Zobrazeno 1 - 10
of 21 675
pro vyhledávání: '"Chen,Lu"'
The rise of "bedroom producers" has democratized music creation, while challenging producers to objectively evaluate their work. To address this, we present AI TrackMate, an LLM-based music chatbot designed to provide constructive feedback on music p
Externí odkaz:
http://arxiv.org/abs/2412.06617
Autor:
Xu, Hongshen, Zhu, Su, Wang, Zihan, Zheng, Hang, Ma, Da, Cao, Ruisheng, Fan, Shuai, Chen, Lu, Yu, Kai
Large Language Models (LLMs) have extended their capabilities beyond language generation to interact with external systems through tool calling, offering powerful potential for real-world applications. However, the phenomenon of tool hallucinations,
Externí odkaz:
http://arxiv.org/abs/2412.04141
Autor:
Ma, Da, Chen, Lu, Zhang, Situo, Miao, Yuxun, Zhu, Su, Chen, Zhi, Xu, Hongshen, Li, Hanqi, Fan, Shuai, Pan, Lei, Yu, Kai
The increasing context window size in Large Language Models (LLMs), such as the GPT and LLaMA series, has improved their ability to tackle complex, long-text tasks, but at the cost of inference efficiency, particularly regarding memory and computatio
Externí odkaz:
http://arxiv.org/abs/2412.02252
The increasing complexity and cost of clinical trials, particularly in the context of oncology and advanced therapies, pose significant challenges for drug development. This study evaluates the predictive capabilities of large language models (LLMs)
Externí odkaz:
http://arxiv.org/abs/2411.17595
Autor:
Gong, Zheng, Deng, Zhuo, Gan, Run, Niu, Zhiyuan, Chen, Lu, Huang, Canfeng, Liang, Jia, Gao, Weihao, Li, Fang, Zhang, Shaochong, Ma, Lan
The retinal fundus images are utilized extensively in the diagnosis, and their quality can directly affect the diagnosis results. However, due to the insufficient dataset and algorithm application, current fundus image quality assessment (FIQA) metho
Externí odkaz:
http://arxiv.org/abs/2411.12273
Autor:
Zhu, Zichen, Tang, Hao, Li, Yansi, Lan, Kunyao, Jiang, Yixuan, Zhou, Hao, Wang, Yixiao, Zhang, Situo, Sun, Liangtai, Chen, Lu, Yu, Kai
Current mobile assistants are limited by dependence on system APIs or struggle with complex user instructions and diverse interfaces due to restricted comprehension and decision-making abilities. To address these challenges, we propose MobA, a novel
Externí odkaz:
http://arxiv.org/abs/2410.13757
Large language models (LLMs) have demonstrated remarkable performance, particularly in multilingual contexts. While recent studies suggest that LLMs can transfer skills learned in one language to others, the internal mechanisms behind this ability re
Externí odkaz:
http://arxiv.org/abs/2410.11718
Accurate and affordable indoor 3D reconstruction is critical for effective robot navigation and interaction. Traditional LiDAR-based mapping provides high precision but is costly, heavy, and power-intensive, with limited ability for novel view render
Externí odkaz:
http://arxiv.org/abs/2410.06613
Similarity search finds objects that are similar to a given query object based on a similarity metric. As the amount and variety of data continue to grow, similarity search in metric spaces has gained significant attention. Metric spaces can accommod
Externí odkaz:
http://arxiv.org/abs/2410.05091
This paper presents a method to evaluate the alignment between the decision-making logic of Large Language Models (LLMs) and human cognition in a case study on legal LLMs. Unlike traditional evaluations on language generation results, we propose to e
Externí odkaz:
http://arxiv.org/abs/2410.09083