Search Results for author: Ziyi Ye

Found 10 papers, 6 papers with code

Improving Legal Case Retrieval with Brain Signals

no code implementations20 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.

EEG Retrieval

Query Augmentation by Decoding Semantics from Brain Signals

1 code implementation24 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.

Document Ranking

Relevance Feedback with Brain Signals

1 code implementation9 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.

Brain Computer Interface Re-Ranking

Language Generation from Brain Recordings

1 code implementation16 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.

Language Modelling Large Language Model +2

GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network

1 code implementation27 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.

Classification EEG

Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System

1 code implementation17 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.

EEG Electroencephalogram (EEG) +2

Web Search via an Efficient and Effective Brain-Machine Interface

no code implementations14 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.

EEG Electroencephalogram (EEG)

Why Don't You Click: Neural Correlates of Non-Click Behaviors in Web Search

no code implementations22 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).

EEG Electroencephalogram (EEG)

Towards More Efficient Federated Learning with Better Optimization Objects

no code implementations19 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.

Federated Learning

Towards a Better Understanding Human Reading Comprehension with Brain Signals

1 code implementation3 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.

EEG Electroencephalogram (EEG) +5

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