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Paper Citation Record · LEDGER

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning

As of 7 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.12612.

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

pith.paper-citation-record.v1
2507.12612 v4

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:54:30.317387Z

measured 43 of 43 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

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy14
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 88cf1c0f-639f-4264-91e3-b2ce8acbe740 · outbound

This paper cites Achille, M.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Achille, M

Reference 1

Resolution
verified fuzzy
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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=2026-08-06T16:54:25.810159Z digest=sha256:0d22e2a4443caf57c91f5bd5f89eb61866abebdb662b2382f7d9331f55d5cabb

Observation 9b223c7b-30dd-49ae-9b40-8f72c45f8789 · outbound

This paper cites Agarwal, K.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Agarwal, K

Reference 2

Resolution
verified fuzzy
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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=2026-08-06T16:54:25.885810Z digest=sha256:0e4c66b325c88b39826373f9e6005f931e7088c1b5f85b5e4cd735c5df075e23

Observation 45424dd5-2189-4c4e-93e3-fdfc2f10cf7c · outbound

This paper cites Alvarez-Melis and N.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Alvarez-Melis and N

Reference 3

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verified fuzzy
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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.

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Observation e8591ec4-e18e-450a-a344-ed594f69cc82 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:26.156947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:26.156947Z digest=sha256:60f2ab7f11aae1649a1c83b0234e7413bdfcaf47ae5487384e7ff0137db0f342

Observation 0fc5b3ae-d75f-45cc-8f7a-b68972dde19f · outbound

This paper cites Brown, B.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Brown, B

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:26.290308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:26.290308Z digest=sha256:e2dd6e11edb217c82bf945b0cf5e7b8d3f666fd09da3813712b55b41c535bfcb

Observation 967b595e-4b66-4fef-80ee-eea36bd4f5f2 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:35.840032Z

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=2026-08-06T16:54:26.434940Z digest=sha256:f13323febc20110d05ff17bc6221e35e985c5a3eb46d5fc101b30204dcdbe8f8

Observation 8dc72f5b-4c4e-4e73-880a-625793c53262 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:35.573940Z

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=2026-08-06T16:54:26.588710Z digest=sha256:345e3434865f8c5ab3b4db38ea4e639c5f65e66a1db0314d1ee6818e01511bda

Observation 13bf518e-69fb-47eb-9727-0096ac2e3537 · outbound

This paper cites Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities

Reference 8

Resolution
verified exact
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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=2026-08-06T16:54:26.744749Z digest=sha256:32faa10006b3cee737537084306586436dd40e5e5d96c9674eef42bf8bb4fed7

Observation a1a8d904-7bc2-434c-bf2f-838112bb689c · outbound

This paper cites Duchi, S.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Duchi, S

Reference 9

Resolution
verified fuzzy
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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=2026-08-06T16:54:26.885769Z digest=sha256:f3feb5f5cdf443b4e9f2829adaddc5024da94efaf66dd519c9c6fe2dfa757fa7

Observation 5a2e13ad-8e1a-4616-8bce-9cbf9a5ae826 · outbound

This paper cites Hwang, Y.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Hwang, Y

Reference 10

Resolution
verified fuzzy
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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=2026-08-06T16:54:27.014573Z digest=sha256:8eb66be70dfb8296f7e1fb9a7a5063524ef26b21375424f125018119e3c44297

Observation 5c350660-ace2-48b1-999c-8d10af4a2e92 · outbound

This paper cites Killamsetty, X.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Killamsetty, X

Reference 11

Resolution
verified fuzzy
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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=2026-08-06T16:54:27.185893Z digest=sha256:25810ff452ec64be66568d78d383036915f1ba3011e98b48e43ecb9a8bd35798

Observation cc43f4bd-4338-4409-9f86-7eca1f98616b · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:34.640857Z

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=2026-08-06T16:54:27.317722Z digest=sha256:e81804952fa75f6729888a7d23c9408463df99926f3d254f245ce9fee75bea26

Observation 52958cfb-130f-4a68-b58c-eeef36058f1f · outbound

This paper cites Kindermann and J.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Kindermann and J

