Shusen Liu - RankMe

63 papers A* 1A 1B 1C 1Misc 1Journal 47Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SciVisAgentBench: A Benchmark for Evaluating Scientific Data Analysis and Visualization Agents. CoRR Kuangshi Ai, Haichao Miao, Kaiyuan Tang, Nathaniel Gorski, Jianxin Sun, Guoxi Liu, Helgi I. Ingólfsson, David Lenz, Hanqi Guo, Hongfeng Yu, Teja Leburu, Michael Molash, Bei Wang, Tom Peterka, Chaoli Wang, Shusen Liu
2025	J	`jnl`	"Understanding Robustness Lottery": A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches. IEEE Trans. Vis. Comput. Graph. Zhimin Li, Shusen Liu, Xin Yu, Bhavya Kailkhura, Jie Cao, James Daniel Diffenderfer, Peer-Timo Bremer, Valerio Pascucci
2025	J	`jnl`	An Evaluation-Centric Paradigm for Scientific Visualization Agents. CoRR Kuangshi Ai, Haichao Miao, Zhimin Li, Chaoli Wang, Shusen Liu
2025	J	`jnl`	Concept Lens: Visual Comparison and Evaluation of Generative Model Manipulations. IEEE Trans. Vis. Comput. Graph. Sangwon Jeong, Mingwei Li, Matthew Berger, Shusen Liu
2025	J	`jnl`	ParaView-MCP: An Autonomous Visualization Agent with Direct Tool Use. CoRR Shusen Liu, Haichao Miao, Peer-Timo Bremer
2025	J	`jnl`	See or Recall: A Sanity Check for the Role of Vision in Solving Visualization Question Answer Tasks with Multimodal LLMs. CoRR Zhimin Li, Haichao Miao, Xinyuan Yan, Valerio Pascucci, Matthew Berger, Shusen Liu
2025	J	`jnl`	Self-supervised and Multi-fidelity Learning for Extended Predictive Soil Spectroscopy. CoRR Luning Sun, José Lucas Safanelli, Jonathan Sanderman, Katerina Georgiou, Colby Brungard, Kanchan Grover, Bryan G. Hopkins, Shusen Liu, Timo Bremer
2025	—	`conf`	VERIRAG: Healthcare Claim Verification via Statistical Audit in Retrieval-Augmented Generation. BCB Shubham Mohole, Hongjun Choi, Shusen Liu, Christine Klymko, Shashank Kushwaha, Derek Shi, Wesam A. Sakla, Sainyam Galhotra, Ruben Glatt
2025	J	`jnl`	VERIRAG: Healthcare Claim Verification via Statistical Audit in Retrieval-Augmented Generation. CoRR Shubham Mohole, Hongjun Choi, Shusen Liu, Christine Klymko, Shashank Kushwaha, Derek Shi, Wesam A. Sakla, Sainyam Galhotra, Ruben Glatt
2024	J	`jnl`	A Visual Comparison of Silent Error Propagation. IEEE Trans. Vis. Comput. Graph. Zhimin Li, Harshitha Menon, Kathryn M. Mohror, Shusen Liu, Luanzheng Guo, Peer-Timo Bremer, Valerio Pascucci
2024	J	`jnl`	AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making. Comput. Graph. Forum Shusen Liu, Haichao Miao, Zhimin Li, Matthew L. Olson, Valerio Pascucci, Peer-Timo Bremer
2024	J	`jnl`	CAN: Concept-Aligned Neurons for Visual Comparison of Deep Neural Network Models. Comput. Graph. Forum Mingwei Li, Sangwon Jeong, Shusen Liu, Matthew Berger
2024	J	`jnl`	Concept Lens: Visually Analyzing the Consistency of Semantic Manipulation in GANs. CoRR Sangwon Jeong, Mingwei Li, Matthew Berger, Shusen Liu
2024	J	`jnl`	Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization. CoRR Hongjun Choi, Jayaraman J. Thiagarajan, Ruben Glatt, Shusen Liu
2024	—	`conf`	RankMean: Module-Level Importance Score for Merging Fine-tuned LLM Models. ACL (Findings) Gabriel J. Perin, Xuxi Chen, Shusen Liu, Bhavya Kailkhura, Zhangyang Wang, Brian Gallagher
2024	J	`jnl`	Text-based Transfer Function Design for Semantic Volume Rendering. CoRR Sangwon Jeong, Jixian Li, Christopher Johnson, Shusen Liu, Matthew Berger
2024	A	`conf`	Text-based transfer function design for semantic volume rendering. IEEE VIS Sangwon Jeong, Jixian Li, Chris R. Johnson, Shusen Liu, Matthew Berger
2024	J	`jnl`	The Visualization JUDGE : Can Multimodal Foundation Models Guide Visualization Design Through Visual Perception? CoRR Matthew Berger, Shusen Liu
