The generalization of Latin hypercube sampling. - Michael D. Shields; Jiaxin Zhang 005 (Reliab. Eng. Syst. Saf., 2016)

Learning nonlinear level sets for dimensionality reduction in function approximation. - Guannan Zhang; Jiaxin Zhang 005; Jacob D. Hinkle (NeurIPS, 2019)

A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. - Jiaxin Zhang 005; Hoang Tran; Dan Lu 001; Guannan Zhang (CoRR, 2020)

Data Driven Modeling of Interfacial Traction Separation Relations using Thermodynamic Consistent Neural Network (TCNN). - Congjie Wei; Jiaxin Zhang 005; Kenneth M. Liechti; Chenglin Wu (CoRR, 2020)

Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics. - Jiaxin Zhang 005; Congjie Wei; Chenglin Wu (CoRR, 2020)

Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials. - Sirui Bi; Jiaxin Zhang 005; Guannan Zhang (CoRR, 2020)

On the quantification and efficient propagation of imprecise probabilities with copula dependence. - Jiaxin Zhang 005; Michael D. Shields (Int. J. Approx. Reason., 2020)

A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models. - Jiaxin Zhang 005; Sirui Bi; Guannan Zhang (AISTATS, 2021)

Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates. - Zhuohang Li; Luyang Liu; Jiaxin Zhang 005; Jian Liu 001 (ICPADS, 2021)

On the Stochastic Stability of Deep Markov Models. - Ján Drgona; Sayak Mukherjee; Jiaxin Zhang 005; Frank Liu 001; Mahantesh Halappanavar (NeurIPS, 2021)

Enabling long-range exploration in minimization of multimodal functions. - Jiaxin Zhang 005; Hoang Tran; Dan Lu 001; Guannan Zhang (UAI, 2021)

Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification. - Jingbo Sun; Li Yang 009; Jiaxin Zhang 005; Frank Liu 001; Mahantesh Halappanavar; Deliang Fan; Yu Cao 001 (CSSL, 2021)

A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models. - Jiaxin Zhang 005; Sirui Bi; Guannan Zhang (CoRR, 2021)

Inverse design of two-dimensional materials with invertible neural networks. - Victor Fung; Jiaxin Zhang 005; Guoxiang Hu; Panchapakesan Ganesh; Bobby G. Sumpter (CoRR, 2021)

Simulation Intelligence: Towards a New Generation of Scientific Methods. - 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; et al. (CoRR, 2021)

Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification. - Jingbo Sun; Li Yang 009; Jiaxin Zhang 005; Frank Liu 001; Mahantesh Halappanavar; Deliang Fan; Yu Cao 001 (AAAI, 2022)

Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage. - Zhuohang Li; Jiaxin Zhang 005; Luyang Liu; Jian Liu 001 (CVPR, 2022)

Privacy-preserving Speech-based Depression Diagnosis via Federated Learning. - Yue Cui; Zhuohang Li; Luyang Liu; Jiaxin Zhang 005; Jian Liu 001 (EMBC, 2022)

Fair and Privacy-Preserving Alzheimer's Disease Diagnosis Based on Spontaneous Speech Analysis via Federated Learning. - Syed Irfan Ali Meerza; Zhuohang Li; Luyang Liu; Jiaxin Zhang 005; Jian Liu 001 (EMBC, 2022)

Atomic structure generation from reconstructing structural fingerprints. - Victor Fung; Shuyi Jia; Jiaxin Zhang 005; Sirui Bi; Junqi Yin; Panchapakesan Ganesh (Mach. Learn. Sci. Technol., 2022)

Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling. - Sirui Bi; Victor Fung; Jiaxin Zhang 005 (AAAI, 2023)

AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution. - Yu Wang 167; Ján Drgona; Jiaxin Zhang 005; Karthik Somayaji Nanjangud Suryanarayana; Malachi Schram; Frank Liu 001; Peng Li 001 (AAAI, 2023)

RecUP-FL: Reconciling Utility and Privacy in Federated learning via User-configurable Privacy Defense. - Yue Cui; Syed Irfan Ali Meerza; Zhuohang Li; Luyang Liu; Jiaxin Zhang 005; Jian Liu 001 (AsiaCCS, 2023)

SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. - Jiaxin Zhang 005; Zhuohang Li; Kamalika Das; Bradley A. Malin; Kumar Sricharan (EMNLP (Findings), 2023)

Speech Privacy Leakage from Shared Gradients in Distributed Learning. - Zhuohang Li; Jiaxin Zhang 005; Jian Liu 001 (ICASSP, 2023)

Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. - Jiaxin Zhang 005; Zhuohang Li; Kamalika Das; Kumar Sricharan (NeurIPS, 2023)

SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. - Jiaxin Zhang 005; Zhuohang Li; Kamalika Das; Bradley A. Malin; Kumar Sricharan (CoRR, 2023)

Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. - Jiaxin Zhang 005; Kamalika Das; Kumar Sricharan (AISTATS, 2024)

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. - Xiang Gao; Jiaxin Zhang 005; Lalla Mouatadid; Kamalika Das (EACL (1), 2024)

Divide-Conquer-Reasoning for Consistency Evaluation and Automatic Improvement of Large Language Models. - Wendi Cui; Zhuohang Li; Damien Lopez; Kamalika Das; Bradley A. Malin; Kumar Sricharan; Jiaxin Zhang 005 (EMNLP (Industry Track), 2024)

Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation. - Zhuohang Li; Jiaxin Zhang 005; Chao Yan 004; Kamalika Das; Kumar Sricharan; Murat Kantarcioglu; Bradley A. Malin (EMNLP, 2024)

Holistic Evaluation for Interleaved Text-and-Image Generation. - Minqian Liu; Zhiyang Xu; Zihao Lin 003; Trevor Ashby; Joy Rimchala; Jiaxin Zhang 005; Lifu Huang (EMNLP, 2024)

Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models. - Jiaxin Zhang 005; Wendi Cui; Yiran Huang; Kamalika Das; Kumar Sricharan (EMNLP, 2024)

On the Quantification of Image Reconstruction Uncertainty without Training Data. - Jiaxin Zhang 005; Sirui Bi; Victor Fung (WACV, 2024)

DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. - Jiaxin Zhang 005; Joy Rimchala; Lalla Mouatadid; Kamalika Das; Kumar Sricharan (WACV, 2024)

DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models. - Wendi Cui; Jiaxin Zhang 005; Zhuohang Li; Damien Lopez; Kamalika Das; Bradley A. Malin; Kumar Sricharan (CoRR, 2024)

GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning. - Syed Irfan Ali Meerza; Luyang Liu; Jiaxin Zhang 005; Jian Liu 001 (CoRR, 2024)

PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models. - Wendi Cui; Jiaxin Zhang 005; Zhuohang Li; Hao Sun; Damien Lopez; Kamalika Das; Bradley A. Malin; Kumar Sricharan (CoRR, 2024)

Lateralization LoRA: Interleaved Instruction Tuning with Modality-Specialized Adaptations. - Zhiyang Xu; Minqian Liu; Ying Shen 006; Joy Rimchala; Jiaxin Zhang 005; Qifan Wang 001; Yu Cheng; Lifu Huang (CoRR, 2024)

Survival of the Safest: Towards Secure Prompt Optimization through Interleaved Multi-Objective Evolution. - Ankita Sinha; Wendi Cui; Kamalika Das; Jiaxin Zhang 005 (CoRR, 2024)

SEE: Strategic Exploration and Exploitation for Cohesive In-Context Prompt Optimization. - Wendi Cui; Jiaxin Zhang 005; Zhuohang Li; Hao Sun; Damien Lopez; Kamalika Das; Bradley A. Malin; Kumar Sricharan (ACL (1), 2025)

Heuristic-based Search Algorithm in Automatic Instruction-focused Prompt Optimization: A Survey. - Wendi Cui; Jiaxin Zhang 005; Zhuohang Li; Hao Sun; Damien Lopez; Kamalika Das; Bradley A. Malin; Kumar Sricharan (ACL (Findings), 2025)

Modality-Specialized Synergizers for Interleaved Vision-Language Generalists. - Zhiyang Xu; Minqian Liu; Ying Shen 006; Joy Rimchala; Jiaxin Zhang 005; Qifan Wang 001; Yu Cheng; Lifu Huang (ICLR, 2025)

Automatic Prompt Optimization via Heuristic Search: A Survey. - Wendi Cui; Jiaxin Zhang 005; Zhuohang Li; Hao Sun; Damien Lopez; Kamalika Das; Bradley A. Malin; Kumar Sricharan (CoRR, 2025)

Towards Statistical Factuality Guarantee for Large Vision-Language Models. - Zhuohang Li; Chao Yan 004; Nicholas J. Jackson; Wendi Cui; Bo Li 026; Jiaxin Zhang 005; Bradley A. Malin (CoRR, 2025)

SCE: Scalable Consistency Ensembles Make Blackbox Large Language Model Generation More Reliable. - Jiaxin Zhang 005; Zhuohang Li; Wendi Cui; Kamalika Das; Bradley A. Malin; Kumar Sricharan (CoRR, 2025)

R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation. - Kaijie Chen; Zihao Lin 003; Zhiyang Xu; Ying Shen 006; Yuguang Yao; Joy Rimchala; Jiaxin Zhang 005; Lifu Huang (CoRR, 2025)

LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer. - Ying Shen 006; Zhiyang Xu; Jiuhai Chen; Shizhe Diao; Jiaxin Zhang 005; Yuguang Yao; Joy Rimchala; Ismini Lourentzou; Lifu Huang (CoRR, 2025)