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portfolio
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publications
Two Generative Design Methods of Hospital Operating Department Layouts Based on Healthcare Systematic Layout Planning and Generative Adversarial Network
Published in Journal of Shanghai Jiaotong University (Science), 2021
Two intelligent design processes based on healthcare systematic layout planning (HSLP) and generative adversarial network (GAN) are proposed in this paper, which aim to solve the generation problem of the plane functional layout of the operating departments (ODs) of general hospitals.
Recommended citation: Zhao, C., Yang, J., Xiong, W., & Li, J. (2021). Two generative design methods of hospital operating department layouts based on healthcare systematic layout planning and generative adversarial network. Journal of Shanghai Jiaotong University (Science), 26, 103-115. https://link.springer.com/article/10.1007/s12204-021-2265-9
Generation of Hospital Emergency Department Layouts Based on Generative Adversarial Networks
Published in Journal of Building Engineering, 2021
This paper takes the functional layout of the emergency departments (EDs) of general hospitals as the research object, combines the hierarchical design concepts and proposes an intelligent functional layout generation method for EDs. It aims to explore the application of intelligent algorithms in architectural design and build an intelligent design method to solve the generation problem of ED layouts.
Recommended citation: Zhao, C. W., Yang, J., & Li, J. (2021). Generation of hospital emergency department layouts based on generative adversarial networks. Journal of Building Engineering, 43, 102539. https://www.sciencedirect.com/science/article/abs/pii/S235271022100396X
Exploring Effective Information Utilization in Multi-Turn Topic-Driven Conversations
Published in arXiv preprint, 2022
In order to expand the information that Pretrained Language Models can utilize, we encode topic and dialogue history information using certain prompts with multiple channels of Fusion-in-Decoder (FiD) and explore the influence of three different channel settings.
Recommended citation: Li, J., He, B., & Mi, F. (2022). Exploring Effective Information Utilization in Multi-Turn Topic-Driven Conversations. arXiv preprint arXiv:2209.00250. https://arxiv.org/abs/2209.00250
Improving Chinese Named Entity Recognition by Search Engine Augmentation
Published in arXiv preprint, 2022
We propose a neural-based approach to perform semantic augmentation using external knowledge from search engine for Chinese NER.
Recommended citation: Mao, Q., Li, J., & Meng, K. (2022). Improving Chinese Named Entity Recognition by Search Engine Augmentation. arXiv preprint arXiv:2210.12662. https://arxiv.org/abs/2210.12662
Generative Diffusion Models on Graphs: Methods and Applications
Published in IJCAI 2023, 2023
In this paper, we first provide a comprehensive overview of generative diffusion models on graphs, In particular, we review representative algorithms for three variants of graph diffusion models, i.e., Score Matching with Langevin Dynamics (SMLD), Denoising Diffusion Probabilistic Model (DDPM), and Score-based Generative Model (SGM). Then, we summarize the major applications of generative diffusion models on graphs with a specific focus on molecule and protein modeling. Finally, we discuss promising directions in generative diffusion models on graph-structured data.
Recommended citation: Wenqi Fan, Chengyi Liu, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li. (2023). Generative Diffusion Models on Graphs: Methods and Applications. IJCAI 2023.
Conflicts, Villains, Resolutions: Towards models of Narrative Media Framing
Published in ACL 2023, 2023
Narrative Framing
Recommended citation: Lea Ferrmann, Jiatong Li, Shima Khanehzar, Gosia Mikolajczak. (2023). Conflicts, Villains, Resolutions: Towards models of Narrative Media Framing. ACL 2023. https://aclanthology.org/2023.acl-long.486/
MFE-NER: Multi-feature Fusion Embedding for Chinese Named Entity Recognition
Published in CCL 2024, 2024
TIn this paper, we propose a new method, Multi-Feature Fusion Embedding for Chinese Named Entity Recognition (MFE-NER), to strengthen the language pattern of Chinese and handle the character substitution problem in Chinese Named Entity Recognition.
