Jiaxin Zhang - RankMe

75 papers A* 13A 6B 1Misc 1Journal 45Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Agentic Confidence Calibration. CoRR Jiaxin Zhang, Caiming Xiong, Chien-Sheng Wu
2026	J	`jnl`	Agentic Uncertainty Quantification. CoRR Jiaxin Zhang, Prafulla Kumar Choubey, Kung-Hsiang Huang, Caiming Xiong, Chien-Sheng Wu
2026	J	`jnl`	From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models. CoRR Jiaxin Zhang, Wendi Cui, Zhuohang Li, Lifu Huang, Bradley A. Malin, Caiming Xiong, Chien-Sheng Wu
2026	J	`jnl`	IR CoRR Mohammad Beigi, Ming Jin, Junshan Zhang, Jiaxin Zhang, Qifan Wang, Lifu Huang
2025	J	`jnl`	Automatic Prompt Optimization via Heuristic Search: A Survey. CoRR Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	—	`conf`	Gradient-guided Attention Map Editing: Towards Efficient Contextual Hallucination Mitigation. NAACL (Findings) Yu Wang, Jiaxin Zhang, Xiang Gao, Wendi Cui, Peng Li, Kamalika Das
2025	J	`jnl`	Gradient-guided Attention Map Editing: Towards Efficient Contextual Hallucination Mitigation. CoRR Yu Wang, Jiaxin Zhang, Xiang Gao, Wendi Cui, Peng Li, Kamalika Das
2025	—	`conf`	Heuristic-based Search Algorithm in Automatic Instruction-focused Prompt Optimization: A Survey. ACL (Findings) Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	J	`jnl`	LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer. CoRR Ying Shen, Zhiyang Xu, Jiuhai Chen, Shizhe Diao, Jiaxin Zhang, Yuguang Yao, Joy Rimchala, Ismini Lourentzou, Lifu Huang
2025	J	`jnl`	MMPersuade: A Dataset and Evaluation Framework for Multimodal Persuasion. CoRR Haoyi Qiu, Yilun Zhou, Pranav Narayanan Venkit, Kung-Hsiang Huang, Jiaxin Zhang, Nanyun Peng, Chien-Sheng Wu
2025	A*	`conf`	Modality-Specialized Synergizers for Interleaved Vision-Language Generalists. ICLR Zhiyang Xu, Minqian Liu, Ying Shen, Joy Rimchala, Jiaxin Zhang, Qifan Wang, Yu Cheng, Lifu Huang
2025	J	`jnl`	Nudging the Boundaries of LLM Reasoning. CoRR Justin Chih-Yao Chen, Becky Xiangyu Peng, Prafulla Kumar Choubey, Kung-Hsiang Huang, Jiaxin Zhang, Mohit Bansal, Chien-Sheng Wu
2025	A*	`conf`	R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation. EMNLP Kaijie Chen, Zihao Lin, Zhiyang Xu, Ying Shen, Yuguang Yao, Joy Rimchala, Jiaxin Zhang, Lifu Huang
2025	J	`jnl`	R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation. CoRR Kaijie Chen, Zihao Lin, Zhiyang Xu, Ying Shen, Yuguang Yao, Joy Rimchala, Jiaxin Zhang, Lifu Huang
2025	J	`jnl`	SCE: Scalable Consistency Ensembles Make Blackbox Large Language Model Generation More Reliable. CoRR Jiaxin Zhang, Zhuohang Li, Wendi Cui, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	—	`conf`	SEE: Strategic Exploration and Exploitation for Cohesive In-Context Prompt Optimization. ACL (1) Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	A*	`conf`	Towards Statistical Factuality Guarantee for Large Vision-Language Models. EMNLP Zhuohang Li, Chao Yan, Nicholas J. Jackson, Wendi Cui, Bo Li, Jiaxin Zhang, Bradley A. Malin
2025	J	`jnl`	Towards Statistical Factuality Guarantee for Large Vision-Language Models. CoRR Zhuohang Li, Chao Yan, Nicholas J. Jackson, Wendi Cui, Bo Li, Jiaxin Zhang, Bradley A. Malin
2024	J	`jnl`	DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models. CoRR Wendi Cui, Jiaxin Zhang, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2024	A	`conf`	DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. WACV Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
2024	A	`conf`	Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. AISTATS Jiaxin Zhang, Kamalika Das, Kumar Sricharan
2024	J	`jnl`	Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. CoRR Jiaxin Zhang, Kamalika Das, Kumar Sricharan
2024	—	`conf`	Divide-Conquer-Reasoning for Consistency Evaluation and Automatic Improvement of Large Language Models. EMNLP (Industry Track) Wendi Cui, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan, Jiaxin Zhang
2024	A*	`conf`	Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation. EMNLP Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley A. Malin
2024	J	`jnl`	Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation. CoRR Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley A. Malin
2024	J	`jnl`	GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning. CoRR Syed Irfan Ali Meerza, Luyang Liu, Jiaxin Zhang, Jian Liu
2024	A*	`conf`	Holistic Evaluation for Interleaved Text-and-Image Generation. EMNLP Minqian Liu, Zhiyang Xu, Zihao Lin, Trevor Ashby, Joy Rimchala, Jiaxin Zhang, Lifu Huang
2024	J	`jnl`	Holistic Evaluation for Interleaved Text-and-Image Generation. CoRR Minqian Liu, Zhiyang Xu, Zihao Lin, Trevor Ashby, Joy Rimchala, Jiaxin Zhang, Lifu Huang
2024	J	`jnl`	Lateralization LoRA: Interleaved Instruction Tuning with Modality-Specialized Adaptations. CoRR Zhiyang Xu, Minqian Liu, Ying Shen, Joy Rimchala, Jiaxin Zhang, Qifan Wang, Yu Cheng, Lifu Huang
2024	A	`conf`	On the Quantification of Image Reconstruction Uncertainty without Training Data. WACV Jiaxin Zhang, Sirui Bi, Victor Fung
2024	J	`jnl`	PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models. CoRR Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2024	—	`conf`	SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. EACL (1) Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
2024	J	`jnl`	SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. CoRR Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
2024	J	`jnl`	Survival of the Safest: Towards Secure Prompt Optimization through Interleaved Multi-Objective Evolution. CoRR Ankita Sinha, Wendi Cui, Kamalika Das, Jiaxin Zhang
2024	A*	`conf`	Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models. EMNLP Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Kumar Sricharan
