Search Results for author: Hongyin Tang

Found 10 papers, 2 papers with code

Enhancing Document Ranking with Task-adaptive Training and Segmented Token Recovery Mechanism

no code implementations EMNLP 2021 Xingwu Sun, Yanling Cui, Hongyin Tang, Fuzheng Zhang, Beihong Jin, Shi Wang

In this paper, we propose a new ranking model DR-BERT, which improves the Document Retrieval (DR) task by a task-adaptive training process and a Segmented Token Recovery Mechanism (STRM).

Document Ranking Retrieval

GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language Model

1 code implementation11 Jun 2023 Shicheng Tan, Weng Lam Tam, Yuanchun Wang, Wenwen Gong, Yang Yang, Hongyin Tang, Keqing He, Jiahao Liu, Jingang Wang, Shu Zhao, Peng Zhang, Jie Tang

Currently, the reduction in the parameter scale of large-scale pre-trained language models (PLMs) through knowledge distillation has greatly facilitated their widespread deployment on various devices.

General Knowledge Knowledge Distillation +1

Inflected Forms Are Redundant in Question Generation Models

no code implementations1 Jan 2023 Xingwu Sun, Hongyin Tang, Chengzhong Xu

Secondly, we propose to adapt QG as a combination of the following actions in the encode-decoder framework: generating a question word, copying a word from the source sequence or generating a word transformation type.

Question Generation Question-Generation

VIRT: Improving Representation-based Models for Text Matching through Virtual Interaction

no code implementations8 Dec 2021 Dan Li, Yang Yang, Hongyin Tang, Jingang Wang, Tong Xu, Wei Wu, Enhong Chen

With the booming of pre-trained transformers, representation-based models based on Siamese transformer encoders have become mainstream techniques for efficient text matching.

Text Matching

TITA: A Two-stage Interaction and Topic-Aware Text Matching Model

no code implementations NAACL 2021 Xingwu Sun, Yanling Cui, Hongyin Tang, Qiuyu Zhu, Fuzheng Zhang, Beihong Jin

To tackle this problem, we define a three-level relevance in keyword-document matching task: topic-aware relevance, partially-relevance and irrelevance.

Text Matching Vocal Bursts Valence Prediction

Improving Document Representations by Generating Pseudo Query Embeddings for Dense Retrieval

no code implementations ACL 2021 Hongyin Tang, Xingwu Sun, Beihong Jin, Jingang Wang, Fuzheng Zhang, Wei Wu

Recently, the retrieval models based on dense representations have been gradually applied in the first stage of the document retrieval tasks, showing better performance than traditional sparse vector space models.

Clustering Retrieval

A Topic Augmented Text Generation Model: Joint Learning of Semantics and Structural Features

no code implementations IJCNLP 2019 Hongyin Tang, Miao Li, Beihong Jin

This model captures structural features by a sequential variational autoencoder component and leverages a topic modeling component based on Gaussian distribution to enhance the recognition of text semantics.

text-classification Text Classification +1

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