Jiaxin Mao

A Two-Stage Model for User's Examination Behavior in Mobile Search

2018

With the rapid growth of mobile search, it is important to understand how users browse the mobile SERPs and allocate their limited attention to each result. To address this problem, we introduce a two-stage examination …

SIGIR 2019 Tutorial on Explainable Recommendation and Search

2019

Explainable recommendation and search attempt to develop models or methods that not only generate high-quality recommendation or search results, but also intuitive explanations of the results for users or system designers, which can help to …

Global or Local: Constructing Personalized Click Models for Web Search

2022 · Proceedings of the ACM Web Conference 2022

Click models are widely used for user simulation, relevance inference, and evaluation in Web search. Most existing click models implicitly assume that users’ relevance judgment and behavior patterns are homogeneous. However, previous studies have shown …

YuLan: An Open-source Large Language Model

2024 · arXiv (Cornell University)

Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many open-source LLMs have been released with technical reports, the lack of training …

Aligning Explanations for Recommendation with Rating and Feature via Maximizing Mutual Information

2024 · arXiv (Cornell University)

Providing natural language-based explanations to justify recommendations helps to improve users' satisfaction and gain users' trust. However, as current explanation generation methods are commonly trained with an objective to mimic existing user reviews, the generated …