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pro vyhledávání: '"Wang, Zengzhi"'
In this report, we pose the following question: Who is the most intelligent AI model to date, as measured by the OlympicArena (an Olympic-level, multi-discipline, multi-modal benchmark for superintelligent AI)? We specifically focus on the most recen
Externí odkaz:
http://arxiv.org/abs/2406.16772
Autor:
Huang, Zhen, Wang, Zengzhi, Xia, Shijie, Li, Xuefeng, Zou, Haoyang, Xu, Ruijie, Fan, Run-Ze, Ye, Lyumanshan, Chern, Ethan, Ye, Yixin, Zhang, Yikai, Yang, Yuqing, Wu, Ting, Wang, Binjie, Sun, Shichao, Xiao, Yang, Li, Yiyuan, Zhou, Fan, Chern, Steffi, Qin, Yiwei, Ma, Yan, Su, Jiadi, Liu, Yixiu, Zheng, Yuxiang, Zhang, Shaoting, Lin, Dahua, Qiao, Yu, Liu, Pengfei
The evolution of Artificial Intelligence (AI) has been significantly accelerated by advancements in Large Language Models (LLMs) and Large Multimodal Models (LMMs), gradually showcasing potential cognitive reasoning abilities in problem-solving and s
Externí odkaz:
http://arxiv.org/abs/2406.12753
Amid the expanding use of pre-training data, the phenomenon of benchmark dataset leakage has become increasingly prominent, exacerbated by opaque training processes and the often undisclosed inclusion of supervised data in contemporary Large Language
Externí odkaz:
http://arxiv.org/abs/2404.18824
High-quality, large-scale corpora are the cornerstone of building foundation models. In this work, we introduce \textsc{MathPile}, a diverse and high-quality math-centric corpus comprising about 9.5 billion tokens. Throughout its creation, we adhered
Externí odkaz:
http://arxiv.org/abs/2312.17120
We observe that current conversational language models often waver in their judgments when faced with follow-up questions, even if the original judgment was correct. This wavering presents a significant challenge for generating reliable responses and
Externí odkaz:
http://arxiv.org/abs/2310.02174
Autor:
Cai, Hongjie, Song, Nan, Wang, Zengzhi, Xie, Qiming, Zhao, Qiankun, Li, Ke, Wu, Siwei, Liu, Shijie, Yu, Jianfei, Xia, Rui
Aspect-based sentiment analysis is a long-standing research interest in the field of opinion mining, and in recent years, researchers have gradually shifted their focus from simple ABSA subtasks to end-to-end multi-element ABSA tasks. However, the da
Externí odkaz:
http://arxiv.org/abs/2306.16956
Recently, ChatGPT has drawn great attention from both the research community and the public. We are particularly interested in whether it can serve as a universal sentiment analyzer. To this end, in this work, we provide a preliminary evaluation of C
Externí odkaz:
http://arxiv.org/abs/2304.04339
Aspect-Based Sentiment Analysis (ABSA) aims to provide fine-grained aspect-level sentiment information. There are many ABSA tasks, and the current dominant paradigm is to train task-specific models for each task. However, application scenarios of ABS
Externí odkaz:
http://arxiv.org/abs/2211.10986
Publikováno v:
In Information Processing and Management July 2024 61(4)
Akademický článek
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