Expert Routing with Synthetic Data for Continual Learning | Paper Citation Record

Observation e7c7f8b0-f5c7-4765-88ae-6790361b4b52 · outbound

This paper cites Unsupervised domain clusters in pretrained language models.

Expert Routing with Synthetic Data for Continual Learning Unsupervised domain clusters in pretrained language models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.000021Z

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Observation b4aba505-b3f9-4377-947f-7136b70c8bfb · outbound

This paper cites Expert gate: Lifelong learning with a network of experts.

Expert Routing with Synthetic Data for Continual Learning Expert gate: Lifelong learning with a network of experts

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.005390Z

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Observation d7ec4dc5-293a-4277-95b4-c03120246ab2 · outbound

This paper cites Learning to Route for Dynamic Adapter Composition in Continual Learning with Language Models.

Expert Routing with Synthetic Data for Continual Learning Learning to Route for Dynamic Adapter Composition in Continual Learning with Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.010226Z

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Observation 2c4c12a1-62fc-481f-bcef-384bb95f873e · outbound

This paper cites Don’t generate me: Training differentially private generative models with sinkhorn divergence.Advances in Neural Information Processing Systems, 34:12480–12492, 2021.

Expert Routing with Synthetic Data for Continual Learning Don’t generate me: Training differentially private generative models with sinkhorn divergence.Advances in Neural Information Processing Systems, 34:12480–12492, 2021

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.699451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f5870fe4-093e-41ab-baa4-5bfff76479a5 · outbound

This paper cites Analysis of the isic image datasets: Usage, benchmarks and recommendations.Medical image analysis, 75:102305, 2022.

Expert Routing with Synthetic Data for Continual Learning Analysis of the isic image datasets: Usage, benchmarks and recommendations.Medical image analysis, 75:102305, 2022

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.682101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b70e2dc0-fc19-4844-b174-880bc4a608da · outbound

This paper cites Efficient lifelong learning with a-GEM.

Expert Routing with Synthetic Data for Continual Learning Efficient lifelong learning with a-GEM

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.025811Z

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Observation 914f8e28-f326-4f33-bddf-6f76b35e788e · outbound

This paper cites On Tiny Episodic Memories in Continual Learning.

Expert Routing with Synthetic Data for Continual Learning On Tiny Episodic Memories in Continual Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.031100Z

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Observation e8217388-3bfb-4d5b-b299-f0ccbfa88c15 · outbound

This paper cites Synthetic data in machine learning for medicine and healthcare.Nature Biomedical Engineering, 5 (6):493–497, 2021.

Expert Routing with Synthetic Data for Continual Learning Synthetic data in machine learning for medicine and healthcare.Nature Biomedical Engineering, 5 (6):493–497, 2021

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.655482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7764e793-5be8-4160-925e-4e08ae5ad88a · outbound

This paper cites Quac: Question answering in context.

Expert Routing with Synthetic Data for Continual Learning Quac: Question answering in context

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.636267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ea3dac1a-fb5c-4f69-9cdc-40ac09eaac60 · outbound

This paper cites an unresolved cited work.

Expert Routing with Synthetic Data for Continual Learning Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:57:32.618090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6c1a8b83-66e1-4cc7-a057-e81bb29d1af3 · outbound

This paper cites Disparities in dermatology ai performance on a diverse, curated clinical image set.Science advances, 8(31): eabq6147, 2022.

Expert Routing with Synthetic Data for Continual Learning Disparities in dermatology ai performance on a diverse, curated clinical image set.Science advances, 8(31): eabq6147, 2022

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.601558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 85d737a2-4e2c-4442-bb05-d89814523d6f · outbound

This paper cites A continual learning survey: Defying forgetting in classification tasks.IEEE transactions on pattern analysis and machine intelligence, 44(7):3366–3385, 2021.

