Paper Citation Record · LEDGER

Scalable Strategies for Continual Learning with Replay

As of 17 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 2026-08-17T06:30:58.91139+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

Resolution: 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 2026-08-17T06:30:58.91139+00:00.

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

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

Source-reported events for the cited work

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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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-17T06:30:58.91139+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-17T06:30:58.91139+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-15T20:36:39.774836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-17T06:30:58.91139+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-15T20:36:39.784001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-17T06:30:58.91139+00:00.

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-17T06:30:58.91139+00:00.

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

Resolution: 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 2026-08-17T06:30:58.91139+00:00.

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

Resolution: 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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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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Source-reported events for the cited work

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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 2026-08-17T06:30:58.91139+00:00.

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

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Source-reported events for the cited work

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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 2026-08-17T06:30:58.91139+00:00.

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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Source-reported events for the cited work

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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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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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Source-reported events for the cited work

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

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Scalable Strategies for Continual Learning with Replay Unresolved cited work

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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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Source-reported events for the cited work

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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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Source-reported events for the cited work

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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

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Source-reported events for the cited work

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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

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Source-reported events for the cited work

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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

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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

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Source-reported events for the cited work

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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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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

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Source-reported events for the cited work

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

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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

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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 2026-08-17T06:30:58.91139+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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

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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

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Source-reported events for the cited work

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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.

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

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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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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.