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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 2026-08-08T06:32:00.761636+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=sha256:7655a5ded8c4795e009b0fa8205173b880088fa34e2efbcdd52023d9510d1b45

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=sha256:837c43466bfb202cbf7e9fe22631366ba2c0e6c13ddbcc1459fff738244b2098

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:b6b99ec41d0fbd5662b301732e28b59626a45ff5b7daae88e01623367acaed05

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:da39b4a46f14ed899a4daa303903a955cad1ee00ba0bb2cae2b87ec4121cd40a

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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verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-01T12:19:16.195694Z digest=sha256:1b9c4dceee84133f5b74b0a1dd77e667042c7ea0aadd400fd014068c4fbf55e4

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=sha256:17e40646a3afdc948a3ea9ad0ea7c53e5d03f9505890e0ce859d4c5dad5b13c2

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=sha256:21713cfb28d0e4cf677aea5b0d9f13047d050d2f99af53892c83928590fad6ab

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=sha256:24949808ae976ba59e010faa2b08f05743f6a4209d0cf13c638b35c554022274

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:fa84d9a3a83ead11e1d99fe8f2ab83b6312a094d86a7cd95a2623fef99c00b1c

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:c8a0857f229e83961a97ffbc3b5c921e52407f5e52606835625f8763889bf402

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=sha256:01983c09cf7138692669fc357c6f4b7fae185f2086eb4c5eb1bc2fb9ad1ca94c

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=sha256:4fff34e0588299399ecb973f05123e4a8a323c2dbf8acf81d48eb84517f898ff

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=sha256:1c580ea8ccd99d7ca4ed9b9f74434e00a577c0166df86c942a5ab7f3c3f98445

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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doi, observed 2026-08-01T12:23:40.290043Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-01T12:19:16.867048Z digest=sha256:6bebfa79e85a41a75849e8d315076ce2053fd80191e45bec8c82981733d3429d

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=sha256:42c65ee6fb208bc9e0de3e582968273108640fc71a6f41be030bf6986fb7982c

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=sha256:439882b1f18e257cc28e253a9408e11975bd84aa8b5ae55021e86d917ffc8d06

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:a8fa9292ee84284e99b3526a94253c7fd1996897c68e9a74e46b81c47990fe77

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:d21af2aa8884fbb7f40e6e782ca84f9581e3faf3a8ba1ea2857b1b9a18e905bb

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=sha256:61aafebc06bc06c7ea638579a2cab0e9a9149d784ab4ecc4b258e442e403ab27

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:ac114f45560e88e975fdfba449fb6a07ee1a187959ef03f51b96de9bca6ef7d6

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=sha256:12ff4b3bc204a4c1da94d374f31541ba91aa97de6d6fcedbe8adeab430df48aa

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=sha256:152aa1b0e733ae65f9b3118cd985dee4ad6205925a8c17ea73f04063ac671074

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:b41def5a2659d6cfd42e02884e24baa658799ccce5db14dca7da0feeee04ede4

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=sha256:4a4ac88905888d9b5efcf9d72c99cde0bc9a7b7afbc266337f59fcbe251fa64e

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:c63fa81272e560e5197a83c86004097aa83e20c6ab8654089323e697bfb43fc2

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=sha256:69c9f446283a662b2975fe84338ba1ddd952fb9d3d56f83437baba5eb50e0eea

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-01T12:19:17.883780Z digest=sha256:840f405f9edd26c2f2275ff7905528e427c9edbac42941cc8c1b5c6dc28fd93f

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=sha256:235da0358dabf94fdd28c21c28c0b552aac9d8c3607401646d834ced42c3aa5a

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=sha256:360a2a70aab4c2824566225ebca575db20044c4b7f4ee52c5e4e444ca98942e1

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=sha256:1ae9e3ad6677d8dd870d96342b57fcb3d4151da4f78c716be87930b71a534aac

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:ace3b1b3ea123ca05f51fcdb145d4160059b431d5a2b507581f60f1c45ace533

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=sha256:12159e9d45538a566d45c844cd9ec8cf3678232df1f0b48f4954d996e44062cc

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=sha256:7dc4ba8fa25938a1eb54ceaec3c2b6d038f67a41daaea1d839b98755f8aad568

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:d3f8b078310f389328fc0452fa06bc6c0c9e4b20049116d76370402fd2398ccf

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-01T12:19:18.421552Z digest=sha256:79347e49335b6fd0cabddaeff57b384cb8ab67eb1339759038bbd833754363f8

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:bf3d4022d81b57ea153a8149bb8cd12bd47fd3610855f03309f829db546cfb33

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=sha256:5f8654447963ed8dded5310cc405105228b7d3d20be639ac64ef080409c60e49

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:bb1054bb0b454801aad52f34934ae835e8de3760a0207d3029bc5a5b80fa738a

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-01T12:19:18.767976Z digest=sha256:510f34cb2b143b0914c97c81aaf762cb92cd42da13c5400d9779b85f585c2148

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=sha256:74ee440cc10a13d9a486efad231bc7ceec316b6d50be0d7bd6624344fa789a23

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=sha256:1af44e7bf50d6b3753341a7f200cce07aa5d107974a718d67f86bcd20d9e58ee

Pith citing papers

No inbound Pith citation observations are available.