Recommended citation: Jiatong Li, Kui Meng. (2024). MFE-NER: Multi-feature Fusion Embedding for Chinese Named Entity Recognition. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference) (pp. 1112-1122). CCL 2024. https://arxiv.org/abs/2109.07877
Fast graph condensation with structure-based neural tangent kernel
Published in WWW 2024, 2024
Graph Condensation
Recommended citation: Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, and Qing Li. (2023). Fast graph condensation with structure-based neural tangent kernel. arXiv preprint arXiv:2310.11046. (Accepted by WWW 24) https://arxiv.org/abs/2310.11046
Chemllm: A chemical large language model
Published in arXiv preprint, 2024
Molecule Discovery, Large Language Models
Recommended citation: Di Zhang, Wei Liu, Qian Tan, Jingdan Chen, Hang Yan, Yuliang Yan, Jiatong Li, Weiran Huang, Xiangyu Yue, Wanli Ouyang, Dongzhan Zhou, Shufei Zhang, Mao Su, Han-Sen Zhong, Yuqiang Li. (2024). Chemllm: A chemical large language model. arXiv preprint arXiv:2402.06852. https://arxiv.org/pdf/2402.06852
Recommender Systems in the Era of Large Language Models (LLMs)
Published in IEEE TKDE, 2024
Recommender Systems, Large Language Models
Recommended citation: Wenqi Fan, Zihuai Zhao, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Jiliang Tang, and Qing Li. (2024). Recommender Systems in the Era of Large Language Models (LLMs). IEEE TKDE. https://arxiv.org/abs/2307.02046
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
Published in IEEE TKDE, 2024
Molecule Discovery, Large Language Models
Recommended citation: Jiatong Li, Yunqing Liu, Wenqi Fan, Xiao-yong Wei, Hui Liu, Jiliang Tang, and Qing Li. (2024). Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective. IEEE TKDE. https://arxiv.org/abs/2306.06615
Search Engine Augmented Chinese Named Entity Recognition for Big Data Content Security
Published in CBDCom 2025, 2025
Chinese Named Entity Recognition, Search Engine Augmentation
Recommended citation: Qinghua Mao, Jiatong Li, Kui Meng, Yuanyuan Sun, Pengjiao Wang, Jianhua Li. (2025). Search Engine Augmented Chinese Named Entity Recognition for Big Data Content Security. CBDCom 2025. https://ieeexplore.ieee.org/document/11344245
Large Language Models are In-Context Molecule Learners
Published in IEEE TKDE, 2025
Molecule Discovery, Large Language Models
Recommended citation: Jiatong Li, Wei Liu, Zhihao Ding, Wenqi Fan, Yuqiang Li, Qing Li. (2025). Large Language Models are In-Context Molecule Learners. IEEE TKDE. https://arxiv.org/pdf/2403.04197.pdf
Llama-berry: Pairwise optimization for o1-like olympiad-level mathematical reasoning
Published in NAACL 2025, 2025
Large Language Models, Reasoning
Recommended citation: Di Zhang, Jianbo Wu, Jingdi Lei, Tong Che, Jiatong Li, Tong Xie, Xiaoshui Huang, Shufei Zhang, Marco Pavone, Yuqiang Li, Wanli Ouyang, Dongzhan Zhou. (2025). Llama-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning. NAACL 2025. https://arxiv.org/pdf/2410.02884
Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning
Published in CVPR 2025, 2025
Vision Large Language Models, Reasoning
Recommended citation: Di Zhang, Jingdi Lei, Junxian Li, Xunzhi Wang, Yujie Liu, Zonglin Yang, Jiatong Li, Weida Wang, Suorong Yang, Jianbo Wu, Peng Ye, Wanli Ouyang, Dongzhan Zhou. (2025). Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning. CVPR 2025. https://arxiv.org/pdf/2411.18203
