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Paper Citation Record · LEDGER

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation

As of 22 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2607.07529.

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

pith.paper-citation-record.v1
2607.07529 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T08:11:23.216344Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

44 of 44 outbound references displayed

  • verified exact16
  • verified fuzzy25
  • unresolved0
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  • malformed identifier0
  • metadata mismatch3

External citation measurements

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Outbound references

Observation 2149fc46-fd88-4942-9259-06950e22afc7 · outbound

This paper cites Advances and open problems in federated learning,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Advances and open problems in federated learning,

Reference 1

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raw_fallback, observed 2026-07-09T08:16:06.002594Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c9df269e-9835-4116-b485-9d0c4d8cead8 · outbound

This paper cites Federated learning incentive mechanism design via shapley value and pareto optimality,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Federated learning incentive mechanism design via shapley value and pareto optimality,

Reference 2

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raw_fallback, observed 2026-07-09T08:16:05.940225Z

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Observation 232e392c-94a0-488c-ba5b-cc6f1332e017 · outbound

This paper cites Data shapley: Equitable valuation of data for machine learning,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Data shapley: Equitable valuation of data for machine learning,

Reference 3

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Observation 4fce9e01-2a9f-49b4-8903-c15af69138fb · outbound

This paper cites Efficient task-specific data valuation for nearest neighbor algorithms,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Efficient task-specific data valuation for nearest neighbor algorithms,

Reference 4

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:a08f68899279a47a0c08e10b1307d737b779ffed95c05c195e20b0786baa33e7

Observation 02ec77c6-7fa6-495e-b430-448ea426193f · outbound

This paper cites Ten challenging problems in federated foundation models,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Ten challenging problems in federated foundation models,

Reference 5

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:4d4930bab67c4777642e6ab190d03ea111a21f1665bef167df2e352806fb3f5f

Observation ec90cf84-aa8f-408d-a329-b41fe28c3ffd · outbound

This paper cites A value for n-person games,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation A value for n-person games,

Reference 6

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:30ebe0fb151b9d70a2269e2ad100b24d6e4aa59623cba0f7c65220c154d7b0b7

Observation 6210b32a-2ba3-4d3b-9e60-76262f976ecb · outbound

This paper cites Federated Learning for Data Market: Shapley-UCB for Seller Selection and Incentives.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Federated Learning for Data Market: Shapley-UCB for Seller Selection and Incentives

Reference 7

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local_arxiv, observed 2026-07-09T08:16:05.713556Z

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:c223a0e3871a1d6ef36a56beffba017ee8ad928e6f87d83b3e1616deccb318e0

Observation bd9a082d-14ce-4992-9dbb-e84b9d0d925d · outbound

This paper cites Fedave: Adaptive data value evaluation frame- work for collaborative fairness in federated learning,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Fedave: Adaptive data value evaluation frame- work for collaborative fairness in federated learning,

Reference 8

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:eff08a6d9af28701f9f8f961ade51744d0b742f269705ac4df42cd5f0f233591

Observation 89be29fc-adf2-447a-b14c-20a4545f1d21 · outbound

This paper cites Incentive mecha- nism of foundation model enabled cross-silo federated learning,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Incentive mecha- nism of foundation model enabled cross-silo federated learning,

Reference 9

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:9bf726d821d586ebb98b12da0086b866db6fb38fd198d48f7937df9868e2bb2b

Observation 5d84ef20-ddff-4cd4-8c4a-28d36b1cc54c · outbound

This paper cites Counterspeculation, auctions, and competitive sealed tenders,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Counterspeculation, auctions, and competitive sealed tenders,

Reference 10

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:b0428bc32d5407e4b66c4a0407fb3ef61609d9ad05ec86b43b739d3856e351e3

Observation 8e09be5b-21b5-4e59-b18c-8b7fb52ff042 · outbound

This paper cites Multipart pricing of public goods,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Multipart pricing of public goods,

Reference 11

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:1f1277982ff501b9e952034e1d94ed7dfe472d436ac585fe6f9d4bfbc7a722e7

