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Paper Citation Record · LEDGER

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models

As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.19604.

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

pith.paper-citation-record.v1
2607.19604 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:19:18.897482Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved35
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a174f1e-397d-44b0-b6d9-d074499eac80 · outbound

This paper cites Pyrkin and Sergei Popov and Artem Babenko , title =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Pyrkin and Sergei Popov and Artem Babenko , title =

Reference 1

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source=arxiv_source observed=2026-08-01T12:19:15.821649Z digest=sha256:d83de159325540babc0d46c9d559476663ccd250c109681239aad95ea3350c44

Observation e1440304-6d60-4348-b451-98d7f535c0c3 · outbound

This paper cites Editing Factual Knowledge in Language Models , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Editing Factual Knowledge in Language Models , booktitle =

Reference 2

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source=arxiv_source observed=2026-08-01T12:19:15.891075Z digest=sha256:be66779416c030283f84c79ece6b4bb1466b5362e21a74ce1f030e181b802c9e

Observation a310c485-652f-41be-a72a-495831fc18fb · outbound

This paper cites Locating and Editing Factual Associations in.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Locating and Editing Factual Associations in

Reference 3

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source=arxiv_source observed=2026-08-01T12:19:15.964981Z digest=sha256:4065cb787784214f6ce38b4bb5452a0661a1e9e600b961c72e7f8738b82ec32c

Observation 4e7265b1-4e15-4a52-92dd-77d542a31b23 · outbound

This paper cites Andonian and Yonatan Belinkov and David Bau , title =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Andonian and Yonatan Belinkov and David Bau , title =

Reference 5

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source=arxiv_source observed=2026-08-01T12:19:16.129012Z digest=sha256:5591c776159a0d14f7664827486248354d8b013de9c5afd6fb0612c83991177e

Observation 21b5f698-c5f5-4722-9cfa-f354cca005ce · outbound

This paper cites Why Does New Knowledge Create Messy Ripple Effects in LLMs? , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Why Does New Knowledge Create Messy Ripple Effects in LLMs? , booktitle =

Reference 6

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doi, observed 2026-08-01T12:23:40.510626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-01T12:19:16.195694Z digest=sha256:173a9e942767e9d3ed7e42b61ed2f9d4075b2d586c754feb0d39f3be61fdaf4a

Observation efc3ed6f-f325-43b8-8e19-fb6d1fd8a75d · outbound

This paper cites Model Editing at Scale leads to Gradual and Catastrophic Forgetting , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Model Editing at Scale leads to Gradual and Catastrophic Forgetting , booktitle =

Reference 7

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source=arxiv_source observed=2026-08-01T12:19:16.277806Z digest=sha256:222ef27ede387be7ef828bb3fd0a50e22fc1e4f0da6a0dbf2d3c92e494efc1c5

Observation 8f016835-e805-4751-874b-23ba79344215 · outbound

This paper cites Dai and Quoc V.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Dai and Quoc V

Reference 8

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source=arxiv_source observed=2026-08-01T12:19:16.358845Z digest=sha256:a19b63d24d4b00bfe4ae252cfa95224e8fa9bde9439142dd8c4c0aec25ba9b53

Observation 318604d5-c934-4f4b-acb3-2a4a54b3cf33 · outbound

This paper cites Manning , title =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Manning , title =

Reference 9

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source=arxiv_source observed=2026-08-01T12:19:16.428124Z digest=sha256:90b72616cddfd3dd71c0774ddc448db2e40862b6ce4ddcc949389e0a533c83c9

Observation 498082d5-c76a-4f5f-b40c-42d6c5a959ac · outbound

This paper cites PropMEND: Hypernetworks for Knowledge Propagation in LLMs.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models PropMEND: Hypernetworks for Knowledge Propagation in LLMs

Reference 10

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source=arxiv_source observed=2026-08-01T12:19:16.491143Z digest=sha256:34caaff5f6829f9861510eee73f57ef9cf4b91fbcf978ee19c25d8b566bd5779