2024	J	`jnl`	Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models. CoRR Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Kumar Sricharan
2023	A*	`conf`	Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling. AAAI Sirui Bi, Victor Fung, Jiaxin Zhang
2023	A*	`conf`	AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution. AAAI Yu Wang, Ján Drgona, Jiaxin Zhang, Karthik Somayaji Nanjangud Suryanarayana, Malachi Schram, Frank Liu, Peng Li
2023	J	`jnl`	DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. CoRR Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
2023	A*	`conf`	Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. NeurIPS Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan
2023	J	`jnl`	Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. CoRR Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan
2023	J	`jnl`	On the Quantification of Image Reconstruction Uncertainty without Training Data. CoRR Sirui Bi, Victor Fung, Jiaxin Zhang
2023	J	`jnl`	RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense. CoRR Yue Cui, Syed Irfan Ali Meerza, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu
2023	A	`conf`	RecUP-FL: Reconciling Utility and Privacy in Federated learning via User-configurable Privacy Defense. AsiaCCS Yue Cui, Syed Irfan Ali Meerza, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu
2023	J	`jnl`	SAC CoRR Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2023	—	`conf`	SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. EMNLP (Findings) Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2023	Misc	`conf`	Speech Privacy Leakage from Shared Gradients in Distributed Learning. ICASSP Zhuohang Li, Jiaxin Zhang, Jian Liu
2023	J	`jnl`	Speech Privacy Leakage from Shared Gradients in Distributed Learning. CoRR Zhuohang Li, Jiaxin Zhang, Jian Liu
2022	J	`jnl`	Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling. CoRR Jiaxin Zhang, Sirui Bi, Victor Fung
2022	J	`jnl`	Atomic structure generation from reconstructing structural fingerprints. CoRR Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh
2022	J	`jnl`	Atomic structure generation from reconstructing structural fingerprints. Mach. Learn. Sci. Technol. Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh
2022	A*	`conf`	Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage. CVPR Zhuohang Li, Jiaxin Zhang, Luyang Liu, Jian Liu
2022	J	`jnl`	Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage. CoRR Zhuohang Li, Jiaxin Zhang, Luyang Liu, Jian Liu
2022	—	`conf`	Fair and Privacy-Preserving Alzheimer's Disease Diagnosis Based on Spontaneous Speech Analysis via Federated Learning. EMBC Syed Irfan Ali Meerza, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu
2022	A*	`conf`	Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification. AAAI Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao
2022	—	`conf`	Privacy-preserving Speech-based Depression Diagnosis via Federated Learning. EMBC Yue Cui, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu
2021	J	`jnl`	A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models. CoRR Jiaxin Zhang, Sirui Bi, Guannan Zhang
2021	A	`conf`	A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models. AISTATS Jiaxin Zhang, Sirui Bi, Guannan Zhang
2021	J	`jnl`	A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models. CoRR Jiaxin Zhang, Sirui Bi, Guannan Zhang
2021	B	`conf`	Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates. ICPADS Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu
2021	J	`jnl`	Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates. CoRR Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu
2021	A	`conf`	Enabling long-range exploration in minimization of multimodal functions. UAI Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang
2021	J	`jnl`	Gradient-based Novelty Detection Boosted by Self-supervised Binary Classification. CoRR Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao
2021	J	`jnl`	Inverse design of two-dimensional materials with invertible neural networks. CoRR Victor Fung, Jiaxin Zhang, Guoxiang Hu, Panchapakesan Ganesh, Bobby G. Sumpter
2021	A*	`conf`	On the Stochastic Stability of Deep Markov Models. NeurIPS Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar
2021	J	`jnl`	On the Stochastic Stability of Deep Markov Models. CoRR Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar
2021	—	`conf`	Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification. CSSL Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao
2021	J	`jnl`	Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR 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
2020	J	`jnl`	A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. CoRR Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang
2020	J	`jnl`	Data Driven Modeling of Interfacial Traction Separation Relations using Thermodynamic Consistent Neural Network (TCNN). CoRR Congjie Wei, Jiaxin Zhang, Kenneth M. Liechti, Chenglin Wu
2020	J	`jnl`	On the quantification and efficient propagation of imprecise probabilities with copula dependence. Int. J. Approx. Reason. Jiaxin Zhang, Michael D. Shields
2020	J	`jnl`	Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials. CoRR Sirui Bi, Jiaxin Zhang, Guannan Zhang
2020	J	`jnl`	Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics. CoRR Jiaxin Zhang, Congjie Wei, Chenglin Wu
2019	A*	`conf`	Learning nonlinear level sets for dimensionality reduction in function approximation. NeurIPS Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle
2016	J	`jnl`	The generalization of Latin hypercube sampling. Reliab. Eng. Syst. Saf. Michael D. Shields, Jiaxin Zhang