Observation 992ed1ad-0ead-420a-8730-67d3e1421bd9 · outbound

This paper cites Incentives in teams,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Incentives in teams,

Reference 12

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:202e431d293a805a041e29773378d0d5207059c15638a10a5d79c35bbad807e9

Observation 5afd109d-37fe-4849-88a4-ff5bdc277481 · outbound

This paper cites Eliciting informative feedback: The peer-prediction method,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Eliciting informative feedback: The peer-prediction method,

Reference 13

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:efbb1e3fc40e634d981a3d5ea434bf84f982eba0f088b77ee30c6260e818982e

Observation 0e558d15-b019-4ede-ac22-277aa5f8377c · outbound

This paper cites FL-Market: Trading Private Models in Federated Learning.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation FL-Market: Trading Private Models in Federated Learning

Reference 14

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local_arxiv, observed 2026-07-09T08:16:05.748253Z

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:8a2cb010d930ab69c4ad35c0cb46a346df78da523ed8d07797c4c782604f507a

Observation 166863ca-44e7-47a2-bfb3-54843479a406 · outbound

This paper cites Mitigating Sybils in Federated Learning Poisoning.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Mitigating Sybils in Federated Learning Poisoning

Reference 15

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local_arxiv, observed 2026-07-09T08:16:05.689241Z

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:54ffa01f5da97cca7f70c90878684c0d034dabdbbb04cbcff1326465d92e957b

Observation 2c3af589-380a-4b25-a29f-bb9903d24347 · outbound

This paper cites Understanding black-box predictions via influence functions,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Understanding black-box predictions via influence functions,

Reference 16

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:45d0df35bab88d697c665c26368d50c395452d78c885863ffd0e804b7c4ee4eb

Observation a9eff0d5-1c00-4d83-b393-a9e553a90fcc · outbound

This paper cites Data valuation using reinforce- ment learning,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Data valuation using reinforce- ment learning,

Reference 17

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:0ffa8deeb9cade29bd6556b368af52cb05700ccde504fc0a5f0062daeec4f734

Observation cc757919-9822-4108-bf47-aee26d2744b5 · outbound

This paper cites Beta shapley: A unified and noise-reduced data valuation framework for machine learning,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Beta shapley: A unified and noise-reduced data valuation framework for machine learning,

Reference 18

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:672a88e5030c42489f5e29ec76fd14fb472ef258d7bbb17cfed7ac50e12bb388

Observation b4cd144d-1455-4422-acea-cd6528c39292 · outbound

This paper cites Fair Document Valuation in LLM Summaries via Shapley Values.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Fair Document Valuation in LLM Summaries via Shapley Values

Reference 19

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arxiv_id, observed 2026-07-10T01:18:45.447774Z

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:0f2fc92cc8bd2fc758e6ce8969be3f075ccb36efb65f400e672c9d40204ecb8e

Observation b67f6625-5289-433f-985a-49d45da525bd · outbound

This paper cites Data auctions for retrieval augmented generation,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Data auctions for retrieval augmented generation,

Reference 20

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:b8dfd8df0937c3ae040233dee45684bf27b8f15e7e7722fcd005bb7e8c486c2e

Observation 5e6871eb-0092-4bb1-9502-79a52bb0121f · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 21

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:38dffcdf1a79e36d4764b235907663f2c199e872628d51bd523f6cb90267af30

Observation 814b74af-d3ef-4593-a426-faf1543a9956 · outbound

This paper cites Lora: Low-rank adaptation of large language mod- els,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Lora: Low-rank adaptation of large language mod- els,

Reference 22

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:7f457d841973c42de68d059f9956761df4a6cf3aca73ecb33de80af3a52642f9

Observation dcc966ca-09d1-4f7c-91f1-3e5ce3ce18cd · outbound

This paper cites Training language models to follow instructions with human feedback,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Training language models to follow instructions with human feedback,

Reference 23

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:b598dc705cf666d05f88eb6730f83179e7f696f0eba054fff469c75697440039

