Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T23:48:45.351883Z
Paper Citation Record · LEDGER
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification
As of 16 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2509.06367.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
43 of 43 outbound references displayed
- verified exact0
- verified fuzzy31
- unresolved12
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 193c4187-057f-44b0-801b-8144bc94ffb4 · outbound
This paper cites an unresolved cited work.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-04T23:48:58.787071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7ede5f4c-bd55-4e56-808b-73cf6b1b33b5 · outbound
This paper cites Next-generation breeding strategies for climate- ready crops.FRONTIERS IN PLANT SCIENCE, 12, JUL 21 2021.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Next-generation breeding strategies for climate- ready crops.FRONTIERS IN PLANT SCIENCE, 12, JUL 21 2021
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:58.404755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation da88f114-97c0-4c1d-99d1-fe683cd308c2 · outbound
This paper cites Farooq, A.
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:58.024753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ee441708-0247-4f0d-95e5-761cb42bb8b4 · outbound
This paper cites Kamilaris and F.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Kamilaris and F
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:57.619770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9fd9cf40-350c-44f2-8a3b-45b572132555 · outbound
This paper cites Computers and Electronics in Agriculture, 140:461–468, 2017.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Computers and Electronics in Agriculture, 140:461–468, 2017
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:57.164750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b839dc57-fb3f-4d3d-9ee2-bf3e770c0a69 · outbound
This paper cites IdentificationandClassificationofMaizeDroughtStressUsing Deep Convolutional Neural Network.Symmetry, 11(2):256, 2019.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification IdentificationandClassificationofMaizeDroughtStressUsing Deep Convolutional Neural Network.Symmetry, 11(2):256, 2019
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:56.804599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2da5954b-9114-4de1-96fe-369e17c07e3f · outbound
This paper cites an unresolved cited work.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-04T23:48:56.564756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5da790e6-57e9-4e67-a21f-d2df1a3e24f0 · outbound
This paper cites Locke, Steven Mirsky, and Edgar Lobaton.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Locke, Steven Mirsky, and Edgar Lobaton
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:56.304745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e6343723-bafc-4ace-a261-ecf7416844cd · outbound
This paper cites an unresolved cited work.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-04T23:48:56.013939Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ae5b8cd9-838f-4c9d-a700-0c17bc79dc5a · outbound
This paper cites Identify- ing crop water stress using deep learning models.Neural Computing and Applications, 33(10):5353–5367, 2021.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Identify- ing crop water stress using deep learning models.Neural Computing and Applications, 33(10):5353–5367, 2021
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:55.824770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 80e3d88e-b33c-4470-8fff-a9dbe7b9cdfc · outbound
This paper cites Drought stress detection technique for wheat crop using machine learning.PeerJ Computer Science, 9:e1268, 2023.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Drought stress detection technique for wheat crop using machine learning.PeerJ Computer Science, 9:e1268, 2023
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:55.614754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 12b08b30-46e9-4c26-8026-79b80c9eef62 · outbound
This paper cites Potatocropstressidentificationinaerialimages using deep learning-based object detection.Agronomy Journal, 113:3991–4002, 2021.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Potatocropstressidentificationinaerialimages using deep learning-based object detection.Agronomy Journal, 113:3991–4002, 2021
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:55.385493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a772bd5f-5478-49a8-ba79-0a38e1015e0f · outbound
This paper cites Explainable light-weight deep learning pipeline for improved drought stress identification.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Explainable light-weight deep learning pipeline for improved drought stress identification
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:55.184764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 613ea37e-409a-4193-b35c-c96bf45a710a · outbound
This paper cites Hyperspectral machine-learning model for screening tea germplasm resources with drought tolerance.Frontiers in Plant Science, 13, 2022.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Hyperspectral machine-learning model for screening tea germplasm resources with drought tolerance.Frontiers in Plant Science, 13, 2022
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:54.964758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 68f9ca57-ae37-480e-bf35-e72a0221e3b7 · outbound
This paper cites Dao, Yuhong He, and Cameron Proctor.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Dao, Yuhong He, and Cameron Proctor
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:54.724992Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7871ef80-1a9c-4793-8564-3f17be7fe84a · outbound
This paper cites an unresolved cited work.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-04T23:48:54.454903Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 99c9d41b-69c2-40f4-9082-1f0a2a9360dd · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:48:41.134745Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23590f85-212c-4874-90d0-db7a05778929 · outbound
This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:48:41.354824Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23e810fe-9659-4c42-8218-005b9f7abb38 · outbound
This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:48:41.474739Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d2ce8e9f-3217-4ec5-9220-7c3644d99ce1 · outbound
This paper cites Acustomisedvisiontransformer for accurate detection and classification of java plum leaf disease.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Acustomisedvisiontransformer for accurate detection and classification of java plum leaf disease
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:54.194756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2145cfad-fe6a-4a5a-aea2-9ff05ff7617e · outbound
This paper cites Effective plant disease diagnosis using vision transformer trained with leafy-generative adversarial network- generated images.Expert Systems with Applications, 254:124387, 2024.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Effective plant disease diagnosis using vision transformer trained with leafy-generative adversarial network- generated images.Expert Systems with Applications, 254:124387, 2024
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:53.904764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 67c2909e-dd2a-4f97-b2c9-57535762eba7 · outbound
This paper cites A deep learning based approach for automated plant disease classification using vision transformer.Scientific Reports, 12(1):11554, 2022.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification A deep learning based approach for automated plant disease classification using vision transformer.Scientific Reports, 12(1):11554, 2022
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:53.584763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 30b5715f-91c5-4c05-8f3c-5f0a356e0f77 · outbound