Observation 4363cbb1-b7a0-4c47-8413-2cb8cd2d3fb9 · outbound

This paper cites Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen

Reference 11

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source=arxiv_source observed=2026-08-01T12:19:16.572211Z digest=sha256:32ae6d9177f4ac883769b13f6629852b4c62e954640edf4cd5b6b78a83484b6c

Observation dd7eff99-29e7-4cae-8af9-8d7eb0cc27b7 · outbound

This paper cites an unresolved cited work.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-01T12:19:16.654828Z digest=sha256:80e029eef054f4946ab10892b9f7b712e554b93fd300991ba121ebdf33f1f9f6

Observation 127345dd-3bfa-4479-a235-5a99ab2e0d17 · outbound

This paper cites Scaling Laws for Neural Language Models.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Scaling Laws for Neural Language Models

Reference 13

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source=arxiv_source observed=2026-08-01T12:19:16.724968Z digest=sha256:19279bd8aa60b35d9c2e83d5b45795e4f5c1ca300667761b542878a9ed59cb18

Observation 4047a737-83e1-4105-9123-08080448a5a0 · outbound

This paper cites Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue , booktitle =

Reference 14

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source=arxiv_source observed=2026-08-01T12:19:16.800701Z digest=sha256:b53244d5c86affaf4d81eb86740377dde1181aeb1a77da38789062921f8d410c

Observation 70162a11-0c59-4cba-835c-708920863ed6 · outbound

This paper cites Hyper-X:.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Hyper-X:

Reference 15

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-01T12:19:16.867048Z digest=sha256:42983730fb5009e91ce03ac563ffb5322d1977cc4206584b41080ff31db42f3d

Observation 4f724a43-9a59-4ac9-b76b-65349a4907f5 · outbound

This paper cites Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection , booktitle =

Reference 16

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source=arxiv_source observed=2026-08-01T12:19:16.925983Z digest=sha256:e4237f85f46ae13cfad1f651c446822693d334037bd93edec66c9efd54fa2782

Observation 1a8ef457-96ac-42d0-8a42-fa96cc8f43bb · outbound

This paper cites Transformer Feed-Forward Layers Are Key-Value Memories , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Transformer Feed-Forward Layers Are Key-Value Memories , booktitle =

Reference 17

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source=arxiv_source observed=2026-08-01T12:19:17.001203Z digest=sha256:dab8076744dd207f006fd7d573d777dffdd7b65274692c6629dc8d23767fc2fb

Observation 1a543f8e-056b-4dd3-984a-ae21a097821c · outbound

This paper cites AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models , booktitle =

Reference 18

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source=arxiv_source observed=2026-08-01T12:19:17.076155Z digest=sha256:10a8c7a8388a84f579341b8fdba1e81eaec39be7c7401d9693ceddb879d7057f

Observation 192f8754-2a91-474a-8d48-b5af01f4ba17 · outbound

This paper cites an unresolved cited work.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Unresolved cited work

Reference 19

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source=arxiv_source observed=2026-08-01T12:19:17.143686Z digest=sha256:43c71bb2ad0dcc0cb72a71202cbd899932e6a6bfaaf8ad4172a4517216acd3a2

Observation 145e785a-8b27-4ff2-9812-263775997937 · outbound

This paper cites an unresolved cited work.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Unresolved cited work

Reference 20

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source=arxiv_source observed=2026-08-01T12:19:17.217121Z digest=sha256:67cd6d8e533f3513b6f9df5eaf59ff4351a669347c8a9c29c97430ef01af3d42

Observation c4d1dd8e-2b3e-42bc-84de-d4ca2dba98b6 · outbound

This paper cites an unresolved cited work.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Unresolved cited work

Reference 21

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source=arxiv_source observed=2026-08-01T12:19:17.290168Z digest=sha256:55a633d4a8fad819de110a850a31fddff519546867d14bb7cd23519b423691f1

Observation 85601252-aefd-49a4-90b0-32e4a49136c8 · outbound

This paper cites Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models , booktitle =

Reference 22

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source=arxiv_source observed=2026-08-01T12:19:17.386156Z digest=sha256:42b80ea681f0919820b7636952f3ea5d690b5f9c85bfae7b3870f290effc63af

