Zobrazeno 1 - 10
of 9 992
pro vyhledávání: '"Yew, P"'
Large multimodal models have demonstrated impressive problem-solving abilities in vision and language tasks, and have the potential to encode extensive world knowledge. However, it remains an open challenge for these models to perceive, reason, plan,
Externí odkaz:
http://arxiv.org/abs/2409.14277
This paper explores the transformative potential of quantum computing in the realm of personalized learning. Traditional machine learning models and GPU-based approaches have long been utilized to tailor educational experiences to individual student
Externí odkaz:
http://arxiv.org/abs/2408.15287
Autor:
Khan, Muhammad Tayyab, Feng, Wenhe, Chen, Lequn, Ng, Ye Han, Tan, Nicholas Yew Jin, Moon, Seung Ki
The integration of Computer-Aided Design (CAD), Computer-Aided Process Planning (CAPP), and Computer-Aided Manufacturing (CAM) plays a crucial role in modern manufacturing, facilitating seamless transitions from digital designs to physical products.
Externí odkaz:
http://arxiv.org/abs/2408.06891
SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models for Southeast Asian Languages
Autor:
Zhang, Wenxuan, Chan, Hou Pong, Zhao, Yiran, Aljunied, Mahani, Wang, Jianyu, Liu, Chaoqun, Deng, Yue, Hu, Zhiqiang, Xu, Weiwen, Chia, Yew Ken, Li, Xin, Bing, Lidong
Large Language Models (LLMs) have shown remarkable abilities across various tasks, yet their development has predominantly centered on high-resource languages like English and Chinese, leaving low-resource languages underserved. To address this dispa
Externí odkaz:
http://arxiv.org/abs/2407.19672
Autor:
Wong, Albert, Cheng, Florence Wing Yau, Keung, Ashley, Hercules, Yamileth, Garcia, Mary Alexandra, Lim, Yew-Wei, Pham, Lien
Topic modelling has become increasingly popular for summarizing text data, such as social media posts and articles. However, topic modelling is usually completed in one shot. Assessing the quality of resulting topics is challenging. No effective meth
Externí odkaz:
http://arxiv.org/abs/2407.17892
In this paper, we present Reed-Solomon coded single-stranded representation learning (RSRL), a novel end-to-end model for learning representations for multi-modal lossless DNA storage. In contrast to existing learning-based methods, the proposed RSRL
Externí odkaz:
http://arxiv.org/abs/2408.00779
Autor:
Jiang, Huiqiang, Li, Yucheng, Zhang, Chengruidong, Wu, Qianhui, Luo, Xufang, Ahn, Surin, Han, Zhenhua, Abdi, Amir H., Li, Dongsheng, Lin, Chin-Yew, Yang, Yuqing, Qiu, Lili
The computational challenges of Large Language Model (LLM) inference remain a significant barrier to their widespread deployment, especially as prompt lengths continue to increase. Due to the quadratic complexity of the attention computation, it take
Externí odkaz:
http://arxiv.org/abs/2407.02490
The rapid research and development of generative artificial intelligence has enabled the generation of high-quality images, text, and 3D models from text prompts. This advancement impels an inquiry into whether these models can be leveraged to create
Externí odkaz:
http://arxiv.org/abs/2406.14917
Autor:
Marino, Bill, Chaudhary, Yaqub, Pi, Yulu, Yew, Rui-Jie, Aleksandrov, Preslav, Rahman, Carwyn, Shen, William F., Robinson, Isaac, Lane, Nicholas D.
As the AI supply chain grows more complex, AI systems and models are increasingly likely to incorporate multiple internally- or externally-sourced components such as datasets and (pre-trained) models. In such cases, determining whether or not the agg
Externí odkaz:
http://arxiv.org/abs/2406.14758
Publikováno v:
IEEE Congress on Evolutionary Computation (CEC), 2024, 1-8
Engineering design optimization requires an efficient combination of a 3D shape representation, an optimization algorithm, and a design performance evaluation method, which is often computationally expensive. We present a prompt evolution design opti
Externí odkaz:
http://arxiv.org/abs/2406.09143