activity
20202023
most citedUncovering ChatGPT's Capabilities in Recommender Systems

187 citations · 345 across the 14 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cs.IR2022★ 23 cited

Law Article-Enhanced Legal Case Matching: a Causal Learning Approach

Zhongxiang Sun, Jun Xu, Xiao Zhang +2

Legal case matching, which automatically constructs a model to estimate the similarities between the source and target cases, has played an essential role in intelligent legal syst…

cs.LG2022★ 1 cited

Reward Imputation with Sketching for Contextual Batched Bandits

Xiao Zhang, Ninglu Shao, Zihua Si +4

Contextual batched bandit (CBB) is a setting where a batch of rewards is observed from the environment at the end of each episode, but the rewards of the non-executed actions are u…

cs.IR2022★ 3 cited

Reinforcement Re-ranking with 2D Grid-based Recommendation Panels

Sirui Chen, Xiao Zhang, Xu Chen +4

Modern recommender systems usually present items as a streaming, one-dimensional ranking list. Recently there is a trend in e-commerce that the recommended items are organized grid…

cs.IR2022

Unbiased Top-k Learning to Rank with Causal Likelihood Decomposition

Haiyuan Zhao, Jun Xu, Xiao Zhang +3

Unbiased learning to rank has been proposed to alleviate the biases in the search ranking, making it possible to train ranking models with user interaction data. In real applicatio…

cs.IR2022★ 42 cited

A Model-Agnostic Causal Learning Framework for Recommendation using Search Data

Zihua Si, Xueran Han, Xiao Zhang +4

Machine-learning based recommender systems(RSs) has become an effective means to help people automatically discover their interests. Existing models often represent the rich inform…