Expert Routing with Synthetic Data for Continual Learning A continual learning survey: Defying forgetting in classification tasks.IEEE transactions on pattern analysis and machine intelligence, 44(7):3366–3385, 2021

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.585814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d4456736-5eb5-41f1-b1b6-322c688050eb · outbound

This paper cites Episodic memory in lifelong language learning.Advances in Neural Information Processing Systems, 32, 2019.

Expert Routing with Synthetic Data for Continual Learning Episodic memory in lifelong language learning.Advances in Neural Information Processing Systems, 32, 2019

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.570382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 09aaf0cc-4c89-4e80-b66b-d570c2d0cac5 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Expert Routing with Synthetic Data for Continual Learning Imagenet: A large-scale hierarchical image database

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.064051Z

Source-reported events for the cited work

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Observation 294dee90-dea2-43d1-91f5-02e4989ec829 · outbound

This paper cites Continual learning beyond a single model.

Expert Routing with Synthetic Data for Continual Learning Continual learning beyond a single model

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.541385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 00f13715-a822-4439-976b-dfc13e64e10c · outbound

This paper cites Differentially Private Diffusion Models.

Expert Routing with Synthetic Data for Continual Learning Differentially Private Diffusion Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.072744Z

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Observation 93c246cf-03b2-4de1-a8ee-65b5f732213b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Expert Routing with Synthetic Data for Continual Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.077846Z

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Observation 0c704528-f45b-4450-b07d-8e4fc7d4229c · outbound

This paper cites Overcoming barriers to data sharing with medical image generation: a comprehensive evaluation.NPJ digital medicine, 4(1):141, 2021.

Expert Routing with Synthetic Data for Continual Learning Overcoming barriers to data sharing with medical image generation: a comprehensive evaluation.NPJ digital medicine, 4(1):141, 2021

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.525502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9ceff1ff-27fe-48c2-a13f-985b1fa083b9 · outbound

This paper cites Now Publishers Inc., 2014.

Expert Routing with Synthetic Data for Continual Learning Now Publishers Inc., 2014

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.509116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 699480e2-1278-4329-b18f-8721d6806348 · outbound

This paper cites Calibrating noise to sensitivity in private data analysis.

Expert Routing with Synthetic Data for Continual Learning Calibrating noise to sensitivity in private data analysis

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.493211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f6fefa10-aff7-45d1-a4b2-41667d4fed0a · outbound

This paper cites an unresolved cited work.

Expert Routing with Synthetic Data for Continual Learning Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:57:32.478109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2b790e95-3d70-4c37-b563-28cea737157d · outbound

This paper cites Catastrophic forgetting in connectionist networks.Trends in cognitive sciences, 3(4):128–135, 1999.

Expert Routing with Synthetic Data for Continual Learning Catastrophic forgetting in connectionist networks.Trends in cognitive sciences, 3(4):128–135, 1999

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.102267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c30a9af6-d6a5-40c1-86ae-8900ca2e8612 · outbound

This paper cites Domain adaptation for medical image analysis: a survey.IEEE Transactions on Biomedical Engineering, 69(3):1173–1185, 2021.

Expert Routing with Synthetic Data for Continual Learning Domain adaptation for medical image analysis: a survey.IEEE Transactions on Biomedical Engineering, 69(3):1173–1185, 2021

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.107021Z

Source-reported events for the cited work

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Observation 9e91b77e-a86e-4583-a6f8-5537b838d789 · outbound

This paper cites Improved schemes for episodic memory-based lifelong learning.Advances in Neural Information Processing Systems, 33:1023–1035, 2020.

Expert Routing with Synthetic Data for Continual Learning Improved schemes for episodic memory-based lifelong learning.Advances in Neural Information Processing Systems, 33:1023–1035, 2020

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.439876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 51e851a1-57b8-4c1f-9f20-895925d13bd4 · outbound

This paper cites Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning.Advances in Neural Information Processing Systems, 34:29335–29347, 2021.

