Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T19:15:34.756343Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2508.13005.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T19:15:34.756343Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
46 of 46 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ac27ed92-a653-40d4-9396-223e66cce63e · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Memory aware synapses: Learning what (not) to forget
Reference 1
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Observation 6053a0f2-6646-447d-9c14-289cd446c137 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Make continual learning stronger via c-flat
Reference 2
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Observation 83b0ac65-1e94-4b16-839e-2a8a5d03253f · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Semi- supervised novelty detection.The Journal of Machine Learn- ing Research, 11:2973–3009, 2010
Reference 3
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Observation 34acb235-0773-4e25-a8c6-51363fcac204 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Dark experience for general continual learning: a strong, simple baseline
Reference 4
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Observation 7e6204ca-9863-4d4b-ac8c-dc642f2fdc17 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Open-set recognition with gaussian mixture variational autoencoders
Reference 5
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Observation 5c9d892f-e85e-45e5-9426-a085bbae92c0 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning On measuring the distance between histograms
Reference 6
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Observation 23bb8d77-ed16-41b7-8880-12d485bda701 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Novelty Detection via Contrastive Learning with Negative Data Augmentation
Reference 7
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Observation 2063f6a4-d868-4c66-adf3-33a9eee897c3 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Learning open set network with discriminative reciprocal points
Reference 8
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Observation 6dc50562-da45-4ec3-8893-c6d58b5c7797 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Is forgetting less a good inductive bias for forward transfer?
Reference 9
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Observation b2216ef0-cc0e-4328-8193-81a520bddcf4 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Imagenet: A large-scale hierarchical im- age database
Reference 10
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Observation 2420c93c-5446-4dce-8a52-ba67db2ad804 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Reducing network agnostophobia
Reference 11
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Observation 974f2f13-12c3-4fa0-9eda-6f54d9c2bd04 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Re- visiting deep ensemble for out-of-distribution detection: A loss landscape perspective
Reference 12
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Observation 8eccccf8-594e-48e7-b0b3-ec702fba8e3e · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Gen- erative openmax for multi-class open set classification
Reference 13
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Observation 58cd43b7-c19c-44f0-b5dc-632e43b104a3 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness
Reference 14
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Observation c7d64894-8bb3-49cf-b61f-d88df431a02f · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Learning a neural- network-based representation for open set recognition
Reference 15
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Observation 9f989af2-d131-4226-9973-3fabc1035774 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Learning a unified classifier incrementally via rebalancing
Reference 16
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Observation 65c20935-d075-4de1-b281-bcca7d7ff7c1 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Overcoming catastrophic forgetting for continual learning via model adaptation
Reference 17
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Observation 30b42798-63d9-4457-a948-9040d20dbbe4 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Compacting, picking and growing for unforgetting continual learning.Ad- vances in neural information processing systems , 32, 2019
Reference 18
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Observation f562e911-e054-4829-9fd6-9eabb53f6048 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Class- incremental learning by knowledge distillation with adaptive feature consolidation
Reference 19
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Observation 2684ecff-71bf-43dd-963a-6d685674f43b · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Large-scale video classification with convolutional neural networks
Reference 20
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Observation f59cc104-eeb8-484d-a9e9-d9560a955c40 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Overcoming catastrophic forgetting in neu- ral networks
Reference 21
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Observation bfdd6082-6da8-475b-bcab-44da84cbfba3 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Similarity of neural network represen- tations revisited
Reference 22
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Observation 86eae241-e3fd-4b53-838b-551341760df3 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Reference 23
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Observation d4d39c2c-5a3d-4d41-9de5-41ce249b5e8c · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Applications of machine learning to machine fault diagnosis: A review and roadmap.Mechanical Systems and Signal Processing, 138:106587, 2020
Reference 24
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Observation 5612c863-0ecd-4de3-b74c-21e1040ec7b3 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Con- trastive continual learning with importance sampling and prototype-instance relation distillation
Reference 25
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Observation 7fb4aa18-a42a-4543-af60-bd3277cd52fe · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Learn to grow: A continual structure learn- ing framework for overcoming catastrophic forgetting
Reference 26
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Observation f07fe84f-d4dc-4314-9170-e39a8671b10f · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Provable and Efficient Continual Representation Learning
Reference 27
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Observation b608b856-d9c4-49bb-b010-feab18a3b612 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Learning without forgetting
Reference 28
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Observation bac1d0c8-3f29-4f96-9846-ddc1655702aa · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Few-shot open-set recognition using meta- learning
Reference 29
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Observation d4973f6c-44d7-438d-87e6-798ca2b247ea · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Catastrophic inter- ference in connectionist networks: The sequential learning problem
Reference 30
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Observation 22c4f889-ca1b-4f9c-ac9f-32b186d1c635 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Class anchor clustering: A loss for distance- based open set recognition
Reference 31
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Observation 830929ec-8477-4a67-aa6b-e59b482f9706 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Open set learning with counterfac- tual images
Reference 32
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Observation fefe1c77-3297-40fb-a0b7-cb2473502b15 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning C2ae: Class conditioned auto-encoder for open-set recognition
Reference 33
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Observation f4a2b5a0-1472-4b20-92b6-c4dca41c26f5 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Generative-discriminative feature representations for open-set recognition
Reference 34
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Observation c9b53f35-e275-470d-a9d0-89c2513ee58c · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning A review of novelty detection
Reference 35
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Observation b0db3ab7-0720-490f-9289-20808c165084 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning icarl: Incremental classifier and representation learning
Reference 36
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Observation 39103b68-5dae-4686-a3bf-228b40113c77 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Overcoming catastrophic forgetting with hard attention to the task
Reference 37
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Observation d3ff99ed-789b-4a47-a1a8-487758aaba94 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Assessing The Importance Of Colours For CNNs In Object Recognition
Reference 38
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Observation 8c8a2993-bc7b-49bf-9754-b62244c717ef · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Dice: Leveraging sparsification for out-of-distribution detection
Reference 39
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Observation 431fcf62-ce39-44b3-9e13-e2360b3d8380 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Ex- ploring diverse representations for open set recognition
Reference 40
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Observation 6cecf683-9941-4900-8af5-05a593c8f484 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Learning to prompt for con- tinual learning
Reference 41
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Observation 67347c73-2450-45d6-bb15-61955621cc10 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Openincre- ment: A unified framework for open set recognition and deep class-incremental learning
Reference 42
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Observation 1e9be925-db1f-44a4-b081-43ab79ff7e74 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Convolutional prototype network for open set recognition
Reference 43
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Observation 9a3fb17a-0ff4-40eb-af8f-db08f36aea7a · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Openood: Benchmarking generalized out-of-distribution detection
Reference 44
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Observation ec4a5563-5f3a-43d6-910b-7210e2b20040 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Generalized out-of-distribution detection: A survey
Reference 45
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Observation 1dfa7e1c-0273-4bf4-811b-3457607dac35 · outbound
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning Classification- reconstruction learning for open-set recognition
Reference 46
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No inbound Pith citation observations are available.