Zobrazeno 1 - 10
of 386
pro vyhledávání: '"Tang Xianfeng"'
Autor:
Xu, Ran, Liu, Hui, Nag, Sreyashi, Dai, Zhenwei, Xie, Yaochen, Tang, Xianfeng, Luo, Chen, Li, Yang, Ho, Joyce C., Yang, Carl, He, Qi
Retrieval-augmented generation (RAG) enhances the question-answering (QA) abilities of large language models (LLMs) by integrating external knowledge. However, adapting general-purpose RAG systems to specialized fields such as science and medicine po
Externí odkaz:
http://arxiv.org/abs/2410.17952
Few-shot Chain-of-Thought (CoT) prompting has demonstrated strong performance in improving the reasoning capabilities of large language models (LLMs). While theoretical investigations have been conducted to understand CoT, the underlying transformer
Externí odkaz:
http://arxiv.org/abs/2410.16540
Autor:
Zhang, Zhiwei, Wang, Fali, Li, Xiaomin, Wu, Zongyu, Tang, Xianfeng, Liu, Hui, He, Qi, Yin, Wenpeng, Wang, Suhang
Large language models (LLMs) have shown remarkable proficiency in generating text, benefiting from extensive training on vast textual corpora. However, LLMs may also acquire unwanted behaviors from the diverse and sensitive nature of their training d
Externí odkaz:
http://arxiv.org/abs/2410.16454
Recent studies show that LLMs, particularly open-source models, struggle to follow complex instructions with multiple constraints. Despite the importance, methods to improve LLMs' adherence to such constraints remain unexplored, and current research
Externí odkaz:
http://arxiv.org/abs/2410.12207
Autor:
Liu, Han, Tang, Xianfeng, Chen, Tianlang, Liu, Jiapeng, Indu, Indu, Zou, Henry Peng, Dai, Peng, Galan, Roberto Fernandez, Porter, Michael D, Jia, Dongmei, Zhang, Ning, Xiong, Lian
The fashion industry is one of the leading domains in the global e-commerce sector, prompting major online retailers to employ recommendation systems for product suggestions and customer convenience. While recommendation systems have been widely stud
Externí odkaz:
http://arxiv.org/abs/2410.11327
Autor:
Luo, Chen, Tang, Xianfeng, Lu, Hanqing, Xie, Yaochen, Liu, Hui, Dai, Zhenwei, Cui, Limeng, Joshi, Ashutosh, Nag, Sreyashi, Li, Yang, Li, Zhen, Goutam, Rahul, Tang, Jiliang, Zhang, Haiyang, He, Qi
Online shopping platforms, such as Amazon, offer services to billions of people worldwide. Unlike web search or other search engines, product search engines have their unique characteristics, primarily featuring short queries which are mostly a combi
Externí odkaz:
http://arxiv.org/abs/2408.02215
Autor:
Han, Haoyu, Li, Juanhui, Huang, Wei, Tang, Xianfeng, Lu, Hanqing, Luo, Chen, Liu, Hui, Tang, Jiliang
Graph Neural Networks (GNNs) have proven to be highly effective for node classification tasks across diverse graph structural patterns. Traditionally, GNNs employ a uniform global filter, typically a low-pass filter for homophilic graphs and a high-p
Externí odkaz:
http://arxiv.org/abs/2406.03464
Autor:
Liu, Fenglin, Li, Zheng, Zhou, Hongjian, Yin, Qingyu, Yang, Jingfeng, Tang, Xianfeng, Luo, Chen, Zeng, Ming, Jiang, Haoming, Gao, Yifan, Nigam, Priyanka, Nag, Sreyashi, Yin, Bing, Hua, Yining, Zhou, Xuan, Rohanian, Omid, Thakur, Anshul, Clifton, Lei, Clifton, David A.
The adoption of large language models (LLMs) to assist clinicians has attracted remarkable attention. Existing works mainly adopt the close-ended question-answering (QA) task with answer options for evaluation. However, many clinical decisions involv
Externí odkaz:
http://arxiv.org/abs/2405.00716
Autor:
Jin, Bowen, Xie, Chulin, Zhang, Jiawei, Roy, Kashob Kumar, Zhang, Yu, Li, Zheng, Li, Ruirui, Tang, Xianfeng, Wang, Suhang, Meng, Yu, Han, Jiawei
Publikováno v:
ACL 2024
Large language models (LLMs), while exhibiting exceptional performance, suffer from hallucinations, especially on knowledge-intensive tasks. Existing works propose to augment LLMs with individual text units retrieved from external knowledge corpora t
Externí odkaz:
http://arxiv.org/abs/2404.07103
Autor:
Wei, Tianxin, Jin, Bowen, Li, Ruirui, Zeng, Hansi, Wang, Zhengyang, Sun, Jianhui, Yin, Qingyu, Lu, Hanqing, Wang, Suhang, He, Jingrui, Tang, Xianfeng
Developing a universal model that can effectively harness heterogeneous resources and respond to a wide range of personalized needs has been a longstanding community aspiration. Our daily choices, especially in domains like fashion and retail, are su
Externí odkaz:
http://arxiv.org/abs/2403.10667