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of 3 733
pro vyhledávání: '"wang, yuqi"'
End-to-end autonomous driving has garnered widespread attention. Current end-to-end approaches largely rely on the supervision from perception tasks such as detection, tracking, and map segmentation to aid in learning scene representations. However,
Externí odkaz:
http://arxiv.org/abs/2406.08481
Autor:
Liu, Che, Wan, Zhongwei, Wang, Yuqi, Shen, Hui, Wang, Haozhe, Zheng, Kangyu, Zhang, Mi, Arcucci, Rossella
Automatic radiology report generation can significantly benefit the labor-intensive process of report writing by radiologists, especially for 3D radiographs like CT scans, which are crucial for broad clinical diagnostics yet underexplored compared to
Externí odkaz:
http://arxiv.org/abs/2406.07146
One of the key materials in solid-state lithium batteries is fast ion conductors. However, the Li+ ion transport in inorganic crystals involves complex factors, making it a mystery to find and design ion conductors with low migration barriers. In thi
Externí odkaz:
http://arxiv.org/abs/2406.02852
Autor:
Zhu, Zheng, Wang, Xiaofeng, Zhao, Wangbo, Min, Chen, Deng, Nianchen, Dou, Min, Wang, Yuqi, Shi, Botian, Wang, Kai, Zhang, Chi, You, Yang, Zhang, Zhaoxiang, Zhao, Dawei, Xiao, Liang, Zhao, Jian, Lu, Jiwen, Huang, Guan
General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual environments to decision-making systems. Recently, the emergence of the
Externí odkaz:
http://arxiv.org/abs/2405.03520
Autor:
Padlewski, Piotr, Bain, Max, Henderson, Matthew, Zhu, Zhongkai, Relan, Nishant, Pham, Hai, Ong, Donovan, Aleksiev, Kaloyan, Ormazabal, Aitor, Phua, Samuel, Yeo, Ethan, Lamprecht, Eugenie, Liu, Qi, Wang, Yuqi, Chen, Eric, Fu, Deyu, Li, Lei, Zheng, Che, d'Autume, Cyprien de Masson, Yogatama, Dani, Artetxe, Mikel, Tay, Yi
We introduce Vibe-Eval: a new open benchmark and framework for evaluating multimodal chat models. Vibe-Eval consists of 269 visual understanding prompts, including 100 of hard difficulty, complete with gold-standard responses authored by experts. Vib
Externí odkaz:
http://arxiv.org/abs/2405.02287
Autor:
Reka Team, Ormazabal, Aitor, Zheng, Che, d'Autume, Cyprien de Masson, Yogatama, Dani, Fu, Deyu, Ong, Donovan, Chen, Eric, Lamprecht, Eugenie, Pham, Hai, Ong, Isaac, Aleksiev, Kaloyan, Li, Lei, Henderson, Matthew, Bain, Max, Artetxe, Mikel, Relan, Nishant, Padlewski, Piotr, Liu, Qi, Chen, Ren, Phua, Samuel, Yang, Yazheng, Tay, Yi, Wang, Yuqi, Zhu, Zhongkai, Xie, Zhihui
We introduce Reka Core, Flash, and Edge, a series of powerful multimodal language models trained from scratch by Reka. Reka models are able to process and reason with text, images, video, and audio inputs. This technical report discusses details of t
Externí odkaz:
http://arxiv.org/abs/2404.12387
Large language models (LLMs), such as GPT3.5, GPT4 and LLAMA2 perform surprisingly well and outperform human experts on many tasks. However, in many domain-specific evaluations, these LLMs often suffer from hallucination problems due to insufficient
Externí odkaz:
http://arxiv.org/abs/2404.10384
Safe and reliable natural language inference is critical for extracting insights from clinical trial reports but poses challenges due to biases in large pre-trained language models. This paper presents a novel data augmentation technique to improve m
Externí odkaz:
http://arxiv.org/abs/2404.09206
In the domain of data science, the predictive tasks of classification, regression, and imputation of missing values are commonly encountered challenges associated with tabular data. This research endeavors to apply Large Language Models (LLMs) toward
Externí odkaz:
http://arxiv.org/abs/2403.20208
Large vision-language models (LVLMs) excel across diverse tasks involving concrete images from natural scenes. However, their ability to interpret abstract figures, such as geometry shapes and scientific plots, remains limited due to a scarcity of tr
Externí odkaz:
http://arxiv.org/abs/2403.00231