Zobrazeno 1 - 10
of 5 776
pro vyhledávání: '"Zhang, WenJie"'
Exploring the predictive capabilities of language models in material science is an ongoing interest. This study investigates the application of language model embeddings to enhance material property prediction in materials science. By evaluating vari
Externí odkaz:
http://arxiv.org/abs/2410.16165
Large Language Models (LLMs) have achieved impressive results in various tasks but struggle with hallucination problems and lack of relevant knowledge, especially in deep complex reasoning and knowledge-intensive tasks. Knowledge Graphs (KGs), which
Externí odkaz:
http://arxiv.org/abs/2410.14211
Graph representation learning, involving both node features and graph structures, is crucial for real-world applications but often encounters pervasive noise. State-of-the-art methods typically address noise by focusing separately on node features wi
Externí odkaz:
http://arxiv.org/abs/2410.12096
Autor:
Sun, Luming, Jiang, Ning, Dou, Liming, Shu, Xinwen, Zhu, Jiazheng, Dong, Subo, Buckley, David, Cenko, S. Bradley, Fan, Xiaohui, Gromadzki, Mariusz, Liu, Zhu, Wang, Jianguo, Wang, Tinggui, Wang, Yibo, Wu, Tao, Yang, Lei, Zhang, Fabao, Zhang, Wenjie, Zhang, Xiaer
We report the discovery of a second optical flare that occurred in September 2021 in IRAS F01004-2237, where the first flare occurred in 2010 has been reported, and present a detailed analysis of multi-band data. The position of the flare coincides w
Externí odkaz:
http://arxiv.org/abs/2410.09720
With growing demands for data privacy and model robustness, graph unlearning (GU), which erases the influence of specific data on trained GNN models, has gained significant attention. However, existing exact unlearning methods suffer from either low
Externí odkaz:
http://arxiv.org/abs/2410.06480
Top-k Nearest Neighbors (kNN) problem on road network has numerous applications on location-based services. As direct search using the Dijkstra's algorithm results in a large search space, a plethora of complex-index-based approaches have been propos
Externí odkaz:
http://arxiv.org/abs/2408.05432
Graph Neural Networks (GNNs) are vital in data science but are increasingly susceptible to adversarial attacks. To help researchers develop more robust GNN models, it's essential to focus on designing strong attack models as foundational benchmarks a
Externí odkaz:
http://arxiv.org/abs/2407.18170
Multi-objective optimization problems (MOPs) are ubiquitous in real-world applications, presenting a complex challenge of balancing multiple conflicting objectives. Traditional evolutionary algorithms (EAs), though effective, often rely on domain-spe
Externí odkaz:
http://arxiv.org/abs/2406.08987
Autor:
Chen, Ping, Zhang, Wenjie, He, Shuibing, Gu, Yingjie, Peng, Zhuwei, Huang, Kexin, Zhan, Xuan, Chen, Weijian, Zheng, Yi, Wang, Zhefeng, Yin, Yanlong, Chen, Gang
Large model training has been using recomputation to alleviate the memory pressure and pipelining to exploit the parallelism of data, tensor, and devices. The existing recomputation approaches may incur up to 40% overhead when training real-world mod
Externí odkaz:
http://arxiv.org/abs/2406.08756
Autor:
Anastassiou, Philip, Chen, Jiawei, Chen, Jitong, Chen, Yuanzhe, Chen, Zhuo, Chen, Ziyi, Cong, Jian, Deng, Lelai, Ding, Chuang, Gao, Lu, Gong, Mingqing, Huang, Peisong, Huang, Qingqing, Huang, Zhiying, Huo, Yuanyuan, Jia, Dongya, Li, Chumin, Li, Feiya, Li, Hui, Li, Jiaxin, Li, Xiaoyang, Li, Xingxing, Liu, Lin, Liu, Shouda, Liu, Sichao, Liu, Xudong, Liu, Yuchen, Liu, Zhengxi, Lu, Lu, Pan, Junjie, Wang, Xin, Wang, Yuping, Wang, Yuxuan, Wei, Zhen, Wu, Jian, Yao, Chao, Yang, Yifeng, Yi, Yuanhao, Zhang, Junteng, Zhang, Qidi, Zhang, Shuo, Zhang, Wenjie, Zhang, Yang, Zhao, Zilin, Zhong, Dejian, Zhuang, Xiaobin
We introduce Seed-TTS, a family of large-scale autoregressive text-to-speech (TTS) models capable of generating speech that is virtually indistinguishable from human speech. Seed-TTS serves as a foundation model for speech generation and excels in sp
Externí odkaz:
http://arxiv.org/abs/2406.02430