Paper Citation Record · LEDGER

Soup to go: mitigating forgetting during continual learning with model averaging

As of 10 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 3 inbound Pith citation observations for arXiv:2501.05559.

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

pith.paper-citation-record.v1
2501.05559 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:22:06.097336Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:12:08.181402Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T05:12:18.079757Z

Reference resolution

22 of 22 outbound references displayed

verified exact1
verified fuzzy6
unresolved14
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd36bfe6-12d6-4965-a89b-62ca782506d2 · outbound

This paper cites doi: 10.1109/tpami.2021.3057446.

Soup to go: mitigating forgetting during continual learning with model averaging doi: 10.1109/tpami.2021.3057446

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.027401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 539b38d2-da05-4803-884e-ee8349586bda · outbound

This paper cites Measuring Forgetting of Memorized Training Examples.

Soup to go: mitigating forgetting during continual learning with model averaging Measuring Forgetting of Memorized Training Examples

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.035721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddb04959-de03-4dbf-ab3e-bbd93fa5358f · outbound

This paper cites doi: 10.1073/pnas.1611835114.

Soup to go: mitigating forgetting during continual learning with model averaging doi: 10.1073/pnas.1611835114

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.043412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a072dca-aa16-4406-9c0d-d6378899220a · outbound

This paper cites But how severe is this forgetting? We quantify this by comparing a model that was trained on and has then forgotten Simpl to a model that has never seen Simpl.

Soup to go: mitigating forgetting during continual learning with model averaging But how severe is this forgetting? We quantify this by comparing a model that was trained on and has then forgotten Simpl to a model that has never seen Simpl

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:22:06.387634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51d9b618-8bc8-4217-abbb-5144562dc8db · outbound

This paper cites URL https://aclanthology.org/2020.nlpcovid19-acl.18.

Soup to go: mitigating forgetting during continual learning with model averaging URL https://aclanthology.org/2020.nlpcovid19-acl.18

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:22:06.416884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 41df0d7b-91bb-407b-b1e7-9b425430841e · outbound

This paper cites Fine-tuned language models are continual learners.

Soup to go: mitigating forgetting during continual learning with model averaging Fine-tuned language models are continual learners

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.076995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f29f48cc-8839-4ebb-a6d6-0d394d84053c · outbound

This paper cites Magicoder: Empowering Code Generation with OSS-Instruct.

Soup to go: mitigating forgetting during continual learning with model averaging Magicoder: Empowering Code Generation with OSS-Instruct

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.080734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05e25eac-b470-4dc9-9fdc-866e99a69794 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Soup to go: mitigating forgetting during continual learning with model averaging MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.084411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dd59a43-89a1-49a9-83e0-2847e5e5dfef · outbound

This paper cites η is a hyperpa- rameter, and Fo is a diagonal matrix with the initial model’s Fisher information.

Soup to go: mitigating forgetting during continual learning with model averaging η is a hyperpa- rameter, and Fo is a diagonal matrix with the initial model’s Fisher information

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:22:06.399031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f66a431a-21ad-41a4-9830-dec0ecab03a7 · outbound

This paper cites Finally, we create some model merging baselines using mergekit (Goddard et al., 2024).

Soup to go: mitigating forgetting during continual learning with model averaging Finally, we create some model merging baselines using mergekit (Goddard et al., 2024)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:22:06.374546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 623d9b2f-7ff1-4b3e-a373-4446b1cbf237 · outbound

This paper cites an unresolved cited work.

Soup to go: mitigating forgetting during continual learning with model averaging Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:22:06.339884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0565378d-4a55-4910-aae6-9e6907e94509 · outbound

This paper cites URL https://doi.org/10.1080/ 09540099550039318.

Soup to go: mitigating forgetting during continual learning with model averaging URL https://doi.org/10.1080/ 09540099550039318

Reference 1995

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.069264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e73247d0-2960-4301-aaea-b25153cd80b1 · outbound

This paper cites URL http://dx.doi.org/10.

Soup to go: mitigating forgetting during continual learning with model averaging URL http://dx.doi.org/10

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.073145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8f8b23f-dd8f-40cd-bddf-66ba78a43592 · outbound

This paper cites COVID-QA: A question an- swering dataset for COVID-19.

Soup to go: mitigating forgetting during continual learning with model averaging COVID-QA: A question an- swering dataset for COVID-19

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:22:06.428548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a5ad6c6f-7535-4df2-bdc8-c793c9583201 · outbound

This paper cites Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool.

Soup to go: mitigating forgetting during continual learning with model averaging Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool

Reference 2017

Resolution: malformed identifier; doi_truncated, observed 2026-08-10T21:22:06.165664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d79e904d-497d-449c-a199-8d9cf32f2c70 · outbound

This paper cites Lawinformedai/claudette tos,.

Soup to go: mitigating forgetting during continual learning with model averaging Lawinformedai/claudette tos,

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:22:06.439982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 168359c9-2f31-4bdb-af68-904e0d658a96 · outbound

This paper cites doi: 10.1007/s10506-019-09243-2.

Soup to go: mitigating forgetting during continual learning with model averaging doi: 10.1007/s10506-019-09243-2

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.051931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 122b7418-f516-4653-a1fa-219d41bdd655 · outbound

This paper cites doi: 10.18653/v1/2020.acl-main.709.

Soup to go: mitigating forgetting during continual learning with model averaging doi: 10.18653/v1/2020.acl-main.709

Reference 2020

Resolution: verified exact; doi, observed 2026-08-10T21:22:06.154191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5c3d6633-e0d3-4f58-9665-1948d626fb6f · outbound

This paper cites doi: https://doi.org/10.1016/j.neunet.2020.12.003.

Soup to go: mitigating forgetting during continual learning with model averaging doi: https://doi.org/10.1016/j.neunet.2020.12.003

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.020107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12abc088-439a-4d63-909d-cc9cd09bdeb2 · outbound

This paper cites An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning.

Soup to go: mitigating forgetting during continual learning with model averaging An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.056328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15471346-957c-4072-809c-53c8fa04c992 · outbound

This paper cites Arcee's MergeKit: A Toolkit for Merging Large Language Models.

Soup to go: mitigating forgetting during continual learning with model averaging Arcee's MergeKit: A Toolkit for Merging Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.031543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation beaae7be-682e-4f0b-acef-9ed6b5c09c36 · outbound

This paper cites Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models.

Soup to go: mitigating forgetting during continual learning with model averaging Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T21:22:06.047021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 652fedc3-3e29-4a3d-ab20-63b95647d0a0 · inbound

Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting cites this paper.

Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting Soup to go: mitigating forgetting during continual learning with model averaging

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-09T11:12:08.181402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5aa130d6-3a08-4964-a631-0b732ee1575a · inbound

Continual Learning in Vision-Language Models via Aligned Model Merging cites this paper.

Continual Learning in Vision-Language Models via Aligned Model Merging Soup to go: mitigating forgetting during continual learning with model averaging

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T12:13:42.925177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba548485-fbd4-4145-a0aa-47a8c4d15c09 · inbound

ORBIT: Preserving Foundational Language Capabilities in GenRetrieval via Origin-Regulated Merging cites this paper.

ORBIT: Preserving Foundational Language Capabilities in GenRetrieval via Origin-Regulated Merging Soup to go: mitigating forgetting during continual learning with model averaging

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:12:18.081220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.