Observation 3bfb41c9-1392-4b86-9bc7-f80f74a46c8f · outbound

This paper cites an unresolved cited work.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Unresolved cited work

Reference 23

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source=arxiv_source observed=2026-08-01T12:19:17.460993Z digest=sha256:4e984e7390d9aa18e3d2723b65630b956e996c60955f5601f6f20f5d3ff4b532

Observation f8531dc2-2722-442b-a50a-f30af87ede2a · outbound

This paper cites Qwen2.5 Technical Report.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Qwen2.5 Technical Report

Reference 24

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source=arxiv_source observed=2026-08-01T12:19:17.539281Z digest=sha256:5e79bc964b1d735c8d6072452bfdf04d59b458156ff1fd978a263d6db6a06660

Observation 30c3add8-2287-4b74-9ed5-139858d08fa0 · outbound

This paper cites 7th International Conference on Learning Representations,.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models 7th International Conference on Learning Representations,

Reference 25

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source=arxiv_source observed=2026-08-01T12:19:17.613806Z digest=sha256:be7a7dbbaf79c02674cea4d66416ff73e201e6c6a619c061085be2536ebe3afa

Observation 6517f153-8569-4876-a2ee-e0d42813ecac · outbound

This paper cites The Twelfth International Conference on Learning Representations,.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models The Twelfth International Conference on Learning Representations,

Reference 26

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source=arxiv_source observed=2026-08-01T12:19:17.693810Z digest=sha256:2f2473097789cef9253dac68a1d018590c4a06619c9c1f4f0413c1cd84ec6b58

Observation 5498ee58-9699-40ab-80ca-5a5c99599455 · outbound

This paper cites Revisiting Catastrophic Forgetting in Large Language Model Tuning , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Revisiting Catastrophic Forgetting in Large Language Model Tuning , booktitle =

Reference 27

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source=arxiv_source observed=2026-08-01T12:19:17.784319Z digest=sha256:177e9f5317609d69ba6bc94aeee1b53a3e4cc3e02f6353dfcd2e86d2514eb565

Observation a4591c00-f4dd-40a6-a956-9d08f21dbf90 · outbound

This paper cites SimSCOOD: Systematic Analysis of Out-of-Distribution Generalization in Fine-tuned Source Code Models , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models SimSCOOD: Systematic Analysis of Out-of-Distribution Generalization in Fine-tuned Source Code Models , booktitle =

Reference 28

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doi, observed 2026-08-01T12:23:40.109532Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-01T12:19:17.883780Z digest=sha256:73081bfd9eddf097f38668bcd635985ce67f097a0001cd8b492cf4f1f5de2e62

Observation 40091b1d-0739-4f1b-93cf-1b45b19fa2e1 · outbound

This paper cites GPT-4 Technical Report.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models GPT-4 Technical Report

Reference 29

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source=arxiv_source observed=2026-08-01T12:19:17.961431Z digest=sha256:5be08e0582a0c14ef34e6b63524643fb853c38085e6df9c7ebc88adb7fbddc72

Observation de22472d-4d01-4f50-9a5d-08073edef84b · outbound

This paper cites CoRR , volume =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models CoRR , volume =

Reference 30

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source=arxiv_source observed=2026-08-01T12:19:18.035271Z digest=sha256:58e59d442d8b4d53c6b777ad307719d78b709e75eb2854d8632f21340bbb5585

Observation e5a626be-66ff-43fd-8279-fa5980ab1e85 · outbound

This paper cites Zero-Shot Relation Extraction via Reading Comprehension , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Zero-Shot Relation Extraction via Reading Comprehension , booktitle =

Reference 31

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source=arxiv_source observed=2026-08-01T12:19:18.103997Z digest=sha256:e7e12b28dde01fbf27c4d4e080bd590d583034cc63ced4ae24779e92fe05a1e1

Observation e3e2f3a2-cf45-42fa-9c83-8227c2380ae1 · outbound

This paper cites WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs , booktitle =

Reference 32

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source=arxiv_source observed=2026-08-01T12:19:18.163029Z digest=sha256:ada8162ef04bd2e23e090485e30c858b304ff80aff6bbaed9862aad341eab416

