Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:43:24.478182Z
Paper Citation Record · LEDGER
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds
As of 20 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2505.02972.
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 2026-08-20T06:33:59.587034+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
54 of 54 outbound references displayed
- verified exact5
- verified fuzzy31
- unresolved18
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 13a8c89b-efec-43fd-b8b2-dd8fd99ec6f9 · outbound
This paper cites write newline.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds write newline
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:23.822283Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 716de14d-d5d5-4830-b305-4675966d0c31 · outbound
This paper cites (2008), Optimization algorithms on matrix manifolds\/ , Princeton University Press.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2008), Optimization algorithms on matrix manifolds\/ , Princeton University Press
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.911554Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cad3a091-5d52-4b65-99c5-e03f9a367be0 · outbound
This paper cites L., et al.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds L., et al
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.897782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1a375ba7-4999-4328-9b80-2b396e58c1ba · outbound
This paper cites (2021), Predicting with proxies: Transfer learning in high dimension, Management Science\/ , 67, 2964--2984.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2021), Predicting with proxies: Transfer learning in high dimension, Management Science\/ , 67, 2964--2984
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.884133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1e5d1660-d832-4d45-8466-3d0f1a2069fc · outbound
This paper cites (2000), A model of inductive bias learning, Journal of artificial intelligence research\/ , 12, 149--198.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2000), A model of inductive bias learning, Journal of artificial intelligence research\/ , 12, 149--198
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.870587Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cf568c04-54ea-41ef-ac4a-ea915c8d724c · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:26.857382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b99baff9-d50a-46ba-9fa2-e149a16b8bf7 · outbound
This paper cites Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-16T00:43:24.886122Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 44ea402a-5733-4599-b22d-eb3832d4514c · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:26.782861Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5ff563fd-b8cc-466e-8bfe-6f66a4e005d8 · outbound
This paper cites (2021), Exploiting shared representations for personalized federated learning, in International conference on machine learning\/ , PMLR.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2021), Exploiting shared representations for personalized federated learning, in International conference on machine learning\/ , PMLR
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.642317Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f5b3cd73-e337-4d7c-b7d3-bc707c50a015 · outbound
This paper cites (2008), Learning from Multiple Sources.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2008), Learning from Multiple Sources
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.575582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8d78efcf-edd6-4e67-8468-a0dda085ce47 · outbound
This paper cites (2020), The advantage of conditional meta-learning for biased regularization and fine tuning, Advances in Neural Information Processing Systems\/ , 33, 964--974.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2020), The advantage of conditional meta-learning for biased regularization and fine tuning, Advances in Neural Information Processing Systems\/ , 33, 964--974
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.549455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5a2a65d1-b994-4b07-ac8d-df66d2b821b3 · outbound
This paper cites (2022), Learning tensor representations for meta-learning, in International Conference on Artificial Intelligence and Statistics\/ , PMLR.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2022), Learning tensor representations for meta-learning, in International Conference on Artificial Intelligence and Statistics\/ , PMLR
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.516847Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation afebe91e-4e87-4f95-9b97-608c1cff40f2 · outbound
This paper cites (2014), Decaf: A deep convolutional activation feature for generic visual recognition, in International conference on machine learning\/ , PMLR.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2014), Decaf: A deep convolutional activation feature for generic visual recognition, in International conference on machine learning\/ , PMLR
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.482973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7f132ba7-da4a-403e-a3e6-c694649c6af6 · outbound
This paper cites Few-Shot Learning via Learning the Representation, Provably.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Few-Shot Learning via Learning the Representation, Provably
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:23.927140Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97371733-0b5d-42f3-a10c-bca26bb974e5 · outbound
This paper cites and Wang, K.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds and Wang, K
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.461603Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9939a250-91f4-4a05-9f21-d414f7bfd93c · outbound
This paper cites C., Feldman, V., Hu, L., and Talwar, K.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds C., Feldman, V., Hu, L., and Talwar, K
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.427742Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0f3f57c1-f3ed-4c31-ac55-1a34dbc7fae4 · outbound
This paper cites (2019), Scaling and benchmarking self-supervised visual representation learning, in Proceedings of the ieee/cvf International Conference on computer vision\/.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2019), Scaling and benchmarking self-supervised visual representation learning, in Proceedings of the ieee/cvf International Conference on computer vision\/