2024	—	`conf`	The Visualization JUDGE: Can Multimodal Foundation Models Guide Visualization Design Through Visual Perception? BELIV Matthew Berger, Shusen Liu
2024	J	`jnl`	Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data. Mach. Learn. Sci. Technol. Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh
2024	J	`jnl`	Visualization Literacy of Multimodal Large Language Models: A Comparative Study. CoRR Zhimin Li, Haichao Miao, Valerio Pascucci, Shusen Liu
2023	J	`jnl`	AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making. CoRR Shusen Liu, Haichao Miao, Zhimin Li, Matthew L. Olson, Valerio Pascucci, Peer-Timo Bremer
2023	—	`conf`	Concept Lens: Visually Analyzing the Consistency of Semantic Manipulation in GANs. IEEE VIS (Short Papers) Sangwon Jeong, Mingwei Li, Matthew Berger, Shusen Liu
2023	A*	`conf`	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models. CVPR Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
2023	J	`jnl`	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models. CoRR Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
2023	J	`jnl`	Instance-wise Linearization of Neural Network for Model Interpretation. CoRR Zhimin Li, Shusen Liu, Bhavya Kailkhura, Timo Bremer, Valerio Pascucci
2023	J	`jnl`	Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data. CoRR Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh
2022	J	`jnl`	"Understanding Robustness Lottery": A Comparative Visual Analysis of Neural Network Pruning Approaches. CoRR Zhimin Li, Shusen Liu, Xin Yu, Bhavya Kailkhura, Jie Cao, James Daniel Diffenderfer, Peer-Timo Bremer, Valerio Pascucci
2022	J	`jnl`	Interactively Assessing Disentanglement in GANs. Comput. Graph. Forum Sangwon Jeong, Shusen Liu, Matthew Berger
2022	J	`jnl`	On-the-fly Object Detection using StyleGAN with CLIP Guidance. CoRR Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan, Wesam A. Sakla, Rushil Anirudh
2022	Misc	`conf`	Sparsity Improves Unsupervised Attribute Discovery in Stylegan. ICASSP Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2021	J	`jnl`	Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations. Nat. Mach. Intell. Harsh Bhatia, Timothy S. Carpenter, Helgi I. Ingólfsson, Gautham Dharuman, Piyush Karande, Shusen Liu, Tomas Oppelstrup, Chris Neale, Felice C. Lightstone, Brian Van Essen, James N. Glosli, Peer-Timo Bremer
2021	J	`jnl`	Reliable Graph Neural Network Explanations Through Adversarial Training. CoRR Donald Loveland, Shusen Liu, Bhavya Kailkhura, Anna M. Hiszpanski, Yong Han
2021	J	`jnl`	SpotSDC: Revealing the Silent Data Corruption Propagation in High-Performance Computing Systems. IEEE Trans. Vis. Comput. Graph. Zhimin Li, Harshitha Menon, Dan Maljovec, Yarden Livnat, Shusen Liu, Kathryn M. Mohror, Peer-Timo Bremer, Valerio Pascucci
2020	J	`jnl`	Actionable Attribution Maps for Scientific Machine Learning. CoRR Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han
2020	J	`jnl`	Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design. CoRR Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han
2020	J	`jnl`	Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge. J. Chem. Inf. Model. Anna M. Hiszpanski, Brian Gallagher, Karthik Chellappan, Peggy Li, Shusen Liu, Hyojin Kim, Jinkyu Han, Bhavya Kailkhura, David J. Buttler, Thomas Yong-Jin Han
2020	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom
2020	J	`jnl`	Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections. Mach. Learn. Sci. Technol. Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2019	J	`jnl`	Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Brian K. Spears
