no code implementations • 19 May 2024 • Congchi Yin, Ziyi Ye, Piji Li
It consists of a main decoding network for language reconstruction and a side network for predictive coding.
no code implementations • 1 Apr 2024 • Shaorun Zhang, Zhiyu He, Ziyi Ye, Peijie Sun, Qingyao Ai, Min Zhang, Yiqun Liu
To address these challenges and provide a more comprehensive understanding of user affective experience and cognitive activity, we propose EEG-SVRec, the first EEG dataset with User Multidimensional Affective Engagement Labels in Short Video Recommendation.
no code implementations • 20 Mar 2024 • Ruizhe Zhang, Qingyao Ai, Ziyi Ye, Yueyue Wu, Xiaohui Xie, Yiqun Liu
Traditional feedback signal such as clicks is too coarse to use as they do not reflect any fine-grained relevance information.
1 code implementation • 24 Feb 2024 • Ziyi Ye, Jingtao Zhan, Qingyao Ai, Yiqun Liu, Maarten de Rijke, Christina Lioma, Tuukka Ruotsalo
If the quality of the initially retrieved documents is low, then the effectiveness of query augmentation would be limited as well.
1 code implementation • 9 Dec 2023 • Ziyi Ye, Xiaohui Xie, Qingyao Ai, Yiqun Liu, Zhihong Wang, Weihang Su, Min Zhang
To explore the effectiveness of brain signals in the context of RF, we propose a novel RF framework that combines BCI-based relevance feedback with pseudo-relevance signals and implicit signals to improve the performance of document re-ranking.
1 code implementation • 16 Nov 2023 • Ziyi Ye, Qingyao Ai, Yiqun Liu, Maarten de Rijke, Min Zhang, Christina Lioma, Tuukka Ruotsalo
Inspired by recent research that revealed associations between the brain and the large computational language models, we propose a generative language BCI that utilizes the capacity of a large language model (LLM) jointly with a semantic brain decoder to directly generate language from functional magnetic resonance imaging (fMRI) input.
1 code implementation • 27 Sep 2023 • Kaiyuan Zhang, Ziyi Ye, Qingyao Ai, Xiaohui Xie, Yiqun Liu
Recognizing this shortfall, there has been a burgeoning interest in recent years in harnessing the potential of Graph Neural Networks (GNN) to exploit the topological information by modeling features selected from each EEG channel in a graph structure.
1 code implementation • 17 Aug 2022 • Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma
We explore the effectiveness of BTA for satisfaction modeling in two popular information access scenarios, i. e., search and recommendation.
no code implementations • 14 Oct 2021 • Xuesong Chen, Ziyi Ye, Xiaohui Xie, Yiqun Liu, Weihang Su, Shuqi Zhu, Min Zhang, Shaoping Ma
While search technologies have evolved to be robust and ubiquitous, the fundamental interaction paradigm has remained relatively stable for decades.
no code implementations • 22 Sep 2021 • Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuancheng Li, Jiaji Li, Xuesong Chen, Min Zhang, Shaoping Ma
Inspired by these findings, we conduct supervised learning tasks to estimate the usefulness of non-click results with brain signals and conventional information (i. e., content and context factors).
no code implementations • 19 Aug 2021 • Zirui Zhu, Ziyi Ye
Federated Learning (FL) is a privacy-protected machine learning paradigm that allows model to be trained directly at the edge without uploading data.
1 code implementation • 3 Aug 2021 • Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma
In this paper, we carefully design a lab-based user study to investigate brain activities during reading comprehension.