Zobrazeno 1 - 10
of 2 515
pro vyhledávání: '"NGUYEN, THIEN"'
Continuous-time trajectory representation has gained significant popularity in recent years, as it offers an elegant formulation that allows the fusion of a larger number of sensors and sensing modalities, overcoming limitations of traditional discre
Externí odkaz:
http://arxiv.org/abs/2410.22931
Autor:
Van Nguyen, Chien, Shen, Xuan, Aponte, Ryan, Xia, Yu, Basu, Samyadeep, Hu, Zhengmian, Chen, Jian, Parmar, Mihir, Kunapuli, Sasidhar, Barrow, Joe, Wu, Junda, Singh, Ashish, Wang, Yu, Gu, Jiuxiang, Dernoncourt, Franck, Ahmed, Nesreen K., Lipka, Nedim, Zhang, Ruiyi, Chen, Xiang, Yu, Tong, Kim, Sungchul, Deilamsalehy, Hanieh, Park, Namyong, Rimer, Mike, Zhang, Zhehao, Yang, Huanrui, Rossi, Ryan A., Nguyen, Thien Huu
Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, making them ideal for various settings including on-device, mobile, edge d
Externí odkaz:
http://arxiv.org/abs/2410.20011
Autor:
Van Nguyen, Chien, Nguyen, Huy Huu, Pham, Thang M., Zhang, Ruiyi, Deilamsalehy, Hanieh, Mathur, Puneet, Rossi, Ryan A., Bui, Trung, Lai, Viet Dac, Dernoncourt, Franck, Nguyen, Thien Huu
Efficient long-context language modeling remains a significant challenge in Natural Language Processing (NLP). While Transformers dominate language tasks, they struggle with long sequences due to quadratic computational complexity in training and lin
Externí odkaz:
http://arxiv.org/abs/2410.18572
Autor:
Jin, Tongxing, Nguyen, Thien-Minh, Xu, Xinhang, Yang, Yizhuo, Yuan, Shenghai, Li, Jianping, Xie, Lihua
Loop closure is an important task in robot navigation. However, existing methods mostly rely on some implicit or heuristic features of the environment, which can still fail to work in common environments such as corridors, tunnels, and warehouses. In
Externí odkaz:
http://arxiv.org/abs/2410.15869
Large-scale LiDAR Bundle Adjustment (LBA) for refining sensor orientation and point cloud accuracy simultaneously is a fundamental task in photogrammetry and robotics, particularly as low-cost 3D sensors are increasingly used for 3D mapping in comple
Externí odkaz:
http://arxiv.org/abs/2410.14565
Autor:
Chen, Meng, Arthur, Philip, Feng, Qianyu, Hoang, Cong Duy Vu, Hong, Yu-Heng, Moghaddam, Mahdi Kazemi, Nezami, Omid, Nguyen, Thien, Tangari, Gioacchino, Vu, Duy, Vu, Thanh, Johnson, Mark, Kenthapadi, Krishnaram, Dharmasiri, Don, Duong, Long, Li, Yuan-Fang
Large language models (LLMs) have shown impressive performance in \emph{code} understanding and generation, making coding tasks a key focus for researchers due to their practical applications and value as a testbed for LLM evaluation. Data synthesis
Externí odkaz:
http://arxiv.org/abs/2411.00005
Currently, it is challenging to investigate aneurismal hemodynamics based on current in-vivo data such as Magnetic Resonance Imaging or Computed Tomography due to the limitations in both spatial and temporal resolutions. In this work, we investigate
Externí odkaz:
http://arxiv.org/abs/2410.12027
Continual Event Detection (CED) poses a formidable challenge due to the catastrophic forgetting phenomenon, where learning new tasks (with new coming event types) hampers performance on previous ones. In this paper, we introduce a novel approach, Lif
Externí odkaz:
http://arxiv.org/abs/2410.08905
Autor:
Tran, Quyen, Le, Minh, Truong, Tuan, Phung, Dinh, Ngo, Linh, Nguyen, Thien, Ho, Nhat, Le, Trung
Drawing inspiration from human learning behaviors, this work proposes a novel approach to mitigate catastrophic forgetting in Prompt-based Continual Learning models by exploiting the relationships between continuously emerging class data. We find tha
Externí odkaz:
http://arxiv.org/abs/2410.04327
Autor:
Tran, Quyen, Thanh, Nguyen Xuan, Anh, Nguyen Hoang, Hai, Nam Le, Le, Trung, Van Ngo, Linh, Nguyen, Thien Huu
Few-shot Continual Relations Extraction (FCRE) is an emerging and dynamic area of study where models can sequentially integrate knowledge from new relations with limited labeled data while circumventing catastrophic forgetting and preserving prior kn
Externí odkaz:
http://arxiv.org/abs/2410.00334