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.406534Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b79fdecf-812e-4aea-9447-ab7473363f58 · outbound
This paper cites Robust angle-based transfer learning in high dimensions.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Robust angle-based transfer learning in high dimensions
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:23.976781Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49485216-3f63-4a0b-b8c2-a7cc6c4e1b7e · outbound
This paper cites H., and Duan, R.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds H., and Duan, R
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.392951Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e69c0ddb-fe3d-491e-ab3b-e80d73b279a5 · outbound
This paper cites Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:24.137177Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f0e46423-0d53-486c-a528-b4d6504cf29b · outbound
This paper cites (2022), Multi-task manifold learning for small sample size datasets, Neurocomputing\/ , 473, 138--157.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2022), Multi-task manifold learning for small sample size datasets, Neurocomputing\/ , 473, 138--157
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.222326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 195bc78b-8feb-4d9d-89b6-a460b588cc44 · outbound
This paper cites (2010), A dirty model for multi-task learning, Advances in neural information processing systems\/ , 23.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2010), A dirty model for multi-task learning, Advances in neural information processing systems\/ , 23
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.109624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 6cccfd9e-a71d-4a1d-b16b-23d4de70fe41 · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 23
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:26.095512Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3f3d246a-186c-4263-ac58-99358bdcdba4 · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 24
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:26.082231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fa41947d-ae78-42f3-8fb0-02f3e747a1e1 · outbound
This paper cites (2020), On the sample complexity of adversarial multi-source pac learning, in International Conference on Machine Learning\/ , PMLR.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2020), On the sample complexity of adversarial multi-source pac learning, in International Conference on Machine Learning\/ , PMLR
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.067957Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0ec92a89-0ad8-448a-a82c-398e0891c86d · outbound
This paper cites and Orabona, F.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds and Orabona, F
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.054901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 94e0446f-35d7-413a-a029-af2d8320f738 · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 27
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:26.041767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7346057f-2fb3-43d6-90be-97a3913fcf52 · outbound
This paper cites (2023), Targeting underrepresented populations in precision medicine: A federated transfer learning approach, The Annals of Applied Statistics\/ , 17, 2970--2992.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2023), Targeting underrepresented populations in precision medicine: A federated transfer learning approach, The Annals of Applied Statistics\/ , 17, 2970--2992
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.025858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3cb3980b-2770-4542-b0bf-5efdc03fdae6 · outbound
This paper cites T., and Li, H.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds T., and Li, H
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:26.012547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0b3befa7-ea66-4ac4-81da-fbbdee5aff6d · outbound
This paper cites On Hypothesis Transfer Learning of Functional Linear Models.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds On Hypothesis Transfer Learning of Functional Linear Models
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:24.180269Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7e12fd77-236f-4f92-bb39-82b31232c137 · outbound
This paper cites Taking Advantage of Sparsity in Multi-Task Learning.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Taking Advantage of Sparsity in Multi-Task Learning
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:24.185010Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ccaefc0-2658-4e47-a966-def0747a4d91 · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 32
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:25.998460Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e9e862a8-acea-4637-a893-f1e21165d310 · outbound
This paper cites (2016), The benefit of multitask representation learning, Journal of Machine Learning Research\/ , 17, 1--32.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2016), The benefit of multitask representation learning, Journal of Machine Learning Research\/ , 17, 1--32
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.984205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b34a672f-ef8d-48e8-8b9b-d5d2626cecb6 · outbound
This paper cites (2019), Pytorch: An imperative style, high-performance deep learning library, Advances in neural information processing systems\/ , 32.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2019), Pytorch: An imperative style, high-performance deep learning library, Advances in neural information processing systems\/ , 32
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.793039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 29934f59-e947-454a-9025-d5010a76e29c · outbound
This paper cites (2018), Do Outliers Ruin Collaboration? in International Conference on Machine Learning\/ , PMLR.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2018), Do Outliers Ruin Collaboration? in International Conference on Machine Learning\/ , PMLR
