| DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models B Wang*, W Chen*, H Pei*, C Xie*, M Kang*, C Zhang*, C Xu, Z Xiong, ... Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2023 | 113 | 2023 |
| Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing S Wang, K Guan, C Zhang, DK Lee, AJ Margenot, Y Ge, J Peng, W Zhou, ... Remote Sensing of Environment 271, 112914, 2022 | 89 | 2022 |
| Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data S Wang, K Guan, C Zhang, Q Zhou, S Wang, X Wu, C Jiang, B Peng, ... Remote Sensing of Environment 285, 113366, 2023 | 18 | 2023 |
| Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning S Wang, K Guan, C Zhang, C Jiang, Q Zhou, K Li, Z Qin, EA Ainsworth, ... Remote Sensing of Environment 285, 113386, 2023 | 15 | 2023 |
| DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer J Hong, JT Wang, C Zhang, Z Li, B Li, Z Wang The Twelfth International Conference on Learning Representations, 2023 | 8 | 2023 |
| Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data C Zhang, S Wang arXiv preprint arXiv:2401.17600, 2024 | 2 | 2024 |
| Airborne hyperspectral imaging of cover crop outcomes and tillage intensity in croplands by machine learning and radiative transfer modeling S Wang, K Guan, Q Zhou, C Zhang, C Jiang, K Li, Z Qin, E Ainsworth, ... AGU Fall Meeting Abstracts 2021, B55K-1320, 2021 | 1 | 2021 |
| Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression J Hong*, J Duan*, C Zhang*, Z Li*, C Xie, K Lieberman, J Diffenderfer, ... arXiv preprint arXiv:2403.15447, 2024 | | 2024 |
| Segment Any Stream: Scalable Water Extent Detection with the Segment Anything Model H Zheng*, C Zhang*, K Guan, Y Deng, S Wang, BL Rhoads, AJ Margenot, ... NeurIPS 2023 Computational Sustainability: Promises and Pitfalls from Theory …, 2023 | | 2023 |
| Quantifying inland water quality across the contiguous United States using Sentinel-2 satellite data and machine learning S Wang, Z Lu, X Jia, Q Zhou, C Zhang, K Guan AGU23, 2023 | | 2023 |
| Quantifying streambank erosion in two watersheds of Illinois through high-resolution aerial imagery and Segment Anything Models C Zhang, S Wang, K Guan, H Zheng, S Wang, BL Rhoads, S Zhou, ... AGU23, 2023 | | 2023 |
| AI-empowered hyperspectral sensing advances agricultural ground truthing across scales S Wang, K Guan, EA Ainsworth, C Zhang, ADB Leakey, Q Zhou, ... AGU Fall Meeting Abstracts 2022, GC42D-0726, 2022 | | 2022 |
| Advancing Airborne Hyperspectral Data Processing for Sustainable Agriculture with Parsl D Friedel, K Guan, Q Zhou, C Zhang, S Wang, DS Katz AGU Fall Meeting Abstracts 2022, B42G-1703, 2022 | | 2022 |
| Cross-scale sensing of field-level crop residue cover and cover crops: integrating field observations, airborne hyperspectral imaging, and satellite data S Wang, K Guan, C Zhang, Q Zhou, EA Ainsworth, AJ Margenot, C Jiang, ... AGU Fall Meeting Abstracts 2022, B45B-07, 2022 | | 2022 |
| Cross-scale sensing of field-level crop nitrogen in the US central Corn Belt to support sustainable fertilization management S Wang, K Guan, Q Zhou, C Zhang, EA Ainsworth, PA Townsend, ... AGU23, 0 | | |
Sheng WangUniversity of Illinois Urbana-ChampaignVerified email at illinois.edu