Observation e431fa01-4480-4c07-b68f-3ae6a9e2a930 · outbound

This paper cites Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models

Reference 24

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local_arxiv, observed 2026-07-09T08:16:05.741642Z

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:4f26999d6a13f9cf1c86aa50eef524bb2e67c7bb197874cc0bcd01f2659ee145

Observation c1252d23-5417-4857-b7a2-88db7385bc22 · outbound

This paper cites Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA

Reference 25

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local_arxiv, observed 2026-07-09T08:16:05.708373Z

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:26855b028ed7f66a9b2e68a74d4d44f8f728b44ea71fc4f6fb0af56a8acf7a36

Observation b100f2cf-d859-4b2f-9011-0c19111bbb4f · outbound

This paper cites FedEx-LoRA: Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation FedEx-LoRA: Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models

Reference 26

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:3f089c43705f6d2e6fd9f98e0cefec330228adef3050616b4e178932722e17f2

Observation bdf73ec2-b8f9-4233-9a08-93a306d9aff6 · outbound

This paper cites LoRA-Fair: Federated LoRA fine-tuning with aggregation and initialization refinement.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation LoRA-Fair: Federated LoRA fine-tuning with aggregation and initialization refinement

Reference 27

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arxiv_id, observed 2026-07-09T08:16:05.725493Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:578f849bcb330db78797cfcb06806d61011ecfa70ad88e5c90c2e16463ea1d03

Observation 89368811-5a6c-41ed-890d-9fa294b71f70 · outbound

This paper cites FLoRA: Federated fine-tuning large language models with heterogeneous low-rank adaptations,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation FLoRA: Federated fine-tuning large language models with heterogeneous low-rank adaptations,

Reference 28

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:ee25ca6406b8905dbf25ee0d88311a9f61d52bf005cffc6383251ba3a32b4c6d

Observation 0466d020-5ac1-4405-8c31-974d21c0b58f · outbound

This paper cites arXiv preprint arXiv:2603.08058 , year=.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation arXiv preprint arXiv:2603.08058 , year=

Reference 29

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arxiv_id, observed 2026-07-09T08:16:05.670527Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:81d26c2228b35880c21c12569c9ed569ad77204a04bc241c4235ed5f701f90e1

Observation a20d093e-9e4f-46c3-8b5a-b329a3e91a5d · outbound

This paper cites WinFLoRA: Incentivizing client-adaptive aggregation in feder- ated LoRA under privacy heterogeneity,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation WinFLoRA: Incentivizing client-adaptive aggregation in feder- ated LoRA under privacy heterogeneity,

Reference 30

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source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:e9a5043d77921dc0783ac1d6730a70c77fb60662b58dbe7e58c87e44b2586ae7

Observation cc9198fe-49b5-4061-8337-774507d0a6a3 · outbound

This paper cites CoRAG: Collaborative retrieval-augmented generation,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation CoRAG: Collaborative retrieval-augmented generation,

Reference 31

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raw_fallback, observed 2026-07-09T08:16:05.964272Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:bd6b6b4b4fb8e4e8a53bfd74b37f0434e623afbab790f8d067378422c5ea81d3

Observation 77dd794e-02fe-4ce4-b5c4-6b3475c0c4a7 · outbound

This paper cites Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation

Reference 32

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local_arxiv, observed 2026-07-09T08:16:05.765349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:c17b84608488a794c9c88f2452dc4844c4161ca8ffeeb7023aa8be27ecdfa682

Observation 07485b65-7f08-46af-bb73-21ae71613359 · outbound

This paper cites Data Measurements for Decentralized Data Markets.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Data Measurements for Decentralized Data Markets

Reference 33

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local_arxiv, observed 2026-07-09T08:16:05.768781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:84b87e3218267aa71fbba446b368db012d480bcda6329cd79af5a167390d0596

Observation 751b1fe4-758d-4f76-bece-da1ebecbc196 · outbound

This paper cites Towards data valuation via asymmetric data shapley,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Towards data valuation via asymmetric data shapley,

