Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:20:39.023682Z
Paper Citation Record · LEDGER
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model
As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2501.08878.
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 2026-08-18T06:34:40.430872+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
52 of 52 outbound references displayed
- verified exact2
- verified fuzzy37
- unresolved13
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ab595c48-d646-4c79-9ba8-88a8f8cbd2ab · outbound
This paper cites Achille, T.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Achille, T
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:40.063267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation be40b0d0-5304-4aa6-9732-a8c5a8c67389 · outbound
This paper cites Uncertainty-based continual learning with adaptive regularization.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Uncertainty-based continual learning with adaptive regularization
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:40.041765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6e9e7b44-d890-4319-8741-cb65c9402869 · outbound
This paper cites Rainbow memory: Continual learning with a memory of diverse samples.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Rainbow memory: Continual learning with a memory of diverse samples
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:40.020521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7803d094-c71d-4ac6-9aff-578c846e3d33 · outbound
This paper cites Online continual learning on a contaminated data stream with blurry task boundaries.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Online continual learning on a contaminated data stream with blurry task boundaries
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:40.002238Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0f81d19a-88c8-47af-922a-ef68579a8247 · outbound
This paper cites Dark experience for general continual learning: a strong, simple baseline.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Dark experience for general continual learning: a strong, simple baseline
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.985618Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a56f98be-8b20-42b8-9b5c-7f80f14232a6 · outbound
This paper cites Co2l: Contrastive continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Co2l: Contrastive continual learning
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.970125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 886dd594-a6b3-48d3-ac77-6dd2e245fb0d · outbound
This paper cites On Tiny Episodic Memories in Continual Learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model On Tiny Episodic Memories in Continual Learning
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.762971Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6b5eedb-22d0-4cb9-98c9-52bdc4f0ec54 · outbound
This paper cites Cortes, X.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Cortes, X
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.954670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4270c64e-2076-472c-b42f-4adef5aa7db5 · outbound
This paper cites Flattening sharpness for dynamic gradient projection memory benefits continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Flattening sharpness for dynamic gradient projection memory benefits continual learning
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.936419Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 422465b6-1975-4d9e-9e21-01507d2852a0 · outbound
This paper cites Kernel continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Kernel continual learning
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.920286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 67ff4fbe-b9cb-4de3-ae4b-e43bf1a97e3f · outbound
This paper cites Loss of plasticity in deep continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Loss of plasticity in deep continual learning
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.899527Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0ea1c13a-6208-4e94-8d2e-ff22f89f044f · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.787828Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0592d4db-afce-4497-a80a-75b655577998 · outbound
This paper cites Dytox: Transformers for continual learning with dynamic token expansion.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Dytox: Transformers for continual learning with dynamic token expansion
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.881834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 402e9ddb-a24e-4449-ac44-a039ef5354e2 · outbound
This paper cites Goodfellow, J.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Goodfellow, J
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.863235Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9f876326-762c-400a-b377-6b060c923807 · outbound
This paper cites Knowledge distillation: A survey.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Knowledge distillation: A survey
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.846204Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c3608c62-7e79-48cd-aeca-c45945883fbd · outbound
This paper cites Not just selection, but exploration: Online class-incremental continual learning via dual view consistency.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Not just selection, but exploration: Online class-incremental continual learning via dual view consistency
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.828147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 48bb0490-362a-429a-9896-7086ebb45e1b · outbound
This paper cites Online continual learning through mutual information maximization.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Online continual learning through mutual information maximization
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.805508Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 299ae2b0-c4fe-4508-8381-9a7dd62257e1 · outbound
This paper cites Distilling the Knowledge in a Neural Network.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Distilling the Knowledge in a Neural Network
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.823772Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 177b8cb2-1001-4979-9ebd-9bfa957134e7 · outbound
This paper cites Compacting, picking and growing for unforgetting continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Compacting, picking and growing for unforgetting continual learning
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.786008Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f645eb07-f879-4e79-a4ae-2b53a06b3435 · outbound
This paper cites Non-exemplar online class-incremental continual learning via dual-prototype self-augment and refinement.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Non-exemplar online class-incremental continual learning via dual-prototype self-augment and refinement
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.768504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 24f6ce5f-f90c-44da-89e1-cf2678ee8612 · outbound
This paper cites Npcl: Neural processes for uncertainty-aware continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Npcl: Neural processes for uncertainty-aware continual learning
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.750202Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 17b0c658-03c5-4689-81f8-5088b17a615b · outbound
This paper cites Generating instance-level prompts for rehearsal-free continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Generating instance-level prompts for rehearsal-free continual learning
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.727186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 856cb201-f963-4588-be4e-372eda8629b1 · outbound
This paper cites Forget-free continual learning with winning subnetworks.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Forget-free continual learning with winning subnetworks
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.703492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f32f5464-c3ee-47f4-b680-6e6cbdc5ba0f · outbound
This paper cites Measuring catastrophic forgetting in neural networks.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Measuring catastrophic forgetting in neural networks
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.685109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 68dd06a8-85c4-46ae-9178-321055c4f44f · outbound
This paper cites Sddgr: Stable diffusion-based deep generative replay for class incremental object detection.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Sddgr: Stable diffusion-based deep generative replay for class incremental object detection
