Zhengliang Liu
Orcid: 0000-0001-7061-6714
According to our database1,
Zhengliang Liu
authored at least 114 papers
between 2019 and 2025.
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Bibliography
2025
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges.
CoRR, July, 2025
Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems.
CoRR, July, 2025
Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task.
IEEE Trans. Big Data, June, 2025
Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications.
IEEE Trans. Big Data, June, 2025
IEEE Trans. Big Data, June, 2025
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions.
CoRR, April, 2025
Community Graph Convolution Neural Network for Alzheimer's Disease Classification and Pathogenetic Factors Identification.
IEEE Trans. Neural Networks Learn. Syst., February, 2025
Fine-Tuning Open-Source Large Language Models to Improve Their Performance on Radiation Oncology Tasks: A Feasibility Study to Investigate Their Potential Clinical Applications in Radiation Oncology.
CoRR, January, 2025
Urban planning in the age of large language models: Assessing OpenAI o1's performance and capabilities across 556 tasks.
Comput. Environ. Urban Syst., 2025
IEEE Trans. Learn. Technol., 2025
Decoding cortical folding patterns in marmosets using machine learning and large language model.
NeuroImage, 2025
Neurocomputing, 2025
EG-SpikeFormer: Eye-Gaze Guided Transformer on Spiking Neural Networks for Medical Image Analysis.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025
2024
CE-GAN: Community Evolutionary Generative Adversarial Network for Alzheimer's Disease Risk Prediction.
IEEE Trans. Medical Imaging, November, 2024
IEEE Trans. Artif. Intell., August, 2024
Structure Mapping Generative Adversarial Network for Multi-View Information Mapping Pattern Mining.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2024
Inf. Fusion, April, 2024
Medical Image Anal., 2024
Knowl. Based Syst., 2024
A recent evaluation on the performance of LLMs on radiation oncology physics using questions of randomly shuffled options.
CoRR, 2024
Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research.
CoRR, 2024
OracleSage: Towards Unified Visual-Linguistic Understanding of Oracle Bone Scripts through Cross-Modal Knowledge Fusion.
CoRR, 2024
Towards Next-Generation Medical Agent: How o1 is Reshaping Decision-Making in Medical Scenarios.
CoRR, 2024
Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation.
CoRR, 2024
CoRR, 2024
LLM-POTUS Score: A Framework of Analyzing Presidential Debates with Large Language Models.
CoRR, 2024
Examining the Commitments and Difficulties Inherent in Multimodal Foundation Models for Street View Imagery.
CoRR, 2024
A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks.
CoRR, 2024
Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports.
CoRR, 2024
CoRR, 2024
Reasoning before Comparison: LLM-Enhanced Semantic Similarity Metrics for Domain Specialized Text Analysis.
CoRR, 2024
Assessing Large Language Models in Mechanical Engineering Education: A Study on Mechanics-Focused Conceptual Understanding.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
A generic framework for embedding human brain function with temporally correlated autoencoder.
Medical Image Anal., October, 2023
Functional brain network identification and fMRI augmentation using a VAE-GAN framework.
Comput. Biol. Medicine, October, 2023
Differentiating brain states via multi-clip random fragment strategy-based interactive bidirectional recurrent neural network.
Neural Networks, August, 2023
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications.
CoRR, 2023
CoRR, 2023
Noisy probing dose facilitated dose prediction for pencil beam scanning proton therapy: physics enhances generalizability.
CoRR, 2023
Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions.
CoRR, 2023
Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities.
CoRR, 2023
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data.
CoRR, 2023
Benchmarking a foundation LLM on its ability to re-label structure names in accordance with the AAPM TG-263 report.
CoRR, 2023
CoRR, 2023
CoRR, 2023
Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges.
CoRR, 2023
CoRR, 2023
CoRR, 2023
Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Data.
CoRR, 2023
Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer.
CoRR, 2023
CoRR, 2023
Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task.
CoRR, 2023
ImpressionGPT: An Iterative Optimizing Framework for Radiology Report Summarization with ChatGPT.
CoRR, 2023
Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics.
CoRR, 2023
Summary of ChatGPT/GPT-4 Research and Perspective Towards the Future of Large Language Models.
CoRR, 2023
Tailoring Large Language Models to Radiology: A Preliminary Approach to LLM Adaptation for a Highly Specialized Domain.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Multimodal Approaches for Alzheimer's Detection Using Patients' Speech and Transcript.
Proceedings of the Brain Informatics - 16th International Conference, 2023
Chat2Brain: A Method for Mapping Open-Ended Semantic Queries to Brain Activation Maps.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, 2023
Individual Functional Network Abnormalities Mapping via Graph Representation-Based Neural Architecture Search.
Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023
Fine-grained Artificial Neurons in Audio-transformers for Disentangling Neural Auditory Encoding.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
2022
Non-Contact Ultralow Rotational Speed Measurement of Real Objects Based on Rotational Doppler Velocimetry.
IEEE Trans. Instrum. Meas., 2022
Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training.
CoRR, 2022
Discovering Dynamic Functional Brain Networks via Spatial and Channel-wise Attention.
CoRR, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
ClinicalRadioBERT: Knowledge-Infused Few Shot Learning for Clinical Notes Named Entity Recognition.
Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022
Graph Representation Neural Architecture Search for Optimal Spatial/Temporal Functional Brain Network Decomposition.
Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022
AgriBERT: Knowledge-Infused Agricultural Language Models for Matching Food and Nutrition.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
2020
Proceedings of the 31st IEEE Visualization Conference, 2020
2019
Remote. Sens., 2019
Scalable min-max multi-objective cyber-security optimisation over probabilistic attack graphs.
Eur. J. Oper. Res., 2019
Let's Gamble: Uncovering the Impact of Visualization on Risk Perception and Decision-Making.
CoRR, 2019
Proceedings of the Optimization of Complex Systems: Theory, 2019