Expert Routing with Synthetic Data for Continual Learning Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning.Advances in Neural Information Processing Systems, 34:29335–29347, 2021

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.421985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ca00f622-1e65-45c7-a57c-c4de43b6316a · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Expert Routing with Synthetic Data for Continual Learning LoRA: Low-Rank Adaptation of Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.121442Z

Source-reported events for the cited work

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Observation 0656dfe3-853c-4e07-8d05-097eed025ef3 · outbound

This paper cites Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension.

Expert Routing with Synthetic Data for Continual Learning Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.403289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b267bd63-c9ef-4846-9171-1d28ce71fd0b · outbound

This paper cites Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study.bmj, 376, 2022.

Expert Routing with Synthetic Data for Continual Learning Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study.bmj, 376, 2022

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.380638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 36f1bad6-57da-450f-a185-f0ba9e7d2592 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Expert Routing with Synthetic Data for Continual Learning Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.135592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2056012c-820f-4649-ba85-eab43551132f · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Expert Routing with Synthetic Data for Continual Learning Adam: A Method for Stochastic Optimization

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.140329Z

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Unavailable: canonical work link unavailable.

Observation 63a04f8c-0124-4b3c-8e6b-9e568224ff79 · outbound

This paper cites Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell.

Expert Routing with Synthetic Data for Continual Learning Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.145173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8a18f01-89e5-4b08-b39f-b946cdb53aaf · outbound

This paper cites Mixture of Experts Meets Prompt-Based Continual Learning.

Expert Routing with Synthetic Data for Continual Learning Mixture of Experts Meets Prompt-Based Continual Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.150082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f98b215c-432a-4681-be30-bbb5593bdada · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

Expert Routing with Synthetic Data for Continual Learning The power of scale for parameter-efficient prompt tuning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.154927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bacf0a96-80fb-41d9-a915-674c43a1aa8a · outbound

This paper cites Theory on Mixture-of-Experts in Continual Learning.

Expert Routing with Synthetic Data for Continual Learning Theory on Mixture-of-Experts in Continual Learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.159315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2816fd85-1ddf-4470-b92b-0e2227bcae64 · outbound

This paper cites Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting.

Expert Routing with Synthetic Data for Continual Learning Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.342404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2cdfd59c-3232-471d-9d40-2c81552a4ec4 · outbound

This paper cites Learning without forgetting.IEEE transactions on pattern analysis and machine intelligence, 40(12):2935–2947, 2017.

Expert Routing with Synthetic Data for Continual Learning Learning without forgetting.IEEE transactions on pattern analysis and machine intelligence, 40(12):2935–2947, 2017

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.168603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d590c6f-db44-4d2c-9d27-54918ebd35ca · outbound

This paper cites The clear benchmark: Continual learning on real-world imagery.

Expert Routing with Synthetic Data for Continual Learning The clear benchmark: Continual learning on real-world imagery

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.312991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 27466e0d-d195-49c3-9bb8-94f9be8a770e · outbound

This paper cites Core50: a new dataset and benchmark for continuous object recognition.

Expert Routing with Synthetic Data for Continual Learning Core50: a new dataset and benchmark for continuous object recognition

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.177422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47c7291e-f369-4b26-982b-54971d62edce · outbound

This paper cites Gradient episodic memory for continual learning.

Expert Routing with Synthetic Data for Continual Learning Gradient episodic memory for continual learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.181897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77e73637-e62c-4c3f-8a3b-132c29c9aa64 · outbound

This paper cites Decoupled Weight Decay Regularization.

Expert Routing with Synthetic Data for Continual Learning Decoupled Weight Decay Regularization

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.186164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb6f1dc6-1f5b-415a-9ce1-f40354fdeadc · outbound

This paper cites DP-LDMs: Differentially Private Latent Diffusion Models.

Expert Routing with Synthetic Data for Continual Learning DP-LDMs: Differentially Private Latent Diffusion Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.190933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e09d318a-92b7-4f51-8c67-afd8e12fa27d · outbound

This paper cites Modeling task relationships in multi-task learning with multi-gate mixture-of-experts.

