47 citations · 142 across the 27 of their papers we have counts for
27 papers
Learning Robust Recommenders from Noisy Implicit Feedback via GMM-Weighted Bayesian Transition Matrix
Zongyu Li, Xuanyu Liu, Gongce Cao +3
Label noise is a central challenge in learning from implicit feedback for recommendation. Conventional approaches discard noisy examples for robustness, but this sacrifices data ef…
D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems
Jiarui Qin, Weiwen Liu, Ruiming Tang +2
A vast amount of user behavior data is constantly accumulating on today's large recommendation platforms, recording users' various interests and tastes. Preserving knowledge from t…
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing
Hangyu Wang, Ting Long, Liang Yin +6
Computerized Adaptive Testing(CAT) refers to an online system that adaptively selects the best-suited question for students with various abilities based on their historical respons…
Replace Scoring with Arrangement: A Contextual Set-to-Arrangement Framework for Learning-to-Rank
Jiarui Jin, Xianyu Chen, Weinan Zhang +5
Learning-to-rank is a core technique in the top-N recommendation task, where an ideal ranker would be a mapping from an item set to an arrangement (a.k.a. permutation). Most existi…
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…
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
Jianghao Lin, Rong Shan, Chenxu Zhu +6
With large language models (LLMs) achieving remarkable breakthroughs in natural language processing (NLP) domains, LLM-enhanced recommender systems have received much attention and…
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance
Yuchen Fang, Zhenggang Tang, Kan Ren +7
Order execution is a fundamental task in quantitative finance, aiming at finishing acquisition or liquidation for a number of trading orders of the specific assets. Recent advance…
Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation
Xianyu Chen, Jian Shen, Wei Xia +9
With the development of the online education system, personalized education recommendation has played an essential role. In this paper, we focus on developing path recommendation s…
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
Yunjia Xi, Weiwen Liu, Jianghao Lin +8
Recommender systems play a vital role in various online services. However, the insulated nature of training and deploying separately within a specific domain limits their access to…
How Can Recommender Systems Benefit from Large Language Models: A Survey
Jianghao Lin, Xinyi Dai, Yunjia Xi +11
With the rapid development of online services, recommender systems (RS) have become increasingly indispensable for mitigating information overload. Despite remarkable progress, con…
MADiff: Offline Multi-agent Learning with Diffusion Models
Zhengbang Zhu, Minghuan Liu, Liyuan Mao +5
Offline reinforcement learning (RL) aims to learn policies from pre-existing datasets without further interactions, making it a challenging task. Q-learning algorithms struggle wit…
Refined Edge Usage of Graph Neural Networks for Edge Prediction
Jiarui Jin, Yangkun Wang, Weinan Zhang +5
Graph Neural Networks (GNNs), originally proposed for node classification, have also motivated many recent works on edge prediction (a.k.a., link prediction). However, existing met…
Sim-to-Real Transfer for Quadrupedal Locomotion via Terrain Transformer
Hang Lai, Weinan Zhang, Xialin He +4
Deep reinforcement learning has recently emerged as an appealing alternative for legged locomotion over multiple terrains by training a policy in physical simulation and then trans…
A Bird's-eye View of Reranking: from List Level to Page Level
Yunjia Xi, Jianghao Lin, Weiwen Liu +5
Reranking, as the final stage of multi-stage recommender systems, refines the initial lists to maximize the total utility. With the development of multimedia and user interface des…
RITA: Boost Driving Simulators with Realistic Interactive Traffic Flow
Zhengbang Zhu, Shenyu Zhang, Yuzheng Zhuang +11
High-quality traffic flow generation is the core module in building simulators for autonomous driving. However, the majority of available simulators are incapable of replicating tr…
Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning
Hua Wei, Jingxiao Chen, Xiyang Ji +11
This paper introduces Honor of Kings Arena, a reinforcement learning (RL) environment based on Honor of Kings, one of the world's most popular games at present. Compared to other e…
Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems
Zhengbang Zhu, Rongjun Qin, Junjie Huang +4
Recommender systems are expected to be assistants that help human users find relevant information automatically without explicit queries. As recommender systems evolve, increasingl…
Multi-Scale User Behavior Network for Entire Space Multi-Task Learning
Jiarui Jin, Xianyu Chen, Weinan Zhang +5
Modelling the user's multiple behaviors is an essential part of modern e-commerce, whose widely adopted application is to jointly optimize click-through rate (CTR) and conversion r…
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning
Zeren Huang, Wenhao Chen, Weinan Zhang +7
Deriving a good variable selection strategy in branch-and-bound is essential for the efficiency of modern mixed-integer programming (MIP) solvers. With MIP branching data collected…
An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages
Lingyue Fu, Jianghao Lin, Weiwen Liu +4
To provide click simulation or relevance estimation based on users' implicit interaction feedback, click models have been much studied during recent years. Most click models focus…
Multi-Level Interaction Reranking with User Behavior History
Yunjia Xi, Weiwen Liu, Jieming Zhu +6
As the final stage of the multi-stage recommender system (MRS), reranking directly affects users' experience and satisfaction, thus playing a critical role in MRS. Despite the impr…
Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization
Minghuan Liu, Zhengbang Zhu, Yuzheng Zhuang +4
Recent progress in state-only imitation learning extends the scope of applicability of imitation learning to real-world settings by relieving the need for observing expert actions.…
Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection
Ting Long, Yutong Xie, Xianyu Chen +3
Program representation, which aims at converting program source code into vectors with automatically extracted features, is a fundamental problem in programming language processing…
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…