activity
20142024
most citedLarge Scale Purchase Prediction with Historical User Actions on B2C Online Retail Platform

9 citations · 17 across the 11 of their papers we have counts for

collaborators

11 papers

cs.IR2024

A Taxation Perspective for Fair Re-ranking

Chen Xu, Xiaopeng Ye, Wenjie Wang +3

Fair re-ranking aims to redistribute ranking slots among items more equitably to ensure responsibility and ethics. The exploration of redistribution problems has a long history in…

cs.IR20242 cited

A Survey of Generative Search and Recommendation in the Era of Large Language Models

Yongqi Li, Xinyu Lin, Wenjie Wang +6

With the information explosion on the Web, search and recommendation are foundational infrastructures to satisfying users' information needs. As the two sides of the same coin, bot…

cs.RO2023

PLV-IEKF: Consistent Visual-Inertial Odometry using Points, Lines, and Vanishing Points

Tong Hua, Tao Li, Liang Pang +4

In this paper, we propose an Invariant Extended Kalman Filter (IEKF) based Visual-Inertial Odometry (VIO) using multiple features in man-made environments. Conventional EKF-based V…

cs.IR2023

Plot Retrieval as an Assessment of Abstract Semantic Association

Shicheng Xu, Liang Pang, Jiangnan Li +5

Retrieving relevant plots from the book for a query is a critical task, which can improve the reading experience and efficiency of readers. Readers usually only give an abstract an…

cs.CL2023

RegaVAE: A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language Modeling

Jingcheng Deng, Liang Pang, Huawei Shen +1

Retrieval-augmented language models show promise in addressing issues like outdated information and hallucinations in language models (LMs). However, current research faces two mai…

cs.CL2023

Multi-level Adaptive Contrastive Learning for Knowledge Internalization in Dialogue Generation

Chenxu Yang, Zheng Lin, Lanrui Wang +6

Knowledge-grounded dialogue generation aims to mitigate the issue of text degeneration by incorporating external knowledge to supplement the context. However, the model often fails…