Expert Routing with Synthetic Data for Continual Learning Modeling task relationships in multi-task learning with multi-gate mixture-of-experts

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.195753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4ce00fd-9b3e-4c35-9729-a86f33e806bd · outbound

This paper cites Catastrophic interference in connectionist networks: The sequential learning problem.

Expert Routing with Synthetic Data for Continual Learning Catastrophic interference in connectionist networks: The sequential learning problem

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.200258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d231e1ea-6f26-4f8e-87fe-936d1f822ffd · outbound

This paper cites An empirical investigation of the role of pre-training in lifelong learning.Journal of Machine Learning Research, 24(214):1–50, 2023.

Expert Routing with Synthetic Data for Continual Learning An empirical investigation of the role of pre-training in lifelong learning.Journal of Machine Learning Research, 24(214):1–50, 2023

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.243965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2659e6da-ac8c-4b43-9ede-0450c8a66fdf · outbound

This paper cites Pad-ufes-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones.Data in brief, 32:106221, 2020.

Expert Routing with Synthetic Data for Continual Learning Pad-ufes-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones.Data in brief, 32:106221, 2020

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.224125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2b9c76ff-412c-47db-a205-38ccd8f80098 · outbound

This paper cites Learning More Generalized Experts by Merging Experts in Mixture-of-Experts.

Expert Routing with Synthetic Data for Continual Learning Learning More Generalized Experts by Merging Experts in Mixture-of-Experts

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.214178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4884ffe6-2f9e-4ca4-808a-2e3aa69fc6e3 · outbound

This paper cites Moment matching for multi-source domain adaptation.

Expert Routing with Synthetic Data for Continual Learning Moment matching for multi-source domain adaptation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.203744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cb223e8b-26e0-4e32-a398-8010d70e1fc8 · outbound

This paper cites Can we trust deep learning based diagnosis? the impact of domain shift in chest radiograph classification.

Expert Routing with Synthetic Data for Continual Learning Can we trust deep learning based diagnosis? the impact of domain shift in chest radiograph classification

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.185249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ee4a2c01-1727-43ce-9e25-2aa7f296860d · outbound

This paper cites LFPT5: A unified framework for lifelong few-shot language learning based on prompt tuning of t5.

Expert Routing with Synthetic Data for Continual Learning LFPT5: A unified framework for lifelong few-shot language learning based on prompt tuning of t5

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.168116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c6f45dd2-ff33-4678-9dab-c49f21d8c77a · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.The Journal of Machine Learning Research, 21(1):5485–5551, 2020.

Expert Routing with Synthetic Data for Continual Learning Exploring the limits of transfer learning with a unified text-to-text transformer.The Journal of Machine Learning Research, 21(1):5485–5551, 2020

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.234524Z

Source-reported events for the cited work

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Observation ec8c3b1e-e913-428d-a92b-7440bdf4262e · outbound

This paper cites Squad: 100,000+ questions for machine comprehension of text.

Expert Routing with Synthetic Data for Continual Learning Squad: 100,000+ questions for machine comprehension of text

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.239336Z

Source-reported events for the cited work

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Observation 3a4ed309-0ffa-4484-a6a0-b59c3917156c · outbound

This paper cites High- resolution image synthesis with latent diffusion models.

Expert Routing with Synthetic Data for Continual Learning High- resolution image synthesis with latent diffusion models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.244277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62c38501-8b31-4da3-b3b9-58bcf45bb3a9 · outbound

This paper cites Divide and not forget: Ensemble of selectively trained experts in Continual Learning.

Expert Routing with Synthetic Data for Continual Learning Divide and not forget: Ensemble of selectively trained experts in Continual Learning

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.249346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a7bf659-9d31-4668-a24a-30cf736bb663 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Expert Routing with Synthetic Data for Continual Learning Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.253975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 577e4dfe-f952-4465-8bd5-535e77a250df · outbound

This paper cites Continual learning with deep generative replay.Advances in neural information processing systems, 30, 2017.

