Zobrazeno 1 - 10
of 184
pro vyhledávání: '"Zhang, Beichen"'
Active learning (AL) is designed to construct a high-quality labeled dataset by iteratively selecting the most informative samples. Such sampling heavily relies on data representation, while recently pre-training is popular for robust feature learnin
Externí odkaz:
http://arxiv.org/abs/2407.14720
Autor:
Zhu, Yutao, Zhou, Kun, Mao, Kelong, Chen, Wentong, Sun, Yiding, Chen, Zhipeng, Cao, Qian, Wu, Yihan, Chen, Yushuo, Wang, Feng, Zhang, Lei, Li, Junyi, Wang, Xiaolei, Wang, Lei, Zhang, Beichen, Dong, Zican, Cheng, Xiaoxue, Chen, Yuhan, Tang, Xinyu, Hou, Yupeng, Ren, Qiangqiang, Pang, Xincheng, Xie, Shufang, Zhao, Wayne Xin, Dou, Zhicheng, Mao, Jiaxin, Lin, Yankai, Song, Ruihua, Xu, Jun, Chen, Xu, Yan, Rui, Wei, Zhewei, Hu, Di, Huang, Wenbing, Gao, Ze-Feng, Chen, Yueguo, Lu, Weizheng, Wen, Ji-Rong
Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many open-source LLMs have been released with technical reports, the lack of
Externí odkaz:
http://arxiv.org/abs/2406.19853
In this study, we discuss how reinforcement learning (RL) provides an effective and efficient framework for solving sociohydrology problems. The efficacy of RL for these types of problems is evident because of its ability to update policies in an ite
Externí odkaz:
http://arxiv.org/abs/2405.20772
Autor:
Zhou, Kun, Zhang, Beichen, Wang, Jiapeng, Chen, Zhipeng, Zhao, Wayne Xin, Sha, Jing, Sheng, Zhichao, Wang, Shijin, Wen, Ji-Rong
Mathematical reasoning is an important capability of large language models~(LLMs) for real-world applications. To enhance this capability, existing work either collects large-scale math-related texts for pre-training, or relies on stronger LLMs (\eg
Externí odkaz:
http://arxiv.org/abs/2405.14365
Contrastive Language-Image Pre-training (CLIP) has been the cornerstone for zero-shot classification, text-image retrieval, and text-image generation by aligning image and text modalities. Despite its widespread adoption, a significant limitation of
Externí odkaz:
http://arxiv.org/abs/2403.15378
Supernet is a core component in many recent Neural Architecture Search (NAS) methods. It not only helps embody the search space but also provides a (relative) estimation of the final performance of candidate architectures. Thus, it is critical that t
Externí odkaz:
http://arxiv.org/abs/2403.11380
Autor:
Zhao, Wayne Xin, Zhou, Kun, Zhang, Beichen, Gong, Zheng, Chen, Zhipeng, Zhou, Yuanhang, Wen, Ji-Rong, Sha, Jing, Wang, Shijin, Liu, Cong, Hu, Guoping
Although pre-trained language models~(PLMs) have recently advanced the research progress in mathematical reasoning, they are not specially designed as a capable multi-task solver, suffering from high cost for multi-task deployment (\eg a model copy f
Externí odkaz:
http://arxiv.org/abs/2306.11027
Autor:
Zhang, Beichen, Zhou, Kun, Wei, Xilin, Zhao, Wayne Xin, Sha, Jing, Wang, Shijin, Wen, Ji-Rong
Chain-of-thought prompting~(CoT) and tool augmentation have been validated in recent work as effective practices for improving large language models~(LLMs) to perform step-by-step reasoning on complex math-related tasks. However, most existing math r
Externí odkaz:
http://arxiv.org/abs/2306.02408
Although large language models (LLMs) have achieved excellent performance in a variety of evaluation benchmarks, they still struggle in complex reasoning tasks which require specific knowledge and multi-hop reasoning. To improve the reasoning abiliti
Externí odkaz:
http://arxiv.org/abs/2305.14323
Autor:
Zhao, Wayne Xin, Zhou, Kun, Li, Junyi, Tang, Tianyi, Wang, Xiaolei, Hou, Yupeng, Min, Yingqian, Zhang, Beichen, Zhang, Junjie, Dong, Zican, Du, Yifan, Yang, Chen, Chen, Yushuo, Chen, Zhipeng, Jiang, Jinhao, Ren, Ruiyang, Li, Yifan, Tang, Xinyu, Liu, Zikang, Liu, Peiyu, Nie, Jian-Yun, Wen, Ji-Rong
Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach, language modelin
Externí odkaz:
http://arxiv.org/abs/2303.18223