Mol-R1: Towards Explicit Long-CoT Reasoning in Molecule Discovery
Published in arXiv preprint, 2025
Molecule Discovery, Large Language Models
Recommended citation: Jiatong Li, Weida Wang*, Qinggang Zhang, Junxian Li, Di Zhang, Changmeng Zheng, Shufei Zhang, Xiaoyong Wei, and Qing Li. (2025). Mol-R1: Towards Explicit Long-CoT Reasoning in Molecule Discovery. arXiv preprint arXiv:2508.08401. https://arxiv.org/abs/2508.08401
CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics
Published in ICLR 2026, 2026
Large Language Models, Benchmark
Recommended citation: Weida Wang*, Dongchen Huang*, Jiatong Li*, Tengchao Yang, Ziyang Zheng, Di Zhang, Dong Han et al. (2026). CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics. ICLR 2026. (Co-First Author) https://arxiv.org/abs/2508.18124
IAG: Input-Aware Backdoor Attack on VLM-Based Visual Grounding
Published in CVPR 2026, 2026
Vision Language Models, Security
Recommended citation: Junxian Li, Beining Xu, Simin Chen, Jiatong Li, Jingdi Lei, Haodong Zhao, and Di Zhang. (2026). IAG: Input-Aware Backdoor Attack on VLM-Based Visual Grounding. CVPR 2026.
MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
Published in IEEE TKDE, 2026
Molecule Discovery, Large Language Models
Recommended citation: Jiatong Li, Yunqing Liu, Wei Liu, Jingdi Le, Di Zhang, Wenqi Fan, Dongzhan Zhou, Yuqiang Li, and Qing Li. (2026). MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts. IEEE TKDE. https://arxiv.org/pdf/2411.14721
Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation
Published in KDD 2026, 2026
Molecule Discovery, Large Language Models
Recommended citation: Jiatong Li*, Junxian Li*, Yunqing Liu, Dongzhan Zhou, and Qing Li. (2026). Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation. KDD 2026. https://arxiv.org/pdf/2412.14642
Chem-R: Learning to Reason as a Chemist
Published in KDD 2026, 2026
Molecule Discovery, Large Language Models, Reasoning
Recommended citation: Weida Wang, Benteng Chen, Di Zhang, Wanhao Liu, Shuchen Pu, Ben Gao, Jin Zeng, Xiaoyong Wei, Tianshu Yu, Shuzhou Sun, Tianfan Fu, Wanli Ouyang, Lei Bai, Jiatong Li, Zifu Wang, Yuqiang Li, Shufei Zhang. (2026). Chem-R: Learning to Reason as a Chemist. KDD 2026.
MolViBench: Evaluating LLMs on Molecular Vibe Coding
Published in arXiv preprint, 2026
Molecule Discovery, Large Language Models
Recommended citation: Jiatong Li*, Yuxuan Ren, Weida Wang, Changmeng Zheng, Xiao-yong Wei, Qing Li, and Yatao Bian. (2026). MolViBench: Evaluating LLMs on Molecular Vibe Coding. arXiv preprint arXiv:2605.02351. https://arxiv.org/abs/2605.02351
talks
Recommender Systems in the Era of Large Language Models (LLMs)
Published:
Wenqi Fan, Jiatong Li, Zihuai Zhao, Yunqing Liu, Yiqi Wang
teaching
COMP2411_20231_A DATABASE SYSTEMS
Teaching Assistant, The Hong Kong Polytechnic University, Department of Computing, 2023
I worked as a teaching assistant of COMP2411_20231_A DATABASE SYSTEMS in the semester of 2023 Fall.
COMP6703_20241_A ADVANCED TOPICS IN DATA ANALYTICS
Teaching Assistant, The Hong Kong Polytechnic University, Department of Computing, 2024
I worked as a teaching assistant of COMP6703_20241_A ADVANCED TOPICS IN DATA ANALYTICSS in the semester of 2024 Fall. I am glad to work with Prof. Hongxia Yang to deliver the course content and help students with their assignments and projects.