2019	J	`jnl`	Function Preserving Projection for Scalable Exploration of High-Dimensional Data. CoRR Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2019	—	`conf`	Generative Counterfactual Introspection for Explainable Deep Learning. GlobalSIP Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han
2019	J	`jnl`	Generative Counterfactual Introspection for Explainable Deep Learning. CoRR Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han
2019	J	`jnl`	NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Models. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Zhimin Li, Tao Li, Vivek Srikumar, Valerio Pascucci, Peer-Timo Bremer
2019	C	`conf`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer
2019	J	`jnl`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears
2019	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer
2018	J	`jnl`	Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. Comput. Graph. Forum Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer
2018	J	`jnl`	Visual Exploration of Semantic Relationships in Neural Word Embeddings. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Vivek Srikumar, Bei Wang, Yarden Livnat, Valerio Pascucci
2018	—	`conf`	Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension. EMNLP (Demonstration) Shusen Liu, Tao Li, Zhimin Li, Vivek Srikumar, Valerio Pascucci, Peer-Timo Bremer
2017	J	`jnl`	Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. CoRR Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer
2017	—	`—`	Visual Exploration of High-Dimensional Spaces Through Identification, Summarization, and Interpretation of Two-Dimensional Projections. Shusen Liu
2017	J	`jnl`	Visualizing High-Dimensional Data: Advances in the Past Decade. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci
2016	J	`jnl`	Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study. Reliab. Eng. Syst. Saf. Dan Maljovec, Shusen Liu, Bei Wang, Diego Mandelli, Peer-Timo Bremer, Valerio Pascucci, Curtis L. Smith
2016	—	`conf`	Embedded domain-specific language and runtime system for progressive spatiotemporal data analysis and visualization. LDAV Cameron Christensen, Ji-Woo Lee, Shusen Liu, Peer-Timo Bremer, Giorgio Scorzelli, Valerio Pascucci
2016	J	`jnl`	The Grassmannian Atlas: A General Framework for Exploring Linear Projections of High-Dimensional Data. Comput. Graph. Forum Shusen Liu, Peer-Timo Bremer, J. J. Jayaraman, Bei Wang, Brian Summa, Valerio Pascucci
2015	J	`jnl`	Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections. Comput. Graph. Forum Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci
2015	—	`conf`	Visualizing High-Dimensional Data: Advances in the Past Decade. EuroVis (STARs) Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci
2014	J	`jnl`	Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data. Comput. Graph. Forum Shusen Liu, Bei Wang, Peer-Timo Bremer, Valerio Pascucci
2014	—	`conf`	Multivariate volume visualization through dynamic projections. LDAV Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci
2012	—	`conf`	Gaussian mixture model based volume visualization. LDAV Shusen Liu, Joshua A. Levine, Peer-Timo Bremer, Valerio Pascucci
2011	B	`conf`	Evaluating graph coloring on GPUs. PPoPP Andre Vincent Pascal Grosset, Peihong Zhu, Shusen Liu, Suresh Venkatasubramanian, Mary W. Hall
2011	J	`jnl`	Feature-Based Statistical Analysis of Combustion Simulation Data. IEEE Trans. Vis. Comput. Graph. Janine Bennett, Vaidyanathan Krishnamoorthy, Shusen Liu, Ray W. Grout, Evatt R. Hawkes, Jacqueline H. Chen, Jason Shepherd, Valerio Pascucci, Peer-Timo Bremer