1 code implementation • 27 Mar 2024 • Zhichao Xu
In this work, we examine \mamba's efficacy through the lens of a classical IR task -- document ranking.
no code implementations • 18 Feb 2024 • Zhichao Xu, Jiepu Jiang
Prior efforts to measure conversational empathy mostly focus on expressed communicative intents -- that is, the way empathy is expressed.
no code implementations • 18 Feb 2024 • Zhichao Xu, Daniel Cohen, Bei Wang, Vivek Srikumar
Inspired by the idea of learning from label proportions, we propose two principles for in-context example ordering guided by model's probability predictions.
1 code implementation • 21 Dec 2023 • Zhichao Xu
Query-focused summarization (QFS) aims to provide a summary of a single document/multi documents that can satisfy the information needs of a given query.
no code implementations • 26 May 2023 • Tao Yang, Zhichao Xu, Zhenduo Wang, Qingyao Ai
However, we find that most existing fair ranking methods adopt greedy algorithms that only optimize rankings for the next immediate session or request.
1 code implementation • 23 Apr 2023 • Zhichao Xu, Daniel Cohen
Query-focused summarization (QFS) aims to provide a summary of a document that satisfies information need of a given query and is useful in various IR applications, such as abstractive snippet generation.
no code implementations • 17 Apr 2023 • Zhenduo Wang, Zhichao Xu, Qingyao Ai
In this paper, we propose a reward-free conversation policy imitation learning framework, which can train a conversation policy without annotated conversation data or manually designed rewards.
no code implementations • 17 Apr 2023 • Zhenduo Wang, Zhichao Xu, Qingyao Ai, Vivek Srikumar
Our goal is to supplement existing work with an insightful hand-analysis of unsolved challenges by the baseline and propose our solutions.
no code implementations • 25 Jan 2023 • Zhichao Xu, Hemank Lamba, Qingyao Ai, Joel Tetreault, Alex Jaimes
In this work, we aim to investigate the effectiveness of this perspective via proposing and evaluating counterfactual explanations for the task of SeRE.
2 code implementations • 18 Dec 2022 • Tao Yang, Zhichao Xu, Zhenduo Wang, Anh Tran, Qingyao Ai
In MCFair, we first develop a ranking objective that includes uncertainty, fairness, and user utility.
1 code implementation • 23 Oct 2022 • Junfei Xiao, Zhichao Xu, Shiyi Lan, Zhiding Yu, Alan Yuille, Anima Anandkumar
The model is trained on a composite dataset consisting of images from 9 datasets (ADE20K, Cityscapes, Mapillary Vistas, ScanNet, VIPER, WildDash 2, IDD, BDD, and COCO) with a simple dataset balancing strategy.
no code implementations • 16 Aug 2022 • Zhichao Xu, Anh Tran, Tao Yang, Qingyao Ai
The results on simulated coarse-grained labeled dataset show that while using coarse-grained labels to train an RL model for LTR tasks still can not outperform traditional approaches using fine-grained labels, it still achieve somewhat promising results and is potentially helpful for future research in LTR.
1 code implementation • 10 Jun 2022 • Zhichao Xu, Yi Han, Tao Yang, Anh Tran, Qingyao Ai
Seeing this gap, we propose a model named Semantic-Enhanced Bayesian Personalized Explanation Ranking (SE-BPER) to effectively combine the interaction information and semantic information.
no code implementations • 6 Apr 2022 • Tao Yang, Zhichao Xu, Qingyao Ai
Result ranking often affects consumer satisfaction as well as the amount of exposure each item receives in the ranking services.
1 code implementation • 17 Jun 2021 • Zhichao Xu, Hansi Zeng, Qingyao Ai
We find that models utilizing only review information can not achieve better performances than vanilla implicit-feedback matrix factorization method.
no code implementations • 16 Jan 2021 • Hansi Zeng, Zhichao Xu, Qingyao Ai
User and item reviews are valuable for the construction of recommender systems.
no code implementations • 19 Aug 2020 • Zhichao Xu, Shuhong Chen
Consensus Sequences of event logs are often used in process mining to quickly grasp the core sequence of events to be performed in a process, or to represent the backbone of the process for doing other analyses.
no code implementations • 19 Aug 2020 • Zhichao Xu, Yi Han, Yongfeng Zhang, Qingyao Ai
In this paper, we interpret purchase utility as the satisfaction level a consumer gets from a product and propose a recommendation framework using EU to model consumers' behavioral patterns.