This paper cites Vision transformer meets con- volutional neural network for plant disease classification.Ecological Informatics, 77:102245, 2023.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Vision transformer meets con- volutional neural network for plant disease classification.Ecological Informatics, 77:102245, 2023
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:53.079787Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 433818e2-495f-406c-8967-05656c18ee5f · outbound
This paper cites ViT- SmartAgri: Vision transformer and smartphone-based plant disease detection for smart agriculture.Agronomy, 14(2):327, 2024.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification ViT- SmartAgri: Vision transformer and smartphone-based plant disease detection for smart agriculture.Agronomy, 14(2):327, 2024
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:52.684855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 598a2e50-6788-488a-978c-e0c808cd013f · outbound
This paper cites Alanazi, and Jong Weon Lee.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Alanazi, and Jong Weon Lee
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:52.286742Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d1fba222-5ba4-41b4-8c83-ba514b70d65f · outbound
This paper cites An explainable vision transformer with transfer learning based efficient drought stress identification.Plant Molecular Biology, 115(4):98, 2025.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification An explainable vision transformer with transfer learning based efficient drought stress identification.Plant Molecular Biology, 115(4):98, 2025
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:51.748398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d9fc2da2-55bb-404e-89f2-477158c76fea · outbound
This paper cites TrIncNet:alightweightvisiontransformer networkforidentificationofplantdiseases.FrontiersinPlantScience, 14, 2023.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification TrIncNet:alightweightvisiontransformer networkforidentificationofplantdiseases.FrontiersinPlantScience, 14, 2023
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:51.284762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a39efd9c-3f4c-46bb-9183-b1126700440f · outbound
This paper cites For- merLeaf: An efficient vision transformer for cassava leaf disease detection.Computers and Electronics in Agriculture, 204:107518, 2023.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification For- merLeaf: An efficient vision transformer for cassava leaf disease detection.Computers and Electronics in Agriculture, 204:107518, 2023
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:50.824753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c120ddca-375c-4a90-8d1f-9550c11ce7ff · outbound
This paper cites A novel hierarchical framework for plant leaf disease detection using residual vision transformer.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification A novel hierarchical framework for plant leaf disease detection using residual vision transformer
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:50.395142Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 25ac9d8a-de3b-462a-9611-eaacaf2b4b69 · outbound
This paper cites PMVT: a lightweight vision transformer for plant disease identificationonmobiledevices.FrontiersinPlantScience,14,2023.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification PMVT: a lightweight vision transformer for plant disease identificationonmobiledevices.FrontiersinPlantScience,14,2023
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:50.033514Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1c42c3fd-f97f-441f-af89-839964cf187d · outbound
This paper cites Resnet50.
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:49.224755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation fb121fe1-ee47-4996-ba19-ab233c1a9331 · outbound
This paper cites DenseNet: Implementing Efficient ConvNet Descriptor Pyramids.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification DenseNet: Implementing Efficient ConvNet Descriptor Pyramids
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:48:43.516593Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8728242-370a-410f-9f45-81dd5c654d8f · outbound
This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:48:43.654758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5075056-56d3-46d1-9a1c-84469da28dc8 · outbound
This paper cites Machineunlearning: Solutions and challenges.IEEE Transactions on Emerging Topics in Computational Intelligence, 8(3):2150–2168, 2024.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Machineunlearning: Solutions and challenges.IEEE Transactions on Emerging Topics in Computational Intelligence, 8(3):2150–2168, 2024
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:48.774759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 55e74bb9-ae29-46a7-bdde-d1244b9d6d71 · outbound
This paper cites An overview of machine unlearning.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification An overview of machine unlearning
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:48.294878Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 40de5051-b376-4410-ad0b-28d65a2188a4 · outbound
This paper cites Machine unlearning.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Machine unlearning
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:47.895165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e926e5bf-9829-490b-9e32-f12f23873f03 · outbound
This paper cites Towards making systems forget with machine unlearning.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Towards making systems forget with machine unlearning
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:47.539562Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d66ed039-a273-41fd-84bb-881607f7c0d9 · outbound
This paper cites Amnesiac ma- chine learning.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Amnesiac ma- chine learning
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:47.198224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 119a2eb3-c69f-4ee2-84f3-e33518bc1c54 · outbound
This paper cites Eternal sunshine of the spotless net: Selective forgetting in deep networks.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Eternal sunshine of the spotless net: Selective forgetting in deep networks
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:48:44.794750Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 061ef7a6-c120-435d-a384-a6d051b24680 · outbound
This paper cites Certified Data Removal from Machine Learning Models.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Certified Data Removal from Machine Learning Models
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:48:44.894752Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dfdd4e07-abb5-4092-819a-a722e06b86fa · outbound
This paper cites Towards unbounded machine unlearning.Advances in neural information processing systems, 36:1957–1987, 2023.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Towards unbounded machine unlearning.Advances in neural information processing systems, 36:1957–1987, 2023
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:46.864396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2ae81e30-beec-4f90-8104-90c40b1b8a1c · outbound
This paper cites an unresolved cited work.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-08-04T23:48:46.489384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2eb7f434-cf7b-4b29-8aa4-df659d997b92 · outbound
This paper cites Labelimg.https://github.com/tzutalin/labelImg, 2019.
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification Labelimg.https://github.com/tzutalin/labelImg, 2019
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T23:48:46.304994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
No inbound Pith citation observations are available.