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Jiaxin Zhang 0005
Person information
- affiliation: Intuit AI Research, Mountain View, CA, USA
- affiliation: Oak Ridge National Laboratory, TN, USA
- affiliation (former): Johns Hopkins University, Department of Civil Engineering, Baltimore, MD, USA
Other persons with the same name
- Jiaxin Zhang — disambiguation page
- Jiaxin Zhang 0001
— Beijing University of Posts and Telecommunications, MOE, Key Laboratory of Universal Wireless Communication, China
- Jiaxin Zhang 0002 — Second Highway Survey Design and Research Institute, Ministry of Communications, Wuhan, China
- Jiaxin Zhang 0003
- Jiaxin Zhang 0004 — Ohio State University, Department of Computer Science and Engineering, Columbus, OH, USA
- Jiaxin Zhang 0006 — University of Science and Technology of China, School of Computer Science and Technology, Hefei, China
- Jiaxin Zhang 0007
- Jiaxin Zhang 0008 — Rhode Island School of Design, Providence, RI, USA
- Jiaxin Zhang 0009
- Jiaxin Zhang 0010 — State Grid Shenyang Electric Power Supply Company, Operation Monitoring Center, China
- Jiaxin Zhang 0011 — Nankai University, College of Computer Science, Tianjin, China
- Jiaxin Zhang 0012
- Jiaxin Zhang 0013
- Jiaxin Zhang 0014
- Jiaxin Zhang 0015 — University of Waterloo, Department of Geography and Environmental Management, ON, Canada
- Jiaxin Zhang 0017 — Dalian Polytechnic University, School of Fashion, China
- Jiaxin Zhang 0018
- Jiaxin Zhang 0019
- Jiaxin Zhang 0020
- Jiaxin Zhang 0021 — Capital Normal University, Beijing, China
- Jiaxin Zhang 0022 — University of Manchester, UK
- Jiaxin Zhang 0023 — State Grid Hebei Electric Power Research Institute, Shijiazhuang, China
- Jiaxin Zhang 0024 — University of Strathclyde, Glasgow, UK
- Jiaxin Zhang 0025
- Jiaxin Zhang 0026 — Dalian University of Technology, DUT-RU International School of Information Science and Engineering, China
- Jiaxin Zhang 0027 — Northeast Electric Power University, Jilin, China
- Jiaxin Zhang 0029
- Jiaxin Zhang 0030
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2020 – today
- 2024
- [c24]Jiaxin Zhang, Kamalika Das, Kumar Sricharan:
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. AISTATS 2024: 2917-2925 - [c23]Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das:
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. EACL (1) 2024: 2336-2346 - [c22]Wendi Cui, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan, Jiaxin Zhang:
Divide-Conquer-Reasoning for Consistency Evaluation and Automatic Improvement of Large Language Models. EMNLP (Industry Track) 2024: 334-361 - [c21]Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley A. Malin:
Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation. EMNLP 2024: 6130-6151 - [c20]Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Kumar Sricharan:
Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models. EMNLP 2024: 21456-21473 - [c19]Minqian Liu, Zhiyang Xu, Zihao Lin, Trevor Ashby, Joy Rimchala, Jiaxin Zhang, Lifu Huang:
Holistic Evaluation for Interleaved Text-and-Image Generation. EMNLP 2024: 22002-22016 - [c18]Jiaxin Zhang, Sirui Bi, Victor Fung:
On the Quantification of Image Reconstruction Uncertainty without Training Data. WACV 2024: 2061-2070 - [c17]Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan:
DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. WACV 2024: 8021-8030 - [i30]Wendi Cui, Jiaxin Zhang, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan:
DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models. CoRR abs/2401.02132 (2024) - [i29]Syed Irfan Ali Meerza, Luyang Liu, Jiaxin Zhang, Jian Liu:
GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning. CoRR abs/2401.03562 (2024) - [i28]Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan:
PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models. CoRR abs/2402.11347 (2024) - [i27]Jiaxin Zhang, Kamalika Das, Kumar Sricharan:
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. CoRR abs/2402.12664 (2024) - [i26]Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das:
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. CoRR abs/2403.02509 (2024) - [i25]Minqian Liu, Zhiyang Xu, Zihao Lin, Trevor Ashby, Joy Rimchala, Jiaxin Zhang, Lifu Huang:
Holistic Evaluation for Interleaved Text-and-Image Generation. CoRR abs/2406.14643 (2024) - [i24]Zhiyang Xu, Minqian Liu, Ying Shen, Joy Rimchala, Jiaxin Zhang, Qifan Wang, Yu Cheng, Lifu Huang:
Lateralization LoRA: Interleaved Instruction Tuning with Modality-Specialized Adaptations. CoRR abs/2407.03604 (2024) - [i23]Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley A. Malin:
Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation. CoRR abs/2410.08320 (2024) - [i22]Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Kumar Sricharan:
Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models. CoRR abs/2410.09629 (2024) - [i21]Ankita Sinha, Wendi Cui, Kamalika Das, Jiaxin Zhang:
Survival of the Safest: Towards Secure Prompt Optimization through Interleaved Multi-Objective Evolution. CoRR abs/2410.09652 (2024) - 2023
- [c16]Yu Wang, Ján Drgona, Jiaxin Zhang, Karthik Somayaji Nanjangud Suryanarayana, Malachi Schram, Frank Liu, Peng Li:
AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution. AAAI 2023: 10244-10252 - [c15]Sirui Bi, Victor Fung, Jiaxin Zhang:
Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling. AAAI 2023: 14711-14719 - [c14]Yue Cui
RecUP-FL: Reconciling Utility and Privacy in Federated learning via User-configurable Privacy Defense. AsiaCCS 2023: 80-94 - [c13]Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan:
SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. EMNLP (Findings) 2023: 15445-15458 - [c12]Zhuohang Li, Jiaxin Zhang, Jian Liu:
Speech Privacy Leakage from Shared Gradients in Distributed Learning. ICASSP 2023: 1-5 - [c11]Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan:
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. NeurIPS 2023 - [i20]Zhuohang Li, Jiaxin Zhang, Jian Liu:
Speech Privacy Leakage from Shared Gradients in Distributed Learning. CoRR abs/2302.10441 (2023) - [i19]Yue Cui, Syed Irfan Ali Meerza, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu:
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense. CoRR abs/2304.05135 (2023) - [i18]Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan:
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. CoRR abs/2310.20153 (2023) - [i17]Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan:
SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. CoRR abs/2311.01740 (2023) - [i16]Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan:
DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. CoRR abs/2311.09625 (2023) - [i15]Sirui Bi, Victor Fung, Jiaxin Zhang:
On the Quantification of Image Reconstruction Uncertainty without Training Data. CoRR abs/2311.09639 (2023) - 2022
- [j3]Victor Fung
Atomic structure generation from reconstructing structural fingerprints. Mach. Learn. Sci. Technol. 3(4): 45018 (2022) - [c10]Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao:
Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification. AAAI 2022: 8370-8377 - [c9]Zhuohang Li, Jiaxin Zhang, Luyang Liu, Jian Liu:
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage. CVPR 2022: 10122-10132 - [c8]Syed Irfan Ali Meerza
Fair and Privacy-Preserving Alzheimer's Disease Diagnosis Based on Spontaneous Speech Analysis via Federated Learning. EMBC 2022: 1362-1365 - [c7]Yue Cui, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu:
Privacy-preserving Speech-based Depression Diagnosis via Federated Learning. EMBC 2022: 1371-1374 - [i14]Zhuohang Li, Jiaxin Zhang, Luyang Liu, Jian Liu:
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage. CoRR abs/2203.15696 (2022) - [i13]Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh:
Atomic structure generation from reconstructing structural fingerprints. CoRR abs/2207.13227 (2022) - [i12]Jiaxin Zhang, Sirui Bi, Victor Fung:
Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling. CoRR abs/2212.01016 (2022) - 2021
- [c6]Jiaxin Zhang, Sirui Bi, Guannan Zhang:
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models. AISTATS 2021: 3745-3753 - [c5]Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu:
Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates. ICPADS 2021: 372-379 - [c4]Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar:
On the Stochastic Stability of Deep Markov Models. NeurIPS 2021: 24033-24047 - [c3]Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang:
Enabling long-range exploration in minimization of multimodal functions. UAI 2021: 1639-1649 - [c2]Jingbo Sun
Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification. CSSL 2021: 118-133 - [i11]Jiaxin Zhang, Sirui Bi, Guannan Zhang:
A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models. CoRR abs/2103.08026 (2021) - [i10]Jiaxin Zhang, Sirui Bi, Guannan Zhang:
A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models. CoRR abs/2103.08594 (2021) - [i9]Victor Fung, Jiaxin Zhang, Guoxiang Hu, Panchapakesan Ganesh, Bobby G. Sumpter:
Inverse design of two-dimensional materials with invertible neural networks. CoRR abs/2106.03013 (2021) - [i8]Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu:
Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates. CoRR abs/2107.01477 (2021) - [i7]Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar:
On the Stochastic Stability of Deep Markov Models. CoRR abs/2111.04601 (2021) - [i6]Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob H. Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer:
Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR abs/2112.03235 (2021) - [i5]Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao:
Gradient-based Novelty Detection Boosted by Self-supervised Binary Classification. CoRR abs/2112.09815 (2021) - 2020
- [j2]Jiaxin Zhang
On the quantification and efficient propagation of imprecise probabilities with copula dependence. Int. J. Approx. Reason. 122: 24-46 (2020) - [i4]Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang:
A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. CoRR abs/2002.03001 (2020) - [i3]Congjie Wei, Jiaxin Zhang, Kenneth M. Liechti, Chenglin Wu:
Data Driven Modeling of Interfacial Traction Separation Relations using Thermodynamic Consistent Neural Network (TCNN). CoRR abs/2011.09946 (2020) - [i2]Jiaxin Zhang
Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics. CoRR abs/2011.14172 (2020) - [i1]Sirui Bi, Jiaxin Zhang
Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials. CoRR abs/2011.14177 (2020)
2010 – 2019
- 2019
- [c1]Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle:
Learning nonlinear level sets for dimensionality reduction in function approximation. NeurIPS 2019: 13199-13208 - 2016
- [j1]Michael D. Shields
The generalization of Latin hypercube sampling. Reliab. Eng. Syst. Saf. 148: 96-108 (2016)
Coauthor Index
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last updated on 2024-12-13 20:05 CET by the dblp team
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