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pro vyhledávání: '"Wang,Liang"'
With the advancement of large language models (LLMs), researchers have explored various methods to optimally leverage their comprehension and generation capabilities in sequential recommendation scenarios. However, several challenges persist in this
Externí odkaz:
http://arxiv.org/abs/2411.14922
Autor:
Yang, Sen, Jiang, Minyue, Fan, Ziwei, Xie, Xiaolu, Tan, Xiao, Li, Yingying, Ding, Errui, Wang, Liang, Wang, Jingdong
Recent advances in autonomous driving systems have shifted towards reducing reliance on high-definition maps (HDMaps) due to the huge costs of annotation and maintenance. Instead, researchers are focusing on online vectorized HDMap construction using
Externí odkaz:
http://arxiv.org/abs/2411.14751
By cross-matching the eclipsing binary catalog from TESS with that from LAMOST MRS, semi-detached eclipsing binaries with radial velocities coverage spanning more than 0.3 phases were authenticated. The absolute parameters for these systems were dete
Externí odkaz:
http://arxiv.org/abs/2411.05387
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 11, pp. 5695-5708, Nov. 2024
Next point-of-interest (POI) recommendation aims to predict a user's next destination based on sequential check-in history and a set of POI candidates. Graph neural networks (GNNs) have demonstrated a remarkable capability in this endeavor by exploit
Externí odkaz:
http://arxiv.org/abs/2411.01169
Molecular property prediction (MPP) is integral to drug discovery and material science, but often faces the challenge of data scarcity in real-world scenarios. Addressing this, few-shot molecular property prediction (FSMPP) has been developed. Unlike
Externí odkaz:
http://arxiv.org/abs/2411.01158
In this paper, we create "Love in Action" (LIA), a body language-based social game utilizing video cameras installed in public spaces to enhance social relationships in real-world. In the game, participants assume dual roles, i.e., requesters, who is
Externí odkaz:
http://arxiv.org/abs/2411.10449
Dual-target therapeutic strategies have become a compelling approach and attracted significant attention due to various benefits, such as their potential in overcoming drug resistance in cancer therapy. Considering the tremendous success that deep ge
Externí odkaz:
http://arxiv.org/abs/2410.20688
Synthetic data generation has become an increasingly popular way of training models without the need for large, manually labeled datasets. For tasks like text embedding, synthetic data offers diverse and scalable training examples, significantly redu
Externí odkaz:
http://arxiv.org/abs/2410.18634
Autor:
Huang, Han, Huo, Yuqi, Zhao, Zijia, Lu, Haoyu, Wu, Shu, Wang, Bingning, Liu, Qiang, Chen, Weipeng, Wang, Liang
Multimodal large language models (MLLMs) have made significant strides by integrating visual and textual modalities. A critical factor in training MLLMs is the quality of image-text pairs within multimodal pretraining datasets. However, $\textit {de
Externí odkaz:
http://arxiv.org/abs/2410.16166
Autor:
Sedlak, Boris, Morichetta, Andrea, Wang, Yuhao, Fei, Yang, Wang, Liang, Dustdar, Schahram, Qu, Xiaobo
In the context of autonomous vehicles (AVs), offloading is essential for guaranteeing the execution of perception tasks, e.g., mobile mapping or object detection. While existing work focused extensively on minimizing inter-vehicle networking latency
Externí odkaz:
http://arxiv.org/abs/2409.17667