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Paper Citation Record · LEDGER

Scalable Strategies for Continual Learning with Replay

As of 20 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 2 inbound Pith citation observations for arXiv:2505.12512.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.12512 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:36:40.017952Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:52:45.940026Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-12T07:31:37.973339Z

Reference resolution

61 of 61 outbound references displayed

  • verified exact3
  • verified fuzzy23
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 985f05ce-91b7-4ef2-8f84-84997dd1a033 · outbound

This paper cites Ss-il: Separated softmax for incremental learning.

Scalable Strategies for Continual Learning with Replay Ss-il: Separated softmax for incremental learning

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.163084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.685795Z digest=sha256:f0646b0acd888787d79089f5882f536da53f6a5726fbc0ab61f87bb9bc84ce3b

Observation 7471c7ee-c21e-405e-b589-346dcdc6b39c · outbound

This paper cites Distillation Scaling Laws.

Scalable Strategies for Continual Learning with Replay Distillation Scaling Laws

Reference 2

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no resolver link, observed 2026-08-15T20:36:39.691481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.691481Z digest=sha256:deccdc5c73fb52a791d3185332fde971e39be0d858d0f38c452c25e9fd90e21f

Observation 6e9377d6-5dd5-4767-b7da-1084cac78dad · outbound

This paper cites Dark experience for general continual learning: a strong, simple baseline.Advances in Neural Information Processing Systems, 33:15920–15930, 2020.

Scalable Strategies for Continual Learning with Replay Dark experience for general continual learning: a strong, simple baseline.Advances in Neural Information Processing Systems, 33:15920–15930, 2020

Reference 3

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no resolver link, observed 2026-08-15T20:36:39.696283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.696283Z digest=sha256:d207998ffcb6c4f4374004f2e435ccd01adba71d0b2aeb0ad3d861f544a7065d

Observation 788d1a61-bef7-4ca7-b183-ddda899cfdb8 · outbound

This paper cites A Survey on In-context Learning.

Scalable Strategies for Continual Learning with Replay A Survey on In-context Learning

Reference 4

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no resolver link, observed 2026-08-15T20:36:39.701007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.701007Z digest=sha256:5ccd828b8817a6aff411081b54e6df4599f0465fe48fb1b39c0058cdcb93806e

Observation bd8ccb5d-a93a-4858-9a25-4ef4e49d2a08 · outbound

This paper cites The Llama 3 Herd of Models.

Scalable Strategies for Continual Learning with Replay The Llama 3 Herd of Models

Reference 5

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no resolver link, observed 2026-08-15T20:36:39.705276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.705276Z digest=sha256:a4b4198d3b391cf9815c9fdb00f0b5d3a14dac62aa8f590fb72dec5bb6e0ba3d

Observation e1f1c890-244a-4890-bbb2-2137017cc03d · outbound

This paper cites A unified continual learn- ing framework with general parameter-efficient tuning.

Scalable Strategies for Continual Learning with Replay A unified continual learn- ing framework with general parameter-efficient tuning

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.139931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.709463Z digest=sha256:b1bb5f18d182051c39ceee90a08da721cc7efd63a56ffbc0c004376ce0f5cb4a

Observation 859c610a-853a-4703-abb8-f362e8785436 · outbound

This paper cites TiC-CLIP: Continual Training of CLIP Models.

Scalable Strategies for Continual Learning with Replay TiC-CLIP: Continual Training of CLIP Models

Reference 7

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no resolver link, observed 2026-08-15T20:36:39.713990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.713990Z digest=sha256:f58c69524d4a6278855c9526e0d1894571b4fc357d9a164142471b6ecf96119e

Observation 3d9e1a87-df4d-4b01-bc48-73f02e670776 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Scalable Strategies for Continual Learning with Replay DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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no resolver link, observed 2026-08-15T20:36:39.719480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.719480Z digest=sha256:b357cb38e5eb067d06e268a1c1b966671b0324523b7e1d876c173db27378562d

Observation 6f80fae7-e518-4f9f-bf7d-33a0f627933e · outbound

This paper cites Rusu, and Razvan Pascanu.

