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Paper Citation Record · LEDGER

Configurable Foundation Models: Building LLMs from a Modular Perspective

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2409.02877.

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

pith.paper-citation-record.v1
2409.02877 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:29:22.426303Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:26:26.699953Z

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 f5630d61-65db-4694-bd49-3df07eb35bc1 · inbound

Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact cites this paper.

Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T18:28:39.470118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:28:39.470118Z digest=sha256:aade5be49f63654b860272a1f75624194083854978926891bb4e2275cfb04f99

Observation db85b348-fe6f-482e-9ca7-8963e3188783 · inbound

A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions cites this paper.

A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 244

Resolution
unresolved
no resolver link, observed 2026-08-11T14:15:32.520997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:15:32.520997Z digest=sha256:a9458ee9a091d1e6777e25715546a65acc5d610ce079b287eb8b8ed5dacb978a

Observation 931621ed-25d2-43db-b4a6-505cc2f888a1 · inbound

A Functional Software Reference Architecture for LLM-Integrated Systems cites this paper.

A Functional Software Reference Architecture for LLM-Integrated Systems Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T16:43:26.598911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:43:26.598911Z digest=sha256:19b54bd25a3b9d275e528b5310bf996290918cd5d99713673810a6981ac132f7

Observation 96d68990-b5e8-4994-9256-0123f6e91ebd · inbound

Harmony: A Unified Framework for Modality Incremental Learning cites this paper.

Harmony: A Unified Framework for Modality Incremental Learning Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T12:29:22.426303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:29:22.426303Z digest=sha256:1a2d27a07817c0666d5941d11395fa7298ddecb85418cae6e2552709103b9094

Observation 5a1d0f61-405b-4df2-ac5c-669f501217df · inbound

What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips cites this paper.

What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-15T22:59:56.431878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:59:56.431878Z digest=sha256:e68f149fca1569f453707d907e08ed60df21b8e4c31967e0fe71c0be1457da1a

Observation 63d5c7f4-ad43-46e0-9853-e3d97d953d44 · inbound

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR cites this paper.

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T10:19:48.485849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:19:48.485849Z digest=sha256:cfc7f8e5f10bc04611ee1babcd5b35e521eb51c4c916a8b89150231948418dbe

Observation 1b4da3d7-7bf2-4fdf-a3b6-103286c73645 · inbound

Cartridges: Lightweight and general-purpose long context representations via self-study cites this paper.

Cartridges: Lightweight and general-purpose long context representations via self-study Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:35.128321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:35.128321Z digest=sha256:e09aa008a78d5f4b757923c779d0a4bac4f802835d8616f8d53aa8c723c195e6

Observation 07c072ab-aa9e-4071-b566-81e6133fdf8a · inbound

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations cites this paper.

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:06:04.745656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T04:09:10.125285Z digest=sha256:e4f7e359dcf839ef49a4c7d6ebcadb0717beddfab69532b55ff2c2985a875069

Observation 1f1fbcd0-7d76-44cb-927f-0ea4c51bebe8 · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:26:26.701628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-28T10:56:13.058872Z digest=sha256:90f386f04f9a8e26d3f02d742567d4a8816e1a6f9283975876ba11189141cdcb

Observation 7591efcf-f0f4-43b9-9d36-fc457c8ffbd5 · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 100

Resolution
unresolved
no resolver link, observed 2026-07-13T07:44:25.325808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T07:44:25.325808Z digest=sha256:17c1e4affda6984f6d2a103aba39b3a5c9da1cf65a7351f2d21167d940ce281f

Observation c8e39e35-aecb-429b-b23f-92e7250ce2b3 · inbound

Generalizable and Computational Efficient Channel Extrapolation for 6G: A Configurable AI-Driven Framework Built from a Modular Perspective cites this paper.

Generalizable and Computational Efficient Channel Extrapolation for 6G: A Configurable AI-Driven Framework Built from a Modular Perspective Configurable Foundation Models: Building LLMs from a Modular Perspective

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T20:24:00.645151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:24:00.645151Z digest=sha256:cb9707a9ac3733fa264b7ec9acc0da4df88a4fac01720f816f81f8b6bc1d2315