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.541557Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 23e538a1-6fbf-4209-bfef-a15b6c1c198e · outbound
This paper cites Learning Discrete Distributions from Untrusted Batches.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Learning Discrete Distributions from Untrusted Batches
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-08-16T00:43:24.795010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d12e86c4-aa07-44f7-b8b7-f4ec97083e52 · outbound
This paper cites (2019), Transfusion: Understanding transfer learning for medical imaging, Advances in neural information processing systems\/ , 32.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2019), Transfusion: Understanding transfer learning for medical imaging, Advances in neural information processing systems\/ , 32
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.497833Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5cb63af2-c004-469c-8a44-866fb15d4546 · outbound
This paper cites (2022), Transfer learning via representation learning, in Federated and Transfer Learning\/ , Springer, 233--257.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2022), Transfer learning via representation learning, in Federated and Transfer Learning\/ , Springer, 233--257
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.484680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation bb805b31-eabb-4d39-a953-8aa7b42a5587 · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 39
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:25.472228Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b7a20eb2-e83a-40e8-8761-8f6afe2eeb41 · outbound
This paper cites K., Jain, P., Netrapalli, P., and Oh, S.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds K., Jain, P., Netrapalli, P., and Oh, S
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.459775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8f584f67-5c4d-4784-b804-974c47b1c4de · outbound
This paper cites and Feng, Y.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds and Feng, Y
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.446473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation de950419-6017-4188-8ef9-951a68030e86 · outbound
This paper cites Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:24.420834Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 613161b7-9be9-4128-962e-6ec4d8e4fd5d · outbound
This paper cites (2022), Unsupervised multi-task and transfer learning on gaussian mixture models, arXiv preprint arXiv:2209.15224\/.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2022), Unsupervised multi-task and transfer learning on gaussian mixture models, arXiv preprint arXiv:2209.15224\/
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:24.425783Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f18f902-003d-4d94-9204-1bb880b1e54a · outbound
This paper cites (2021), Provable meta-learning of linear representations, in International Conference on Machine Learning\/ , PMLR.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2021), Provable meta-learning of linear representations, in International Conference on Machine Learning\/ , PMLR
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.432715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 647c552f-57d3-4956-9213-aeacc8749754 · outbound
This paper cites (2020), On the theory of transfer learning: The importance of task diversity, Advances in neural information processing systems\/ , 33, 7852--7862.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2020), On the theory of transfer learning: The importance of task diversity, Advances in neural information processing systems\/ , 33, 7852--7862
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.374560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 87b30182-a6df-41ac-9b59-8cf7393ae512 · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:25.235186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7a61d678-20dc-478b-8f99-524cff820ccc · outbound
This paper cites Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:43:24.445550Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 008f8fe8-2e23-4aa1-a835-60f94ab11a2d · outbound
This paper cites M., Wilson, T.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds M., Wilson, T
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.114484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation bd3e5a34-36ad-428b-9c04-1a587678eddf · outbound
This paper cites Multitask Learning and Bandits via Robust Statistics.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Multitask Learning and Bandits via Robust Statistics
Reference 49
- Resolution
- verified exact
- local_arxiv, observed 2026-08-16T00:43:24.675930Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5c723c4d-c837-4265-9d8e-a034844b771f · outbound
This paper cites and Yang, Q.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds and Yang, Q
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:25.099597Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5b532b74-699c-45ee-afb4-448c2badf66d · outbound
This paper cites an unresolved cited work.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:43:25.084673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ccf76da2-d004-4646-88c6-ab434b496893 · outbound
This paper cites SOFARI: High-Dimensional Manifold-Based Inference.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds SOFARI: High-Dimensional Manifold-Based Inference
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-08-16T00:43:24.655932Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c8c5203d-8ca9-43e2-b236-da0e549d6f0a · outbound
This paper cites Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-08-16T00:43:24.560639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation dba8f54e-ee9f-4b06-91b5-f66d4adfdc21 · outbound
This paper cites (2024), Doubly robust augmented model accuracy transfer inference with high dimensional features, Journal of the American Statistical Association\/ , 1--26.
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds (2024), Doubly robust augmented model accuracy transfer inference with high dimensional features, Journal of the American Statistical Association\/ , 1--26
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:43:24.989381Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.