Scalable Strategies for Continual Learning with Replay Rusu, and Razvan Pascanu

Reference 9

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raw_fallback, observed 2026-08-15T20:36:41.125192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.725893Z digest=sha256:7afa71a3543449311b7534fd2e2271bfcd78b8425cf6eb511f19161370158e41

Observation 3870a8a1-62b1-453f-b26d-1e10f0a3636b · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Scalable Strategies for Continual Learning with Replay Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 10

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no resolver link, observed 2026-08-15T20:36:39.730477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.730477Z digest=sha256:b8c43b5c09c6b4f1429b5a1520c1b9c1ede89a775bfe8af6e80615ed26e46818

Observation f922df78-30c3-4c7a-b258-5f3f7f8d154b · outbound

This paper cites Hayes, Ronald Kemker, and Christopher Kanan.

Scalable Strategies for Continual Learning with Replay Hayes, Ronald Kemker, and Christopher Kanan

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.111002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.736161Z digest=sha256:878119c957e7d726f4f7d8c7db38ae68a07d35c36a9603df197d5d229bb25a80

Observation 495ee9ba-6910-41ed-afb2-c690a904f61f · outbound

This paper cites Replay in Deep Learning: Current Approaches and Missing Biological Elements.

Scalable Strategies for Continual Learning with Replay Replay in Deep Learning: Current Approaches and Missing Biological Elements

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:36:40.627276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.741283Z digest=sha256:6185ad0c0ba7c0e2fc9b610e63e7a70e3b4fb9383ebb01020fbd02d6d40b0080

Observation 97881e55-a423-42f2-9ce6-24de3d6228ea · outbound

This paper cites Watch Your Step: Optimal Retrieval for Continual Learning at Scale.

Scalable Strategies for Continual Learning with Replay Watch Your Step: Optimal Retrieval for Continual Learning at Scale

Reference 13

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no resolver link, observed 2026-08-15T20:36:39.748015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.748015Z digest=sha256:a48091ea2975650d711d2b33bb3e112c9ce0ec7dbbc3b25a096573177dd3e197

Observation 33d4d77b-8cb5-4845-aa0f-ac8351a737b3 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Scalable Strategies for Continual Learning with Replay Distilling the Knowledge in a Neural Network

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.757280Z digest=sha256:aa67b3aff8e973fe5efe1c9d7e0a0b6399ce76f0471e6a4a4fd43b236e92c202

Observation c24566ed-89be-4730-9c1f-824c4bf8f4ec · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Scalable Strategies for Continual Learning with Replay Parameter-efficient transfer learning for nlp

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.098287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.764504Z digest=sha256:99af969d747c2353c59e1a2b7bac23b7e7e187b1d256b682874d8c09d1017a46

Observation 3224e36d-6780-43dc-9465-543921014df8 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Scalable Strategies for Continual Learning with Replay Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.084908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.770037Z digest=sha256:5e00737d6761737313f8879ca71066cebcb9fc8b2617e9e9de0f7639b2f9b6a5

Observation 6a5429c5-cdd9-4625-8a41-beb6d3d51615 · outbound

This paper cites A Survey on Retrieval-Augmented Text Generation for Large Language Models.

Scalable Strategies for Continual Learning with Replay A Survey on Retrieval-Augmented Text Generation for Large Language Models

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.774836Z digest=sha256:3955f544213fed0fc79985f466916cbcacb9fa46b45461e5cb6c0723be55a4cc

Observation 8888d7a0-a06f-4b9f-affa-669abc410381 · outbound

This paper cites Position: Open-endedness is essential for artificial superhuman intelligence.

Scalable Strategies for Continual Learning with Replay Position: Open-endedness is essential for artificial superhuman intelligence

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.070832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.779833Z digest=sha256:6a594b10026b324c91c639ab56de7c01f3d3aead3eb2beaa00c79b09240bb75b

Observation 2c718bbd-17db-4aa6-b20e-c781404f3d96 · outbound

This paper cites Simple and Scalable Strategies to Continually Pre-train Large Language Models.

