Zobrazeno 1 - 10
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pro vyhledávání: '"Chen, XinYue"'
Recently, federated multi-view clustering (FedMVC) has emerged to explore cluster structures in multi-view data distributed on multiple clients. Existing approaches often assume that clients are isomorphic and all of them belong to either single-view
Externí odkaz:
http://arxiv.org/abs/2410.09484
Large shared displays, such as digital whiteboards, are useful for supporting co-located team collaborations by helping members perform cognitive tasks such as brainstorming, organizing ideas, and making comparisons. While recent advancement in Large
Externí odkaz:
http://arxiv.org/abs/2409.13968
Memory-guided Network with Uncertainty-based Feature Augmentation for Few-shot Semantic Segmentation
Autor:
Chen, Xinyue, Shi, Miaojing
The performance of supervised semantic segmentation methods highly relies on the availability of large-scale training data. To alleviate this dependence, few-shot semantic segmentation (FSS) is introduced to leverage the model trained on base classes
Externí odkaz:
http://arxiv.org/abs/2406.00545
Autor:
Popov, Vitaliy, Chen, Xinyue, Wang, Jingying, Kemp, Michael, Sandhu, Gurjit, Kantor, Taylor, Mateju, Natalie, Wang, Xu
Publikováno v:
CHI'2024
Shared gaze visualizations have been found to enhance collaboration and communication outcomes in diverse HCI scenarios including computer supported collaborative work and learning contexts. Given the importance of gaze in surgery operations, especia
Externí odkaz:
http://arxiv.org/abs/2403.14561
Retrieval-augmented generation (RAG) has rapidly advanced the language model field, particularly in question-answering (QA) systems. By integrating external documents during the response generation phase, RAG significantly enhances the accuracy and r
Externí odkaz:
http://arxiv.org/abs/2402.01767
Autor:
Chen, Xinyue, Xu, Jie, Ren, Yazhou, Pu, Xiaorong, Zhu, Ce, Zhu, Xiaofeng, Hao, Zhifeng, He, Lifang
Federated multi-view clustering has the potential to learn a global clustering model from data distributed across multiple devices. In this setting, label information is unknown and data privacy must be preserved, leading to two major challenges. Fir
Externí odkaz:
http://arxiv.org/abs/2309.13697
Publikováno v:
CSCW October 2023
While videoconferencing is prevalent, concurrent participation channels are limited. People experience challenges keeping up with the discussion, and misunderstanding frequently occurs. Through a formative study, we probed into the design space of pr
Externí odkaz:
http://arxiv.org/abs/2309.12115
Autor:
Lian, Zhen, Meng, Yuze, Ma, Lei, Maity, Indrajit, Yan, Li, Wu, Qiran, Huang, Xiong, Chen, Dongxue, Chen, Xiaotong, Chen, Xinyue, Blei, Mark, Taniguchi, Takashi, Watanabe, Kenji, Tongay, Sefaattin, Lischner, Johannes, Cui, Yong-Tao, Shi, Su-Fei
Strongly enhanced electron-electron interaction in semiconducting moir\'e superlattices formed by transition metal dichalcogenides (TMDCs) heterobilayers has led to a plethora of intriguing fermionic correlated states. Meanwhile, interlayer excitons
Externí odkaz:
http://arxiv.org/abs/2308.10799
Autor:
Lian, Zhen, Chen, Dongxue, Ma, Lei, Meng, Yuze, Su, Ying, Yan, Li, Huang, Xiong, Wu, Qiran, Chen, Xinyue, Blei, Mark, Taniguchi, Takashi, Watanabe, Kenji, Tongay, Sefaattin, Zhang, Chuanwei, Cui, Yong-Tao, Shi, Su-Fei
Publikováno v:
Nature Communications volume 14, Article number: 4604 (2023)
Transition metal dichalcogenide (TMDC) moir\'e superlattices, owing to the moir\'e flatbands and strong correlation, can host periodic electron crystals and fascinating correlated physics. The TMDC heterojunctions in the type-II alignment also enable
Externí odkaz:
http://arxiv.org/abs/2308.03219
Vision-language models (VLMs) are impactful in part because they can be applied to a variety of visual understanding tasks in a zero-shot fashion, without any fine-tuning. We study $\textit{generative VLMs}$ that are trained for next-word generation
Externí odkaz:
http://arxiv.org/abs/2306.01879