Expert Routing with Synthetic Data for Continual Learning Continual learning with deep generative replay.Advances in neural information processing systems, 30, 2017

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.259171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69828bf9-b98a-4cbf-9d1e-f1f83074768a · outbound

This paper cites Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA.

Expert Routing with Synthetic Data for Continual Learning Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.263942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a91e4a4b-cd1c-4b2f-bdf5-185faba174ff · outbound

This paper cites Coda-prompt: Continual de- composed attention-based prompting for rehearsal-free continual learning.

Expert Routing with Synthetic Data for Continual Learning Coda-prompt: Continual de- composed attention-based prompting for rehearsal-free continual learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.103281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5cdc4ca7-5f9f-4d93-ad84-976e4d51d465 · outbound

This paper cites An Introduction to Lifelong Supervised Learning.

Expert Routing with Synthetic Data for Continual Learning An Introduction to Lifelong Supervised Learning

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.274531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5a88997-c146-457c-b990-179a185027d4 · outbound

This paper cites {LAMAL}: {LA}nguage modeling is all you need for lifelong language learning.

Expert Routing with Synthetic Data for Continual Learning {LAMAL}: {LA}nguage modeling is all you need for lifelong language learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.083615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 955e76e9-b0c0-4b3f-9935-b67da6d15329 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, 5(1):1–9, 2018.

Expert Routing with Synthetic Data for Continual Learning The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, 5(1):1–9, 2018

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.285323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6a23436-a6b7-4456-bd9f-ffe7227d6ec3 · outbound

This paper cites an unresolved cited work.

Expert Routing with Synthetic Data for Continual Learning Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:57:32.056162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bb240881-11eb-43f7-87ea-4e4fb159e207 · outbound

This paper cites Three scenarios for continual learning.

Expert Routing with Synthetic Data for Continual Learning Three scenarios for continual learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.295563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b5c6ec2-06a9-4b8e-8a69-580f9f4a5164 · outbound

This paper cites Visualizing data using t-sne.Journal of machine learning research, 9(11), 2008.

Expert Routing with Synthetic Data for Continual Learning Visualizing data using t-sne.Journal of machine learning research, 9(11), 2008

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.300522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87588a2c-8496-4e7e-99c1-39458d28e27f · outbound

This paper cites Development and multi-site external validation of a generalizable risk prediction model for bipolar disorder.medRxiv, pages 2023–02, 2023.

Expert Routing with Synthetic Data for Continual Learning Development and multi-site external validation of a generalizable risk prediction model for bipolar disorder.medRxiv, pages 2023–02, 2023

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:32.027793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 37dc7dec-a101-4c57-a3fe-f8d924126516 · outbound

This paper cites Coscl: Cooperation of small continual learners is stronger than a big one.

Expert Routing with Synthetic Data for Continual Learning Coscl: Cooperation of small continual learners is stronger than a big one

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.310123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 778752bd-6d74-4c68-9c57-e97f616cc089 · outbound

This paper cites Hierarchical decomposition of prompt-based continual learning: Rethinking obscured sub-optimality.Advances in Neural Information Processing Systems, 36, 2024.

Expert Routing with Synthetic Data for Continual Learning Hierarchical decomposition of prompt-based continual learning: Rethinking obscured sub-optimality.Advances in Neural Information Processing Systems, 36, 2024

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:31.993906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ebbf925c-6fe5-49a2-bbad-6bb68f93fd31 · outbound

This paper cites S-prompts learning with pre-trained transformers: An occam’s razor for domain incremental learning.

Expert Routing with Synthetic Data for Continual Learning S-prompts learning with pre-trained transformers: An occam’s razor for domain incremental learning

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:31.973117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6ee5b627-a790-4114-83e2-5aaa077b34eb · outbound

This paper cites Dualprompt: Complementary prompting for rehearsal-free continual learning.