Scalable Strategies for Continual Learning with Replay Simple and Scalable Strategies to Continually Pre-train Large Language Models

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.784001Z digest=sha256:7bc499e05bf27655761dd21eaa206763e8ff9e733d8898def8908bbe38fed47f

Observation 7e1a2f26-a80c-47e1-bb98-8354b09bd90d · outbound

This paper cites Open- clip, 2021.

Scalable Strategies for Continual Learning with Replay Open- clip, 2021

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.054406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.788881Z digest=sha256:8f2e406ccb655eb2a276154beadd251e2ad0a8903c34fccb25b18dbb18d2282d

Observation e6d95999-68ee-400b-8c66-2b9bc6e87e53 · outbound

This paper cites Editing Models with Task Arithmetic.

Scalable Strategies for Continual Learning with Replay Editing Models with Task Arithmetic

Reference 21

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no resolver link, observed 2026-08-15T20:36:39.793386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.793386Z digest=sha256:5ec371324a3099964bb5bd1aa16de943355c24b46ac41159d84e8017f7f36ea7

Observation 61bac005-b78d-486d-9202-919e9cb24b05 · outbound

This paper cites Unlocking the power of function vectors for characterizing and mitigating catastrophic forgetting in continual instruction tuning.

Scalable Strategies for Continual Learning with Replay Unlocking the power of function vectors for characterizing and mitigating catastrophic forgetting in continual instruction tuning

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.040915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.798482Z digest=sha256:5c254fd7170b75652d6846e6731f3b5f636be457afff1d4a2be425cde66bb854

Observation 7f555cfc-9042-4487-a01a-3751b809df4a · outbound

This paper cites Continual pre-training of lan- guage models.

Scalable Strategies for Continual Learning with Replay Continual pre-training of lan- guage models

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.025125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.803852Z digest=sha256:7e2b0b6ed0221a2f8b02633b0bae3969e35edd9c6549c09038a30577995e6e9e

Observation f0dd6fb5-fd24-45e8-af91-82822e4cdef4 · outbound

This paper cites Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A.

Scalable Strategies for Continual Learning with Replay Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-15T20:36:41.010130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.808375Z digest=sha256:f63930e44e67e24514097ae26981f85cbcdb14b5a1ae95ebe2a47da5c336624d

Observation 13765f42-efc1-43d7-a60e-41d34c6af33d · outbound

This paper cites McClel- land.

Scalable Strategies for Continual Learning with Replay McClel- land

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.995704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.812304Z digest=sha256:792c2d67c22e6ab1ce9ca26409d781f872602f203dae99475d8c2903d03a7e7e

Observation 1d6be6db-a26c-482c-bf29-50f6b9ca3087 · outbound

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

Scalable Strategies for Continual Learning with Replay The power of scale for parameter-efficient prompt tuning

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.980529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.817843Z digest=sha256:185f3f6d516a189582a853d528036852827f6b66b273c95c3ff75192d5d51ea6

Observation 3d4106fb-e760-4675-9a09-5a98e81deb17 · outbound

This paper cites Eurekaverse: Environment Curriculum Generation via Large Language Models.

Scalable Strategies for Continual Learning with Replay Eurekaverse: Environment Curriculum Generation via Large Language Models

Reference 27

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no resolver link, observed 2026-08-15T20:36:39.822334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.822334Z digest=sha256:63472921ed774c5c68555c05207830b8630cbfe97a2ef7878b2005006ab95a1f

Observation 3827d59c-ad38-4f1a-9a14-cb402e741ab5 · outbound

This paper cites Loss decoupling for task- agnostic continual learning.

Scalable Strategies for Continual Learning with Replay Loss decoupling for task- agnostic continual learning

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.967764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.827875Z digest=sha256:573522906d096217c9f2e4576a4f92ca89c1c5532fa19957371090777ee5aa39

Observation c1f271fa-c67b-46e2-bd0a-1e4a7ffcc0b4 · outbound

This paper cites A Survey of In-Context Reinforcement Learning.

Scalable Strategies for Continual Learning with Replay A Survey of In-Context Reinforcement Learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.832090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.832090Z digest=sha256:04d4a53b8a602cf91617fda8f5f701c6c1ea62987c04c787bd78042179a8a741

Observation 455113d9-aa82-437a-a1f9-e2718abeca46 · outbound

This paper cites Task arithmetic in the tangent space: Improved editing of pre-trained models.

