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ORCIDJing Huang 0014
Person information
- affiliation: Stanford University, Department of Computer Science, CA, USA
- affiliation (former): University of Illinois at Urbana-Champaign, Department of Computer Science, Urbana, IL, USA
Other persons with the same name
- Jing Huang — disambiguation page
- Jing Huang 0001 — SUN Microsystems, Santa Clara, CA, USA (and 1 more)
- Jing Huang 0002
![[0000-0003-1438-5071]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-1438-5071")
— Jilin University, School of Computer Science and Technology, Changchun, China - Jing Huang 0003 — Beijing University of Technology, Institute of Artificial Intelligence and Robotics, China
- Jing Huang 0004 — Westlake Institute for Advanced Study, Institute for Biology, Hangzhou, China (and 2 more)
- Jing Huang 0005 — Zhejiang Gongshang University, School of Information and Electronic Engineering, Hangzhou, China (and 1 more)
- Jing Huang 0006 — Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning / IDG/McGovern Institute for Brain Research, China (and 1 more)
- Jing Huang 0007 — University of Victoria, Department of Mathematics and Statistics, BC, Canada (and 1 more)
- Jing Huang 0008 — Qualcomm, Santa Clara, CA, USA (and 2 more)
- Jing Huang 0009 — Wuhan Polytechnic, Wuhan City, China
- Jing Huang 0010 — Nanyang Technological University, School of EEE, VIRTUS IC Design Centre of Excellence, Singapore
- Jing Huang 0011 — South China University of Technology, School of Mathematics, Guangzhou, China (and 1 more)
- Jing Huang 0012 — Hunan University, College of Computer Science and Electronic Engineering, Key Laboratory for Embedded and Network Computing, Changsha, China
- Jing Huang 0013 — Wuhan University of Technology, School of Computer Science and Technology, Wuhan, China
- Jing Huang 0015 — Hunan University, College of Mechanical and Vehicle Engineering, State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Changsha, China
- Jing Huang 0016 — Hohai University, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing, China
- Jing Huang 0017 — Sichuan University, School of Public Administration, Chengdu, China
- Jing Huang 0018 — Southern Medical University, Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou, China (and 1 more)
- Jing Huang 0019 — JD AI Research and Platform, Mountain View, CA, USA (and 2 more)
- Jing Huang 0020 — Facebook, Menlo Park, CA, USA (and 1 more)
- Jing Huang 0021 — University of Pennsylvania, Perelman School of Medicine, Departmant of Biostatistics, Epidemiology and Informatics, Philadelphia, PA, USA
- Jing Huang 0022 — Iowa State University, Department of Electrical and Computer Engineering, Ames, IA, USA
- Jing Huang 0023 — University of Illinois at Chicago, Department of Electrical and Computer Engineering, Chicago, IL, USA
- Jing Huang 0024 — Veracyte, Department of Research & Development, San Francisco, CA, USA (and 1 more)
- Jing Huang 0025 — University of Virginia, Department of Aerospace and Mechanical Engineering, Charlottesville, VA, USA (and 1 more)
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2020 – today
- 2024
[c7]Jing Huang, Zhengxuan Wu, Christopher Potts, Mor Geva, Atticus Geiger:
RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations. ACL (1) 2024: 8669-8687- [c6]Jing Huang, Diyi Yang, Christopher Potts:
Demystifying Verbatim Memorization in Large Language Models. EMNLP 2024: 10711-10732 - [c5]Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts:
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions. NAACL (Demonstrations) 2024: 158-165 - [i7]Zhengxuan Wu, Atticus Geiger, Jing Huang, Aryaman Arora, Thomas Icard, Christopher Potts, Noah D. Goodman:
A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments. CoRR abs/2401.12631 (2024) - [i6]Jing Huang, Zhengxuan Wu, Christopher Potts, Mor Geva, Atticus Geiger:
RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations. CoRR abs/2402.17700 (2024) - [i5]Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts:
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions. CoRR abs/2403.07809 (2024) - [i4]Jing Huang, Diyi Yang, Christopher Potts:
Demystifying Verbatim Memorization in Large Language Models. CoRR abs/2407.17817 (2024) - 2023
- [c4]Jing Huang, Zhengxuan Wu, Kyle Mahowald, Christopher Potts:
Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training. ACL (Findings) 2023: 12163-12180 - [c3]Jing Huang, Atticus Geiger, Karel D'Oosterlinck, Zhengxuan Wu, Christopher Potts:
Rigorously Assessing Natural Language Explanations of Neurons. BlackboxNLP@EMNLP 2023: 317-331 - [c2]Jing Huang, Diyi Yang:
Culturally Aware Natural Language Inference. EMNLP (Findings) 2023: 7591-7609 - [i3]Jing Huang, Atticus Geiger, Karel D'Oosterlinck, Zhengxuan Wu, Christopher Potts:
Rigorously Assessing Natural Language Explanations of Neurons. CoRR abs/2309.10312 (2023) - 2022
- [i2]Jing Huang, Zhengxuan Wu, Kyle Mahowald, Christopher Potts:
Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training. CoRR abs/2212.09897 (2022) - 2021
- [c1]Liwei Wang, Jing Huang, Yin Li, Kun Xu, Zhengyuan Yang, Dong Yu:
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation. CVPR 2021: 14090-14100 - 2020
- [i1]Liwei Wang, Jing Huang, Yin Li, Kun Xu, Zhengyuan Yang, Dong Yu:
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation. CoRR abs/2007.01951 (2020)
2010 – 2019
- 2019
- [j1]Liwei Wang, Yin Li, Jing Huang, Svetlana Lazebnik:
Learning Two-Branch Neural Networks for Image-Text Matching Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 41(2): 394-407 (2019)
Coauthor Index
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