1 code implementation • 15 Oct 2024 • Juexiao Zhang, Gao Zhu, Sihang Li, Xinhao Liu, Haorui Song, Xinran Tang, Chen Feng
In this work, we propose to build Multiview Scene Graphs (MSG) from unposed images, representing a scene topologically with interconnected place and object nodes.
no code implementations • 4 Oct 2024 • Yanchen Luo, Junfeng Fang, Sihang Li, Zhiyuan Liu, Jiancan Wu, An Zhang, Wenjie Du, Xiang Wang
The de novo generation of molecules with targeted properties is crucial in biology, chemistry, and drug discovery.
1 code implementation • 28 Aug 2024 • Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, Hengxing Cai
To develop an LLM specialized in scientific literature understanding, we propose a hybrid strategy that integrates continual pre-training (CPT) and supervised fine-tuning (SFT), to simultaneously infuse scientific domain knowledge and enhance instruction-following capabilities for domain-specific tasks. cIn this process, we identify two key challenges: (1) constructing high-quality CPT corpora, and (2) generating diverse SFT instructions.
1 code implementation • 23 May 2024 • Zhiyuan Liu, Yaorui Shi, An Zhang, Sihang Li, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua
To resolve the challenges above, we propose a new pretraining method, ReactXT, for reaction-text modeling, and a new dataset, OpenExp, for experimental procedure prediction.
1 code implementation • 15 Mar 2024 • Hengxing Cai, Xiaochen Cai, Shuwen Yang, Jiankun Wang, Lin Yao, Zhifeng Gao, Junhan Chang, Sihang Li, Mingjun Xu, Changxin Wang, Hongshuai Wang, Yongge Li, Mujie Lin, Yaqi Li, Yuqi Yin, Linfeng Zhang, Guolin Ke
Scientific literature often includes a wide range of multimodal elements, such as tables, charts, and molecule, which are hard for text-focused LLMs to understand and analyze.
1 code implementation • 4 Mar 2024 • Hengxing Cai, Xiaochen Cai, Junhan Chang, Sihang Li, Lin Yao, Changxin Wang, Zhifeng Gao, Hongshuai Wang, Yongge Li, Mujie Lin, Shuwen Yang, Jiankun Wang, Mingjun Xu, Jin Huang, Xi Fang, Jiaxi Zhuang, Yuqi Yin, Yaqi Li, Changhong Chen, Zheng Cheng, Zifeng Zhao, Linfeng Zhang, Guolin Ke
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis.
1 code implementation • 6 Feb 2024 • Junfeng Fang, Shuai Zhang, Chang Wu, Zhengyi Yang, Zhiyuan Liu, Sihang Li, Kun Wang, Wenjie Du, Xiang Wang
Molecular Relational Learning (MRL), aiming to understand interactions between molecular pairs, plays a pivotal role in advancing biochemical research.
1 code implementation • 25 Jan 2024 • Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian
Through 3D molecule-text alignment and 3D molecule-centric instruction tuning, 3D-MoLM establishes an integration of 3D molecular encoder and LM.
1 code implementation • 5 Dec 2023 • Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang, Xiangnan He
Treating the "sequential behaviors of users" as a distinct modality beyond texts, we employ a projector to align the traditional recommender's ID embeddings with the LLM's input space.
1 code implementation • 24 Oct 2023 • YiRong Chen, Zhenyu Wang, Xiaofen Xing, huimin zheng, Zhipei Xu, Kai Fang, Junhong Wang, Sihang Li, Jieling Wu, Qi Liu, Xiangmin Xu
Large language models (LLMs) have performed well in providing general and extensive health suggestions in single-turn conversations, exemplified by systems such as ChatGPT, ChatGLM, ChatDoctor, DoctorGLM, and etc.
1 code implementation • 19 Oct 2023 • Zhiyuan Liu, Sihang Li, Yanchen Luo, Hao Fei, Yixin Cao, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua
MolCA enables an LM (e. g., Galactica) to understand both text- and graph-based molecular contents via the cross-modal projector.
Ranked #4 on Molecule Captioning on ChEBI-20
no code implementations • 7 Oct 2023 • Jingyi Pan, Sihang Li, Yucheng Chen, Jinjing Zhu, Lin Wang
Moreover, semantic segmentation models trained on daytime datasets often face difficulties in generalizing effectively to nighttime conditions.
no code implementations • 13 Jul 2023 • Sihang Li, Kuangzheng Li, Haibing Lu
Many companies and organizations have started to use some form of AIenabled auto mated tools to assist in their hiring process, e. g. screening resumes, interviewing candi dates, performance evaluation.
1 code implementation • 15 Jun 2023 • Yiming Li, Sihang Li, Xinhao Liu, Moonjun Gong, Kenan Li, Nuo Chen, Zijun Wang, Zhiheng Li, Tao Jiang, Fisher Yu, Yue Wang, Hang Zhao, Zhiding Yu, Chen Feng
Monocular scene understanding is a foundational component of autonomous systems.
3D Semantic Scene Completion 3D Semantic Scene Completion from a single 2D image
1 code implementation • 8 Mar 2023 • Liangliang Yao, Changhong Fu, Sihang Li, Guangze Zheng, Junjie Ye
The proposed method designs a new task-specific object saliency mining network to refine the cross-correlation operation and effectively discriminate foreground and background information.
1 code implementation • 8 Mar 2023 • Changhong Fu, Mutian Cai, Sihang Li, Kunhan Lu, Haobo Zuo, Chongjun Liu
To address the above issues, this work proposes a novel framework with continuity-aware latent interframe information mining for reliable UAV tracking, i. e., ClimRT.
no code implementations • 24 Nov 2022 • Xianlin Song, Sihang Li, Zhuangzhuang Wang
In this work, a 3D information fusion algorithm based on 3D stationary wavelet transform and joint weighted evaluation optimization is proposed to fuse multi-focus photoacoustic data to achieve large-volumetric and high-resolution 3D imaging.
1 code implementation • 14 Aug 2022 • Changhong Fu, Haolin Dong, Junjie Ye, Guangze Zheng, Sihang Li, Jilin Zhao
Pixel-level range mask is introduced to make HighlightNet more focused on the enhancement of the tracking object and regions without light sources.
1 code implementation • 1 Aug 2022 • Changhong Fu, Weiyu Peng, Sihang Li, Junjie Ye, Ziang Cao
Specifically, with local-modeling to global-search mechanism, the proposed tracker replaces the global encoder by a novel local-recognition encoder.
1 code implementation • 16 Jun 2022 • Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua
Specifically, without supervision signals, RGCL uses a rationale generator to reveal salient features about graph instance-discrimination as the rationale, and then creates rationale-aware views for contrastive learning.
1 code implementation • 3 Mar 2022 • Changhong Fu, Sihang Li, Xinnan Yuan, Junjie Ye, Ziang Cao, Fangqiang Ding
Therefore, to help increase awareness of the potential risk and the robustness of UAV tracking, this work proposes a novel adaptive adversarial attack approach, i. e., Ad$^2$Attack, against UAV object tracking.