling Method for Interactive Machine Translation (2022.acl-long)

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Challenge: Existing IMT systems relying on lexical constrained decoding (LCD) are limited in translation efficiency and quality due to LCD.
Approach: They propose a novel interactive neural machine translation system that uses lexical constraints to decode missing words in a manually revised translation.
Outcome: The proposed system performs significantly better and faster than state-of-the-art IMT on three translation tasks.
Enhancing Document Ranking with Task-adaptive Training and Segmented Token Recovery Mechanism (2021.emnlp-main)

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Challenge: Document Retrieval (DR) requires the machine to retrieve and rank documents according to their relevance with the query.
Approach: They propose a ranking model DR-BERT which improves the Document Retrieval task by a task-adaptive training process and a Segmented Token Recovery Mechanism.
Outcome: The proposed ranking model keeps in the top three on the MS MARCO leaderboard since 2020.

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