1 code implementation • 28 Feb 2024 • Sirui Hong, Yizhang Lin, Bang Liu, Bangbang Liu, Binhao Wu, Danyang Li, Jiaqi Chen, Jiayi Zhang, Jinlin Wang, Li Zhang, Lingyao Zhang, Min Yang, Mingchen Zhuge, Taicheng Guo, Tuo Zhou, Wei Tao, Wenyi Wang, Xiangru Tang, Xiangtao Lu, Xiawu Zheng, Xinbing Liang, Yaying Fei, Yuheng Cheng, Zongze Xu, Chenglin Wu
Large Language Model (LLM)-based agents have demonstrated remarkable effectiveness.
no code implementations • 22 Feb 2024 • Xiuying Chen, Tairan Wang, Qingqing Zhu, Taicheng Guo, Shen Gao, Zhiyong Lu, Xin Gao, Xiangliang Zhang
Our findings confirm that FM offers a more logical approach to evaluating scientific summaries.
no code implementations • 20 Feb 2024 • Yujun Zhou, Yufei Han, Haomin Zhuang, Taicheng Guo, Kehan Guo, Zhenwen Liang, Hongyan Bao, Xiangliang Zhang
Large Language Models (LLMs) demonstrate remarkable capabilities across diverse applications.
no code implementations • 6 Feb 2024 • Zhenwen Liang, Kehan Guo, Gang Liu, Taicheng Guo, Yujun Zhou, Tianyu Yang, Jiajun Jiao, Renjie Pi, Jipeng Zhang, Xiangliang Zhang
The paper introduces SceMQA, a novel benchmark for scientific multimodal question answering at the college entrance level.
1 code implementation • 21 Jan 2024 • Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
To provide the community with an overview of this dynamic field, we present this survey to offer an in-depth discussion on the essential aspects of multi-agent systems based on LLMs, as well as the challenges.
no code implementations • 7 Oct 2023 • Taicheng Guo, Changsheng Ma, Xiuying Chen, Bozhao Nan, Kehan Guo, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
With the widespread adoption of generative models, the Variational Autoencoder(VAE) framework has typically been employed to tackle challenges in reaction prediction, where the reactants are encoded as a condition for the decoder, which then generates the product.
1 code implementation • NeurIPS 2023 • Taicheng Guo, Kehan Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
In this paper, rather than pursuing state-of-the-art performance, we aim to evaluate capabilities of LLMs in a wide range of tasks across the chemistry domain.
1 code implementation • 28 Jul 2022 • Taicheng Guo, Lu Yu, Basem Shihada, Xiangliang Zhang
Second, the user preference over these topics is transferable across different platforms.