Expert Routing with Synthetic Data for Continual Learning Dualprompt: Complementary prompting for rehearsal-free continual learning

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.324695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe7ef7a3-e138-4adc-bea6-b4fd77ece1b7 · outbound

This paper cites Learning to prompt for continual learning.

Expert Routing with Synthetic Data for Continual Learning Learning to prompt for continual learning

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.333192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62fb31f0-7e1f-457f-a215-ad13793616ab · outbound

This paper cites Efficient meta lifelong-learning with limited memory.

Expert Routing with Synthetic Data for Continual Learning Efficient meta lifelong-learning with limited memory

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:31.929497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d6575dd5-b26c-4360-afe1-b7633744bf1e · outbound

This paper cites BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors.

Expert Routing with Synthetic Data for Continual Learning BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:57:31.485357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 33ae1996-2132-4d55-b067-3319dfaca1d2 · outbound

This paper cites Boosting continual learning of vision-language models via mixture-of-experts adapters.

Expert Routing with Synthetic Data for Continual Learning Boosting continual learning of vision-language models via mixture-of-experts adapters

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.348280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 820d1a40-6c7e-4b1f-81be-386c4b2d81a5 · outbound

This paper cites Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study.PLoS medicine, 15(11):e1002683, 2018.

Expert Routing with Synthetic Data for Continual Learning Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study.PLoS medicine, 15(11):e1002683, 2018

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.357172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3083eac-9018-4df9-94e6-eb8b7b2f644f · outbound

This paper cites Continual learning through synaptic intelligence.

Expert Routing with Synthetic Data for Continual Learning Continual learning through synaptic intelligence

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.362861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1eaa1cf-c5e1-4465-a000-e143b1a19a32 · outbound

This paper cites Continual Learning with Pre-Trained Models: A Survey.

Expert Routing with Synthetic Data for Continual Learning Continual Learning with Pre-Trained Models: A Survey

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T05:57:31.367933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdc13217-42ca-4434-bba6-2a158b922d02 · outbound

This paper cites Mixture-of-experts with expert choice routing.Advances in Neural Information Processing Systems, 35:7103–7114, 2022.

Expert Routing with Synthetic Data for Continual Learning Mixture-of-experts with expert choice routing.Advances in Neural Information Processing Systems, 35:7103–7114, 2022

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:31.877446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0d3b8093-3836-4ffb-8599-a48003d1c6d6 · outbound

This paper cites an unresolved cited work.

Expert Routing with Synthetic Data for Continual Learning Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:57:31.859336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 56c10383-b2df-48c4-aefe-99f146ccf794 · outbound

This paper cites an unresolved cited work.

Expert Routing with Synthetic Data for Continual Learning Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:57:31.840415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e88470f6-9a3d-4b99-8fab-13fe6c7621c4 · outbound

This paper cites an unresolved cited work.

Expert Routing with Synthetic Data for Continual Learning Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:57:31.821263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 97f84c41-11b6-4bf8-9eb6-46b25cc0d902 · outbound

This paper cites Generate article, question and answer.

Expert Routing with Synthetic Data for Continual Learning Generate article, question and answer

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:31.804847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 524ecbb5-830f-4310-9d72-6fdd610c7775 · outbound

This paper cites (2) In the original Generative Replay implementation, the generator is sequentially finetuned (in addition to the classifier) on each domain in the sequence.

Expert Routing with Synthetic Data for Continual Learning (2) In the original Generative Replay implementation, the generator is sequentially finetuned (in addition to the classifier) on each domain in the sequence

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:31.787122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8a11a4e6-c5da-4e7a-9540-806eb1401470 · outbound

This paper cites The BERT-base architecture has 12 Transformer layers, 12 self-attention heads, and 768 hidden dimensions (110M parameters).

Expert Routing with Synthetic Data for Continual Learning The BERT-base architecture has 12 Transformer layers, 12 self-attention heads, and 768 hidden dimensions (110M parameters)

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:57:31.769064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Reference resolution

Outbound references

Pith citing papers