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Paper Citation Record · LEDGER

AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2302.07027.

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

pith.paper-citation-record.v1
2302.07027 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:58:45.122333Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T11:32:37.088147Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6f8ea430-8cd3-4720-ba36-25831f0259b9 · inbound

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

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-13T11:32:37.089595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T11:32:36.738536Z digest=sha256:5a9d1aa6665a55839d653fac34dd60ba50df23873aade0cc1ee05576b5984fbc

Observation 8de607fb-8dbd-4dc1-9972-e0cf5bf53464 · inbound

CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing cites this paper.

CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T13:58:45.122333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T13:58:45.122333Z digest=sha256:9402ba80256fda5c6ab6e54312e053b4fdbf17eb3cac2609711e8156c55aba8a

Observation c6f511af-e303-474e-abc6-8ae8dbe74248 · inbound

FlexOlmo: Open Language Models for Flexible Data Use cites this paper.

FlexOlmo: Open Language Models for Flexible Data Use AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T18:57:16.005446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:57:16.005446Z digest=sha256:ab45c4d78bd590ed706fda7e8c6140707d05ba742042a149464f78ab8556f0f5

Observation 69590e2e-09af-40ad-b1ea-8164a0f2160f · inbound

Tensorized Clustered LoRA Merging for Multi-Task Interference cites this paper.

Tensorized Clustered LoRA Merging for Multi-Task Interference AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T01:01:48.104090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T01:01:48.104090Z digest=sha256:ed663ace207e9052a5bcc3b61dd59a1922362477e035fb081c4be4cb38ab283b

Observation 3607e9dd-72d6-4334-98d1-783525177c5a · inbound

Semantic-guided LoRA Parameters Generation cites this paper.

Semantic-guided LoRA Parameters Generation AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-05T05:37:05.785956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:37:05.785956Z digest=sha256:44d489a303dfdf68b688cde56ac51c45be5f1ae8faa2fd83f9ab63003e3d83bb