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pro vyhledávání: '"hu, Helan"'
Rethinking Semantic Parsing for Large Language Models: Enhancing LLM Performance with Semantic Hints
Semantic Parsing aims to capture the meaning of a sentence and convert it into a logical, structured form. Previous studies show that semantic parsing enhances the performance of smaller models (e.g., BERT) on downstream tasks. However, it remains un
Externí odkaz:
http://arxiv.org/abs/2409.14469
Autor:
Gao, Bofei, Song, Feifan, Miao, Yibo, Cai, Zefan, Yang, Zhe, Chen, Liang, Hu, Helan, Xu, Runxin, Dong, Qingxiu, Zheng, Ce, Xiao, Wen, Zhang, Ge, Zan, Daoguang, Lu, Keming, Yu, Bowen, Liu, Dayiheng, Cui, Zeyu, Yang, Jian, Sha, Lei, Wang, Houfeng, Sui, Zhifang, Wang, Peiyi, Liu, Tianyu, Chang, Baobao
Large Language Models (LLMs) exhibit remarkably powerful capabilities. One of the crucial factors to achieve success is aligning the LLM's output with human preferences. This alignment process often requires only a small amount of data to efficiently
Externí odkaz:
http://arxiv.org/abs/2409.02795
The rapid advancement of large language models has given rise to a plethora of applications across a myriad of real-world tasks, mainly centered on aligning with human intent. However, the complexities inherent in human intent necessitate a dependenc
Externí odkaz:
http://arxiv.org/abs/2405.12163
Autor:
Tang, Xiangru, Liu, Yuliang, Cai, Zefan, Shao, Yanjun, Lu, Junjie, Zhang, Yichi, Deng, Zexuan, Hu, Helan, An, Kaikai, Huang, Ruijun, Si, Shuzheng, Chen, Sheng, Zhao, Haozhe, Chen, Liang, Wang, Yan, Liu, Tianyu, Jiang, Zhiwei, Chang, Baobao, Fang, Yin, Qin, Yujia, Zhou, Wangchunshu, Zhao, Yilun, Cohan, Arman, Gerstein, Mark
Despite Large Language Models (LLMs) like GPT-4 achieving impressive results in function-level code generation, they struggle with repository-scale code understanding (e.g., coming up with the right arguments for calling routines), requiring a deeper
Externí odkaz:
http://arxiv.org/abs/2311.09835
Distantly-Supervised Named Entity Recognition (DS-NER) is widely used in real-world scenarios. It can effectively alleviate the burden of annotation by matching entities in existing knowledge bases with snippets in the text but suffer from the label
Externí odkaz:
http://arxiv.org/abs/2311.08010