Scalable Strategies for Continual Learning with Replay Task arithmetic in the tangent space: Improved editing of pre-trained models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.952431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.837751Z digest=sha256:962f805c8125ab06f6c33593cd276bc61d051b17f2cb7409f14ac6fe52b5be22

Observation 28fd64b7-a0d6-4a7f-9e56-ffd91e4277df · outbound

This paper cites R+X: Retrieval and Execution from Everyday Human Videos.

Scalable Strategies for Continual Learning with Replay R+X: Retrieval and Execution from Everyday Human Videos

Reference 31

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unresolved
no resolver link, observed 2026-08-15T20:36:39.842118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.842118Z digest=sha256:0f8a266c83b72a8a20173190666ad8e76cf86a9439c867ea88361da308552624

Observation 98194bbd-0b94-46e3-9f1f-33ed707f5209 · outbound

This paper cites Berg, and Li Fei-Fei.

Scalable Strategies for Continual Learning with Replay Berg, and Li Fei-Fei

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.936323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.850282Z digest=sha256:ef7c4dcdd63dbb788c817b6de0d4c9b2a71378afd15977f091a89e8ea2ab2f13

Observation 0c0baaa2-7591-4ba1-b17a-d09cb7dbf5ca · outbound

This paper cites Progressive Neural Networks.

Scalable Strategies for Continual Learning with Replay Progressive Neural Networks

Reference 33

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unresolved
no resolver link, observed 2026-08-15T20:36:39.855457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.855457Z digest=sha256:223f3a3c5a15b75ccd3ede3653ccb7a2f2add238a1e0db300f5b8f73c6f08573

Observation c7cd136f-cd94-4286-ac17-1aa84e3c8e58 · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-15T20:36:40.921579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.860939Z digest=sha256:99ac4fe97109f0b76040e17275699a33251ae9e469b0d2bdd710f3148617293e

Observation 15020da6-b3f2-429a-81ca-394ab6548143 · outbound

This paper cites A Closer Look at Rehearsal-Free Continual Learning.

Scalable Strategies for Continual Learning with Replay A Closer Look at Rehearsal-Free Continual Learning

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:36:40.402912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.865942Z digest=sha256:73df8ca8bb23d9fdc5513b69fa31d562994529de787242845cd3c67f549dfebc

Observation e05a5980-71c8-4beb-a424-7a969622d53a · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Scalable Strategies for Continual Learning with Replay Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 36

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no resolver link, observed 2026-08-15T20:36:39.872490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.872490Z digest=sha256:09e25443e97f842cde8b8943411f0a317bf8d0855579b55ac820ce39c4db916d

Observation 4dd46f1b-11be-4283-b32a-6f773cc1f83d · outbound

This paper cites Improving online continual learning performance and stability with temporal ensembles.

Scalable Strategies for Continual Learning with Replay Improving online continual learning performance and stability with temporal ensembles

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.905420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.877626Z digest=sha256:8fdd31d4a5897fbc0a1d2f4b73977c1caaf11c7406371dfb086530ef24933b28

Observation 65709ad1-695d-4403-ace5-438c5a833753 · outbound

This paper cites Logit standardization in knowledge distillation.

Scalable Strategies for Continual Learning with Replay Logit standardization in knowledge distillation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.891410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.883576Z digest=sha256:52cd0a6fb93de763c37d8e29fa37021b9312579d5e53a5efa6d183fe53028470

Observation b9a7c7a7-16bb-434c-9c01-90c1c7832ad5 · outbound

This paper cites Three scenarios for continual learning.

Scalable Strategies for Continual Learning with Replay Three scenarios for continual learning

Reference 39

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unresolved
no resolver link, observed 2026-08-15T20:36:39.888750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.888750Z digest=sha256:249ebe860d4f6424b97badfec93d893e88109fc0f6fdb7721d2d7cd732f16f63

Observation 39782e8a-3ebb-47d3-908d-e82e2a40511a · outbound

This paper cites Continual Learning: Applications and the Road Forward.