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-09T08:16:05.761388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:64406e1a4c4cfaf3edb6c43facd10ebd6040dfcf8ebbe9e86b753c953b293dbe

Observation 1387c366-453b-4fb1-ad56-dde1c67d2e21 · outbound

This paper cites Rethinking data value: Asymmetric data shapley for structure-aware valuation in data markets and machine learning pipelines,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Rethinking data value: Asymmetric data shapley for structure-aware valuation in data markets and machine learning pipelines,

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-09T08:16:05.681454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:86a608dcd614dbd3234b0ba643468638ed676717ace57a956c117ae64318fa99

Observation e3a67199-c77c-4153-a84b-d86aab02ea3a · outbound

This paper cites Precedence-Constrained Winter Value for Effective Graph Data Valuation.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Precedence-Constrained Winter Value for Effective Graph Data Valuation

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-07-09T08:16:05.685688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:ad301fca4f49f61c76c6b16ec8f0803b5d5b755569402ae9c8a55e4f70e19d32

Observation ea7580b9-b21f-4b8a-b8fa-1c695346f1b7 · outbound

This paper cites Owen sam- pling accelerates contribution estimation in federated learning,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Owen sam- pling accelerates contribution estimation in federated learning,

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-09T08:16:05.720421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:8ebe4477cfab74481178730930da4e55d9b0943657545db2d1f7df4074860b54

Observation bddb2bdd-85b4-4eae-9e42-23b8bb37d8c1 · outbound

This paper cites Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-07-09T08:16:05.698302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:a04720602cbec12388395b05b8cfdd73787612eb89f76c4272132cc265a12f09

Observation c164b0aa-2143-4dd3-bda0-04f4c37fa1ec · outbound

This paper cites C-FedRAG: A Confidential Federated Retrieval-Augmented Generation System.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation C-FedRAG: A Confidential Federated Retrieval-Augmented Generation System

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-07-09T08:16:05.755100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:73e1137c31db813b9e7583cc8d234bb4ec94b55f59c96dc7be828919819a00b3

Observation 7d32c65b-edbc-48f9-a6e4-d04664feba79 · outbound

This paper cites Fweb3: A practical incentive-aware federated learning framework,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Fweb3: A practical incentive-aware federated learning framework,

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-09T08:16:05.736024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:84409ad8293eaf17ae8cc8a2cb90a7cf9b289105506d62d895a4538015289947

Observation 9fad2d5a-e419-4677-906d-4f7db90228e5 · outbound

This paper cites The Shapley value for cooperative games under precedence constraints,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation The Shapley value for cooperative games under precedence constraints,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T08:16:05.948805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:e84e96ebab96d373fb73b721eedcf414270c6f2e9a4beac33c8f3054be988c94

Observation 5a3a65df-cddb-41f4-8428-65f4f9264eac · outbound

This paper cites Values of games with a priori unions,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Values of games with a priori unions,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T08:16:05.926093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:582a2043602ddc4edc99429f5bb14e8ec67c63b07f4f738048e519720210fec3

Observation 03d85fa0-3987-4fc3-9def-d5e4b3c51ae7 · outbound

This paper cites Concentrated differential privacy: Simpli- fications, extensions, and lower bounds,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation Concentrated differential privacy: Simpli- fications, extensions, and lower bounds,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T08:16:05.998584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:ed36dff96bd4ca30c0d508c5ecfdf86b1b1611c37568484e4cff6e094d037957

Observation c189975c-c4e5-46b6-befa-3837fe579d8b · outbound

This paper cites R ´enyi differential privacy,.

FedMark-FM: Auditable, Risk-Adjusted Data Markets for Federated Foundation-Model Adaptation R ´enyi differential privacy,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T08:16:05.960241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T08:11:23.216344Z digest=sha256:6531c8ea8c64e02e4bb04e3e99b53f40073e90cbc7320c4e6095541ce51a9c15

Pith citing papers

No inbound Pith citation observations are available.