291 citations · 592 across the 16 of their papers we have counts for
16 papers
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
Jianghao Lin, Bo Chen, Hangyu Wang +7
Click-through rate (CTR) prediction has become increasingly indispensable for various Internet applications. Traditional CTR models convert the multi-field categorical data into ID…
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction
Jianghao Lin, Yanru Qu, Wei Guo +4
With the widespread application of personalized online services, click-through rate (CTR) prediction has received more and more attention and research. The most prominent features…
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction
Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao +14
Diabetes prediction is an important data science application in the social healthcare domain. There exist two main challenges in the diabetes prediction task: data heterogeneity si…
A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation
Dinghan Shen, Mingzhi Zheng, Yelong Shen +2
Adversarial training has been shown effective at endowing the learned representations with stronger generalization ability. However, it typically requires expensive computation to…
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding
Yanru Qu, Dinghan Shen, Yelong Shen +3
Data augmentation has been demonstrated as an effective strategy for improving model generalization and data efficiency. However, due to the discrete nature of natural language, de…
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning
Yuning Mao, Yanru Qu, Yiqing Xie +2
While neural sequence learning methods have made significant progress in single-document summarization (SDS), they produce unsatisfactory results on multi-document summarization (M…
GIKT: A Graph-based Interaction Model for Knowledge Tracing
Yang Yang, Jian Shen, Yanru Qu +5
With the rapid development in online education, knowledge tracing (KT) has become a fundamental problem which traces students' knowledge status and predicts their performance on ne…
An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation
Yanru Qu, Ting Bai, Weinan Zhang +2
This paper studies graph-based recommendation, where an interaction graph is constructed from historical records and is lever-aged to alleviate data sparsity and cold start problem…
Dynamically Fused Graph Network for Multi-hop Reasoning
Yunxuan Xiao, Yanru Qu, Lin Qiu +4
Text-based question answering (TBQA) has been studied extensively in recent years. Most existing approaches focus on finding the answer to a question within a single paragraph. How…
Sampled in Pairs and Driven by Text: A New Graph Embedding Framework
Liheng Chen, Yanru Qu, Zhenghui Wang +5
In graphs with rich texts, incorporating textual information with structural information would benefit constructing expressive graph embeddings. Among various graph embedding model…
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
Yanru Qu, Bohui Fang, Weinan Zhang +5
User response prediction is a crucial component for personalized information retrieval and filtering scenarios, such as recommender system and web search. The data in user response…
Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition
Zhenghui Wang, Yanru Qu, Liheng Chen +7
We study the problem of named entity recognition (NER) from electronic medical records, which is one of the most fundamental and critical problems for medical text mining. Medical…
QA4IE: A Question Answering based Framework for Information Extraction
Lin Qiu, Hao Zhou, Yanru Qu +7
Information Extraction (IE) refers to automatically extracting structured relation tuples from unstructured texts. Common IE solutions, including Relation Extraction (RE) and open…
Collaborative Filtering with Graph-based Implicit Feedback
Minzhe Niu, Weinan Zhang, Yanru Qu +4
Introducing consumed items as users' implicit feedback in matrix factorization (MF) method, SVD++ is one of the most effective collaborative filtering methods for personalized reco…
Wasserstein Distance Guided Representation Learning for Domain Adaptation
Jian Shen, Yanru Qu, Weinan Zhang +1
Domain adaptation aims at generalizing a high-performance learner on a target domain via utilizing the knowledge distilled from a source domain which has a different but related da…
Product-based Neural Networks for User Response Prediction
Yanru Qu, Han Cai, Kan Ren +4
Predicting user responses, such as clicks and conversions, is of great importance and has found its usage in many Web applications including recommender systems, web search and onl…