Scalable Strategies for Continual Learning with Replay Continual Learning: Applications and the Road Forward

Reference 40

Resolution
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no resolver link, observed 2026-08-15T20:36:39.895084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.895084Z digest=sha256:b20574d709748f62842c865f9f5f2dbac3ceb5a0be913413e16d77486d38d247

Observation f1aaca85-2405-4aba-b369-c9fb4944ccae · outbound

This paper cites LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery.

Scalable Strategies for Continual Learning with Replay LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.902351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.902351Z digest=sha256:de2b1c08f86d115641aaf77bd2b16bdf858c8c6863da894402b1957f0f8f08f9

Observation 1b7527e8-1669-4f8f-8b44-a4d7c65436ea · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Scalable Strategies for Continual Learning with Replay Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.908612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.908612Z digest=sha256:92a139805482b4eabd9475896b3f9ac401a2ce6490147204cd717ff89f8afcdb

Observation 245eb1cf-096e-44af-b060-9da2b18229c3 · outbound

This paper cites A Comprehensive Survey of Continual Learning: Theory, Method and Application.

Scalable Strategies for Continual Learning with Replay A Comprehensive Survey of Continual Learning: Theory, Method and Application

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.913971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.913971Z digest=sha256:6042781833438cac1da2a068a827fd052f3fafdbcde38895967aba9727b0e3fc

Observation c280793e-2621-45d2-949f-31769d41da21 · outbound

This paper cites HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning.

Scalable Strategies for Continual Learning with Replay HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.919886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.919886Z digest=sha256:9ec8b4284accfadc2ab10274a56b4e7540376a17de9c2fa91b994c677fe79d3f

Observation cad0bd5e-de43-4592-b323-ef15ef4e9faf · outbound

This paper cites Scaling Pre-training to One Hundred Billion Data for Vision Language Models.

Scalable Strategies for Continual Learning with Replay Scaling Pre-training to One Hundred Billion Data for Vision Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.924686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.924686Z digest=sha256:00fbd52c6a0b8fc39c2cf8f3f4766ecfa76829e51001be21480a7b250f402ef5

Observation 2a030f35-316d-49a6-b1a1-a327d3a076a4 · outbound

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

Scalable Strategies for Continual Learning with Replay Dualprompt: Com- plementary prompting for rehearsal-free continual learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.876702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.929448Z digest=sha256:8561865918d0a8a8c8dc67cea5761af31ff97daaf421ec9b1f7e22feaed65850

Observation 747174de-b0c3-410a-81e1-7a763d9dbf49 · outbound

This paper cites Learning to prompt for con- tinual learning.

Scalable Strategies for Continual Learning with Replay Learning to prompt for con- tinual learning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.862286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.933407Z digest=sha256:5bc1b7e87d4891d3d43c68dd5e235bbb305e06df2d88d1f075733b83fe54cf6c

Observation 2701cef0-8d5b-4a49-aaa9-7a540a88dae8 · outbound

This paper cites Continual Learning with Low Rank Adaptation.

Scalable Strategies for Continual Learning with Replay Continual Learning with Low Rank Adaptation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.938877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.938877Z digest=sha256:8075135258ec35c5d1e543c6a6ca3702b433a771de0234c821a018bcc82a454a

Observation 75944516-8a84-42d9-ab38-082a0b82108a · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.847535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.943806Z digest=sha256:44567e43f9d268f521678aebee71abc789a7747c56094fb7690ffa5a59f89a50

Observation a95ecb7e-e125-47fd-bedd-b7e95b2b3394 · outbound

This paper cites Ties-merging: Resolving interference when merging models.

Scalable Strategies for Continual Learning with Replay Ties-merging: Resolving interference when merging models

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.832841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.948484Z digest=sha256:b02d1061e63dba0a2f70ad43a9d3f1dfa39aa1721a98c459fc74dd04de26bc40

Observation 09021c6b-cf5b-4ed8-9934-44ffd9b31f61 · outbound

This paper cites What Matters for Model Merging at Scale?.

Scalable Strategies for Continual Learning with Replay What Matters for Model Merging at Scale?

