| Large Language Models for Automated Open-domain Scientific Hypotheses Discovery Z Yang, X Du, J Li, J Zheng, S Poria, E Cambria ACL 2024; 🏆Best Poster Award in ICML 2024 AI4Science workshop, 2023 | 109* | 2023 |
| Language Models as Inductive Reasoners Z Yang, L Dong, X Du, H Cheng, E Cambria, X Liu, J Gao, F Wei EACL 2024, 2022 | 89* | 2022 |
| LLM4SR: A Survey on Large Language Models for Scientific Research Z Luo*, Z Yang*, Z Xu, W Yang, X Du arXiv preprint arXiv:2501.04306, 2025 | 62* | 2025 |
| A Survey on Semantic Processing Techniques R Mao*, K He*, X Zhang*, G Chen*, J Ni*, Z Yang*, E Cambria IF 101, 101988, 2021 | 62 | 2021 |
| MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses Z Yang, W Liu, B Gao, T Xie, Y Li, W Ouyang, S Poria, E Cambria, D Zhou ICLR 2025, 2024 | 61 | 2024 |
| Logical Reasoning Over Natural Language as Knowledge Representation: A Survey Z Yang, X Du, R Mao, J Ni, E Cambria ACL 2023 NLRSE workshop, 2023 | 40* | 2023 |
| Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning D Zhang, J Lei, J Li, X Wang, Y Liu, Z Yang, J Li, W Wang, S Yang, J Wu, ... CVPR 2025, 2024 | 32 | 2024 |
| Improving Event Duration Prediction via Time-aware Pre-training Z Yang, X Du, A Rush, C Cardie EMNLP 2020, 2020 | 27 | 2020 |
| ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition Y Liu*, Z Yang*, T Xie, J Ni, B Gao, Y Li, S Tang, W Ouyang, E Cambria, ... arXiv preprint arXiv:2503.21248, 2025 | 23 | 2025 |
| Reducing the Dilution: An Analysis of the Information Sensitiveness of Capsule Network With a Practical Solution Z Yang, X Wang | 21* | 2019 |
| End-to-end Case-Based Reasoning for Commonsense Knowledge Base Completion Z Yang, X Du, E Cambria, C Cardie EACL 2023 (Oral), 2023 | 19 | 2023 |
| Finding the Pillars of Strength for Multi-Head Attention J Ni, R Mao, Z Yang, H Lei, E Cambria ACL 2023, 2023 | 16 | 2023 |
| Task-Aware Self-Supervised Framework for Dialogue Discourse Parsing W Li, L Zhu, W Shao, Z Yang, E Cambria EMNLP 2023, 2023 | 8 | 2023 |
| Harnessing Large Language Models for Scientific Novelty Detection Y Liu, Z Yang, S Poria, TS Nguyen, E Cambria arXiv preprint arXiv:2505.24615, 2025 | 6 | 2025 |
| Miromind-M1: An Open-Source Advancement in Mathematical Reasoning via Context-Aware Multi-Stage Policy Optimization X Li, Y Xiao, D Ng, H Ye, Y Deng, X Lin, B Wang, Z Mo, C Zhang, Y Zhang, ... Technical Report, 2025 | 4 | 2025 |
| MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search Z Yang, W Liu, B Gao, Y Liu, W Li, T Xie, L Bing, W Ouyang, E Cambria, ... NeurIPS 2025, 2025 | 4 | 2025 |
| MOOSE-Chem3: Toward Experiment-Guided Hypothesis Ranking via Simulated Experimental Feedback W Liu*, Z Yang*, J Wang, L Bing, D Zhang, D Zhou, Y Li, H Li, E Cambria, ... arXiv preprint arXiv:2505.17873, 2025 | 3 | 2025 |
Erik CambriaProfessor @ NTU CCDS & Visiting @ MIT Media LabVerified email at media.mit.edu