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.668092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a8c17d98-72c7-4a6a-abd7-4f1b6c7e24d2 · outbound
This paper cites Auto-Encoding Variational Bayes.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Auto-Encoding Variational Bayes
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.867860Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7245ab07-80f7-48aa-ae52-678767eef2d2 · outbound
This paper cites Learning multiple layers of features from tiny images.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Learning multiple layers of features from tiny images
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.652810Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9c4d9471-fe2c-4e7a-9c1e-70ca75bcfde8 · outbound
This paper cites Tiny image Net visual recognition challenge.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Tiny image Net visual recognition challenge
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.636132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ec53eb2d-2eff-4690-8ac7-90d55a11f1b4 · outbound
This paper cites Li and D.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Li and D
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.621037Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a50799c3-c9e0-42e4-bcd1-db28db99fc81 · outbound
This paper cites Gradient episodic memory for continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Gradient episodic memory for continual learning
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.603713Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f5723e87-4dcf-4949-8c6c-51e399cd4c0f · outbound
This paper cites an unresolved cited work.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Unresolved cited work
Reference 31
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T20:20:39.586532Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 16f665d2-b074-4d99-bd17-39d1d88b35db · outbound
This paper cites McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, and Anton van den Hengel.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, and Anton van den Hengel
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.570107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4a3c24cd-f6ec-4e6c-b12b-d8ab3939731d · outbound
This paper cites Semantic Residual Prompts for Continual Learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Semantic Residual Prompts for Continual Learning
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T20:20:39.204648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2c061209-0e55-4cff-9458-62b21e21f43a · outbound
This paper cites Variational Continual Learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Variational Continual Learning
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.911959Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43f43e51-e996-4799-8c55-133550d9c5f6 · outbound
This paper cites an unresolved cited work.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Unresolved cited work
Reference 35
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T20:20:39.554171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fc642ca5-767d-49b7-aff9-cd4dcf76e9c2 · outbound
This paper cites Polikar, L.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Polikar, L
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.536223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 18a858b2-de7f-4dab-856b-2308f94a2200 · outbound
This paper cites Lifelong Generative Modeling.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Lifelong Generative Modeling
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T20:20:39.158664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5fe8699a-f3e1-4397-943e-0b63f2965bde · outbound
This paper cites iCaRL : Incremental classifier and representation learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model iCaRL : Incremental classifier and representation learning
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.518727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation eb3ba633-f4d3-492c-ac56-5a74d845a374 · outbound
This paper cites an unresolved cited work.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Unresolved cited work
Reference 39
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T20:20:39.497901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0c0aef99-8148-418f-bf65-3d04c0440552 · outbound
This paper cites Online structured L aplace approximations for overcoming catastrophic forgetting.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Online structured L aplace approximations for overcoming catastrophic forgetting
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.478725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9e1e833f-bb08-44c8-ae12-1e9a325b97f0 · outbound
This paper cites Progressive Neural Networks.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Progressive Neural Networks
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.953119Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 373654e3-f998-44ce-bcab-e0e21e19ff30 · outbound
This paper cites Continual learning via bit-level information preserving.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Continual learning via bit-level information preserving
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.457859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b598d235-8d17-40ad-99d0-61f06d9dafc9 · outbound
This paper cites an unresolved cited work.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T20:20:39.439468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ae3294f4-ceef-458e-8bc6-19f73588eca1 · outbound
This paper cites Gcr: Gradient coreset based replay buffer selection for continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Gcr: Gradient coreset based replay buffer selection for continual learning
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.421891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8b0d7f2c-5c27-449a-8c26-594dbb245fdf · outbound
This paper cites Efficient feature transformations for discriminative and generative continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Efficient feature transformations for discriminative and generative continual learning
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.403707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a332aaa9-47be-4c20-8fad-604df18a768c · outbound
This paper cites Training networks in null space of feature covariance for continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Training networks in null space of feature covariance for continual learning
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.385149Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b644440e-a5c3-4dcf-bb0f-b87ef46fc9b9 · outbound
This paper cites A Unified and General Framework for Continual Learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model A Unified and General Framework for Continual Learning
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.988078Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c40d900b-bff8-45cc-b794-4766a16870b5 · outbound
This paper cites BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:20:38.993578Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29ad6371-87cd-4f9d-8d45-bfd0b422b043 · outbound
This paper cites Meta-attention for vit-backed continual learning.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Meta-attention for vit-backed continual learning
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.367059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8efa32e0-8cbd-4c81-bc61-7128e0ad167b · outbound
This paper cites Boosting continual learning of vision-language models via mixture-of-experts adapters.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Boosting continual learning of vision-language models via mixture-of-experts adapters
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:20:39.348430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c1c0ed7c-6eba-46d5-8454-f7505401bbb0 · outbound
This paper cites an unresolved cited work.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T20:20:39.331369Z
Source-reported events for the cited work
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Observation 93d35d33-7d43-4a74-83ca-bc67a3cb0263 · outbound
This paper cites Online incremental feature learning with denoising autoencoders.
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model Online incremental feature learning with denoising autoencoders
Reference 52
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- raw_fallback, observed 2026-08-10T20:20:39.312027Z
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
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