Observation d950fed7-0ea1-4fc3-8518-0cf9438aba89 · outbound

This paper cites FinGPT: Open-Source Financial Large Language Models , journal =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models FinGPT: Open-Source Financial Large Language Models , journal =

Reference 33

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source=arxiv_source observed=2026-08-01T12:19:18.213607Z digest=sha256:d61f72dd907453c754e5b5bd392ed7cf620173ac2cff26061a83b7d959ac3201

Observation 7302e2a1-ea3c-4c4f-a8b5-d3ef49fa1c03 · outbound

This paper cites 2026 , url =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models 2026 , url =

Reference 34

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source=arxiv_source observed=2026-08-01T12:19:18.280654Z digest=sha256:06f28d360defb907a5d545abbc84673775bcc0309a0209e6743a337622a05f5c

Observation 05a3c1e6-6487-4887-80ba-f7ed1219145b · outbound

This paper cites Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations? , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations? , booktitle =

Reference 35

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source=arxiv_source observed=2026-08-01T12:19:18.347001Z digest=sha256:e09f8c3ee8cf73302187d04de3e6360a7e4080ec22d4147d4c03e414936376f4

Observation f191d92e-8868-4655-aabe-326a0ea23a1f · outbound

This paper cites Question Answering on Patient Medical Records with Private Fine-Tuned LLMs.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Question Answering on Patient Medical Records with Private Fine-Tuned LLMs

Reference 36

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local_arxiv, observed 2026-08-01T12:23:39.909062Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-01T12:19:18.421552Z digest=sha256:c435b4f6189e29e82aad3acec612b227353a68633735c66bfe1bd5e44a4cbf56

Observation 4e0f849c-32e3-46d2-9f04-8313e76fbac6 · outbound

This paper cites CoRR , volume =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models CoRR , volume =

Reference 37

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source=arxiv_source observed=2026-08-01T12:19:18.518879Z digest=sha256:144cb3f66abcfacaed8cabddf61e861232b83f198a51ee91afeff3975e8b92f2

Observation 578020cc-c2b0-4d3f-a25e-ec9a2d9f88e1 · outbound

This paper cites Chi and Quoc V.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Chi and Quoc V

Reference 38

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source=arxiv_source observed=2026-08-01T12:19:18.593743Z digest=sha256:3165c050c26b806de7e6d79abf40bcc44ba664b96ff7292c16581be76b890863

Observation 403040e8-bc5f-479a-87d4-8f9bdcc9b22b · outbound

This paper cites The Thirty-Fourth.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models The Thirty-Fourth

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:19:18.691931Z digest=sha256:8f33aa7f98a68d4d2f9215fbd9e0fb7f72b85963ce121164c885deb8166b77e1

Observation dfc4e5ba-7947-4337-8844-b20f605ebd91 · outbound

This paper cites K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters , booktitle =.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters , booktitle =

Reference 40

Resolution
verified exact
doi, observed 2026-08-01T12:23:39.637736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-01T12:19:18.767976Z digest=sha256:0f1c179b8a248ed99d040c230c53c70be5f234879ac5a9be52b3677ea51a3da8

Observation dfe05132-28ed-4f45-a9e9-1ded434fb2b7 · outbound

This paper cites Proceedings of the 57th Conference of the Association for Computational Linguistics,.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Proceedings of the 57th Conference of the Association for Computational Linguistics,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T12:19:18.822928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:19:18.822928Z digest=sha256:2498ce73ac8809f5dee5b73dbbff750ca052f6bbad2d7acae60011b950eae0ee

Observation 530e3df9-f1a5-4dc0-87fe-f78a56833c4f · outbound

This paper cites Fine-Tuning or Retrieval? Comparing Knowledge Injection in.

Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models Fine-Tuning or Retrieval? Comparing Knowledge Injection in

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-01T12:19:18.897482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:19:18.897482Z digest=sha256:a0909040e7fee86ded3219c885db873184f83926eace62ec3bd972f4428a8c3f

Pith citing papers

No inbound Pith citation observations are available.