1 code implementation • 22 Nov 2024 • Wanqi Yang, Yanda Li, Meng Fang, Yunchao Wei, Tianyi Zhou, Ling Chen
We evaluate six state-of-the-art LLMs with voice interaction capabilities, including Gemini-1. 5-Pro, GPT-4o, and others, using three distinct evaluation methods on the CAA benchmark.
no code implementations • 25 Sep 2024 • Wanqi Yang, Yanda Li, Meng Fang, Ling Chen
Time-Sensitive Question Answering (TSQA) demands the effective utilization of specific temporal contexts, encompassing multiple time-evolving facts, to address time-sensitive questions.
no code implementations • 5 Aug 2024 • Yanda Li, Chi Zhang, Wanqi Yang, Bin Fu, Pei Cheng, Xin Chen, Ling Chen, Yunchao Wei
In the deployment phase, RAG technology enables efficient retrieval and update from this knowledge base, thereby empowering the agent to perform tasks effectively and accurately.
no code implementations • 17 Jul 2024 • Wanqi Yang, Yunqiu Xu, Yanda Li, Kunze Wang, Binbin Huang, Ling Chen
In this study, we explore an emerging research area of Continual Learning for Temporal Sensitive Question Answering (CLTSQA).
no code implementations • 4 Jul 2024 • Wanqi Yang, Haoran Wang, Lei Wang, Ge Song, Yang Gao
However, current FS-UDA methods are still suffer from two issues: 1) the data from different domains can not be effectively aligned by few-shot labeled data due to the large domain gaps, 2) it is unstable and time-consuming to generalize to new FS-UDA tasks. To address this issue, we put forward a novel Efficient Meta Prompt Learning Framework for FS-UDA.
no code implementations • 2 Jul 2024 • Shulei Qiu, Wanqi Yang, Ming Yang
In HFRP, we fuse the channel features and the spatial features.
no code implementations • 2 Jul 2024 • Yuquan Xie, Wanqi Yang, Jinyu Wei, Ming Yang, Yang Gao
To address this issue, we propose a domain generalization approach for knowledge tracing, where existing education systems are considered source domains, and new education systems with limited data are considered target domains.
no code implementations • 1 Jul 2024 • Like Xin, Wanqi Yang, Lei Wang, Ming Yang
In cross-view learning, reliable view guidance enhances the confidence of the cluster structures in other views.
no code implementations • 27 Apr 2024 • Like Xin, Wanqi Yang, Lei Wang, Ming Yang
We assume that the view with a good cluster structure is the reliable view, which acts as a supervisor to guide the clustering of the other views.
no code implementations • 5 Jan 2023 • Lei Yu, Wanqi Yang, Shengqi Huang, Lei Wang, Ming Yang
However, the goal of FS-UDA and FSL are relevant yet distinct, since FS-UDA aims to classify the samples in target domain rather than source domain.
no code implementations • 6 Aug 2021 • Shengqi Huang, Wanqi Yang, Lei Wang, Luping Zhou, Ming Yang
Inspired by the recent local descriptor based few-shot learning (FSL), our general UDA model is fully built upon local descriptors (LDs) for image classification and domain adaptation.
no code implementations • 31 Jul 2020 • Yinghuan Shi, Wanqi Yang, Kim-Han Thung, Hao Wang, Yang Gao, Yang Pan, Li Zhang, Dinggang Shen
Then, we build a novel computer-aided prescription model by learning the relation between observed symptoms and prescription drug.
no code implementations • 20 Apr 2020 • Wanqi Yang, Tong Ling, Chengmei Yang, Lei Wang, Yinghuan Shi, Luping Zhou, Ming Yang
To address this issue, we propose a novel approach called Conditional ADversarial Image Translation (CADIT) to explicitly align the class distributions given samples between the two domains.
1 code implementation • 27 Apr 2018 • Jinquan Sun, Yinghuan Shi, Yang Gao, Lei Wang, Luping Zhou, Wanqi Yang, Dinggang Shen
In this paper, we present a novel method for interactive medical image segmentation with the following merits.