| HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering Z Yang, P Qi, S Zhang, Y Bengio, WW Cohen, R Salakhutdinov, ... Empirical Methods in Natural Language Processing (EMNLP), 2018 | 363 | 2018 |
| Graph Convolution over Pruned Dependency Trees Improves Relation Extraction Y Zhang, P Qi, CD Manning Empirical Methods in Natural Language Processing (EMNLP), 2018 | 278 | 2018 |
| Stanford’s graph-based neural dependency parser at the conll 2017 shared task T Dozat, P Qi, CD Manning Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw …, 2017 | 159 | 2017 |
| Universal Dependency Parsing from Scratch P Qi, T Dozat, Y Zhang, CD Manning Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw …, 2018 | 152 | 2018 |
| Sharp nearby, fuzzy far away: How neural language models use context U Khandelwal, H He, P Qi, D Jurafsky Annual Meeting of the Association for Computational Linguistics (ACL), 2018 | 133 | 2018 |
| Stanza: A Python Natural Language Processing Toolkit for Many Human Languages P Qi, Y Zhang, Y Zhang, J Bolton, CD Manning Association of Computational Linguistics (ACL) System Demonstrations, 2020 | 124 | 2020 |
| Building DNN Acoustic Models for Large Vocabulary Speech Recognition AL Maas, P Qi, Z Xie, AY Hannun, CT Lengerich, D Jurafsky, AY Ng Computer Speech & Language, 2014 | 95* | 2014 |
| Answering Complex Open-domain Questions Through Iterative Query Generation P Qi, X Lin, L Mehr, Z Wang, CD Manning Empirical Methods in Natural Language Processing and International Joint …, 2019 | 39 | 2019 |
| Arc-swift: A Novel Transition System for Dependency Parsing P Qi, CD Manning Proceedings of the 55th annual meeting of the Association for Computational …, 2017 | 20 | 2017 |
| Stanford at TAC KBP 2016: Sealing Pipeline Leaks and Understanding Chinese. Y Zhang, AT Chaganty, A Paranjape, D Chen, J Bolton, P Qi, CD Manning TAC, 2016 | 14 | 2016 |
| TinkerBell: Cross-lingual Cold-Start Knowledge Base Construction. M Al-Badrashiny, J Bolton, AT Chaganty, K Clark, C Harman, L Huang, ... TAC, 2017 | 13 | 2017 |
| Modeling response properties of V2 neurons using a hierarchical K-means model X Hu, J Zhang, P Qi, B Zhang Neurocomputing 134, 198-205, 2014 | 6 | 2014 |
| Hierarchical k-means algorithm for modeling visual area v2 neurons X Hu, P Qi, B Zhang International Conference on Neural Information Processing, 373-381, 2012 | 6 | 2012 |
| Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversations P Qi, Y Zhang, CD Manning arXiv preprint arXiv:2004.14530, 2020 | 5 | 2020 |
| Biomedical and Clinical English Model Packages in the Stanza Python NLP Library Y Zhang, Y Zhang, P Qi, CD Manning, CP Langlotz arXiv preprint arXiv:2007.14640, 2020 | 4 | 2020 |
| Retrieve, Rerank, Read, then Iterate: Answering Open-Domain Questions of Arbitrary Complexity from Text P Qi, H Lee, O Sido, CD Manning arXiv preprint arXiv:2010.12527, 2020 | 3 | 2020 |
| Neural Generation Meets Real People: Towards Emotionally Engaging Mixed-Initiative Conversations A Paranjape, A See, K Kenealy, H Li, A Hardy, P Qi, KR Sadagopan, ... arXiv preprint arXiv:2008.12348, 2020 | 3 | 2020 |
| Stanford at TAC KBP 2017: Building a Trilingual Relational Knowledge Graph A Chaganty, A Paranjape, J Bolton, M Lamm, J Lei, A See, K Clark, ... Proceedings of TAC, 2017 | 3 | 2017 |
| Neural text summarization U Khandelwal, P Qi, D Jurafsky Stanford University, Stanford, CA, USA, 2016 | 3 | 2016 |
| Learning nonlinear statistical regularities in natural images by modeling the outer product of image intensities P Qi, X Hu Neural computation 26 (4), 693-711, 2014 | 3 | 2014 |
Christopher D ManningProfessor of Computer Science and Linguistics, Stanford UniversityVerified email at stanford.edu