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.952965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.952965Z digest=sha256:f5d90c94ae013cdb921469788036b60c57c5226813d0d07f35020178bef713dc

Observation 684d57f5-55f6-449c-9788-0f61bc491016 · outbound

This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.

Scalable Strategies for Continual Learning with Replay Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Reference 52

Resolution
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no resolver link, observed 2026-08-15T20:36:39.958433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.958433Z digest=sha256:24909f8ef260cd29859687a3603be4b372e91f6afc262f9b5595765898d63973

Observation 5a7b8dc7-2c9d-47b7-af29-680c90fe9ff4 · outbound

This paper cites Continual Learners are Incremental Model Generalizers.

Scalable Strategies for Continual Learning with Replay Continual Learners are Incremental Model Generalizers

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:36:40.147891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.963383Z digest=sha256:b96f1ef8be07d0bdab00fe0a264ae297756f2c5bbb982b55a786f51f763e2af4

Observation b7fb3d7e-7836-4b2f-96f2-ca3acf4d7ecf · outbound

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

Scalable Strategies for Continual Learning with Replay Boosting continual learning of vision-language models via mixture-of-experts adapters

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.815167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.968019Z digest=sha256:1a88143fd06ffbe0f656ece458756f49659b6e67c68dfe741ae529181a94ad20

Observation 682bb8c4-0519-4a91-aed8-9bffb16f6c31 · outbound

This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch.

Scalable Strategies for Continual Learning with Replay Language models are super mario: Absorbing abilities from homologous models as a free lunch

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:36:40.798360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:39.977613Z digest=sha256:a07fd8d9c16399d017759e64f6e805c909ea5e217ace42e9d8a498d0c8aa5c35

Observation 49af8606-e438-4229-aee3-1729c705c914 · outbound

This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

Scalable Strategies for Continual Learning with Replay When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.982811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.982811Z digest=sha256:8d292a8cb1ebdffeb1da58805f7cb37a06dd2e35d114b0c1730e849a25f759a4

Observation 738483fd-c6de-459c-bfb7-471a867d4dcf · outbound

This paper cites C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models.

Scalable Strategies for Continual Learning with Replay C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.988068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.988068Z digest=sha256:ab21197366887a5f290b06dc45ace94bcc116cbc873e971530a516b05f384d5a

Observation 561bb109-b054-4d2f-8d3e-f75c5540c614 · outbound

This paper cites Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models.

Scalable Strategies for Continual Learning with Replay Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-15T20:36:39.994817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:36:39.994817Z digest=sha256:b2d13933bdd5b891cdff98dbb4c69be2e391e45c2a92ed08fb03b4c6607f09f2

Observation 3d221bd1-4184-4cdc-8350-88d2d9ec76a2 · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.776185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:40.001203Z digest=sha256:465be98fe936bdb58b6ef9030e39d266a03fda3a1f75a94bceb38bff0d402d48

Observation 8321aee1-8b30-488a-867c-8c0068008d87 · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.760425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:40.011692Z digest=sha256:a1ad4f74f0a248287e5ac4ad3509e1813aff77e0ab8d5cc06ab07343ea61eb0d

Observation 96c8ffc4-0274-4c01-a541-9b3875b9665a · outbound

This paper cites an unresolved cited work.

Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-15T20:36:40.745781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T20:36:40.017952Z digest=sha256:9966826c8b7c82179ddd9c19571e23337c8abd561c6441c3cb0ae5d3ba14e522

Pith citing papers

Observation 2f44ee6f-2ef0-49ec-a217-d0177ddb041c · inbound

Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training cites this paper.

Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training Scalable Strategies for Continual Learning with Replay

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:31:38.010166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-12T02:32:08.672114Z digest=sha256:351f161db540a09f080e7dc5f0f66b1fb4253f08ba2c7b24756a27b6396319ec

Observation 1424c1d9-c3e7-409b-9289-51a06d2c05a3 · inbound

Diffract: Spectral View of LLM Domain Adaptation cites this paper.

Diffract: Spectral View of LLM Domain Adaptation Scalable Strategies for Continual Learning with Replay

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T15:52:45.940026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T15:52:45.940026Z digest=sha256:2737304f7472a916acfa96d163e31d70ab1cefdafad829db990a8a28da0aa244