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:54:34.382229Z

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=2026-08-06T16:54:27.438105Z digest=sha256:838eed6ccda880ab7bb43cd3678d999d0529b0082db69cd26e8510027fc27dda

Observation b6a731ef-4019-4643-853e-4f233d05a1d1 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:27.561840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:27.561840Z digest=sha256:1c5c6111efa54ecdffb4ba3eee0cbefabc7d2ed8db5d25ed1e0965098b13bf97

Observation 5fb6e712-1a87-4439-9d06-00ef19be8653 · outbound

This paper cites Kuhn and A.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Kuhn and A

Reference 15

Resolution
verified fuzzy
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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=2026-08-06T16:54:27.698857Z digest=sha256:48f65bcf6de5f8ec3dff13102f8f0f1b057c38588a2a77921f0f8f0c77933151

Observation 05df662c-0994-415a-bc30-a197e0e01a3a · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:27.826638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:27.826638Z digest=sha256:c36922ec8507e94e1a3dd489595c1a4f44cb280ee652b7e075f6467c4a4b7d38

Observation 111e95f3-43c0-47a8-8f13-77ceac3ef911 · outbound

This paper cites Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:27.921929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:27.921929Z digest=sha256:bfed14c0f150a8292bee01e877a91c9229782a80f9a1b7f4c8ab8ffe2d925aa2

Observation 1dc607a7-58cc-4395-a982-852553487513 · outbound

This paper cites RegMix: Data Mixture as Regression for Language Model Pre-training.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning RegMix: Data Mixture as Regression for Language Model Pre-training

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:28.022180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:28.022180Z digest=sha256:ff00e22a27227e00a0c3562fcff86d0861ff05257c7763b93da96bba2888586e

Observation eb09f32b-6092-4a17-9746-7276e7f659e5 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 19

Resolution
unresolved
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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=2026-08-06T16:54:28.099799Z digest=sha256:10b2a0e2ce310b9869b720ce7b25e164f5add2cfa1b67d4ce76e5cd949866386

Observation 44876557-a577-47f2-bcc0-d053e24297b5 · outbound

This paper cites Longpre, L.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Longpre, L

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:54:33.786577Z

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.

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Observation 15071aaa-eb02-42cb-abec-2b1e6955a5ab · outbound

This paper cites D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:28.284721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:28.284721Z digest=sha256:ede2aacaddde981cb518776575dde2360009dd5b26de3557be7b8e4ffb061470

Observation 98fe3553-768b-4d52-97ae-32970e91bc89 · outbound

This paper cites Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:28.347464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:28.347464Z digest=sha256:79a6bfcfdf169a0797c236ac681ecba98fdc0f2d15abc5510806d69d5982ad18

Observation f79e9035-ee4f-49ed-85e2-dd686d5bbc4c · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:33.624615Z

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.

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Observation a0e79e35-113a-4db4-8d43-c0aa7a583d9b · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:28.510290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:28.510290Z digest=sha256:5957b4eea37a901b5ae9ce71075f0c200d6b9afb0b9ebae2ab8b67d4e65cca57

Observation e51f19fc-f3a0-495e-89f2-12621d0bb678 · outbound

This paper cites Multitask Prompted Training Enables Zero-Shot Task Generalization.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Multitask Prompted Training Enables Zero-Shot Task Generalization

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:28.618124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:28.618124Z digest=sha256:7b3524e4cbe253cee3af9d91bc987136a430c62ebdfdfd3c69bba24c28283678

Observation bf489a80-e78e-45c6-9324-1afd2fb5dccd · outbound

This paper cites Sener and S.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Sener and S

Reference 26

Resolution
verified fuzzy
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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=2026-08-06T16:54:28.746369Z digest=sha256:76fba6541b341760dae6271728d21ca65daacfca3e770e9505bd06a968b3b7d5

Observation ddaba4b7-03d2-486b-ac8f-09775e93a87f · outbound

This paper cites Toneva, A.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Toneva, A

Reference 27

Resolution
verified fuzzy
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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=2026-08-06T16:54:28.930033Z digest=sha256:d78c3841db8097aea50287c7a5208fdbb82180dacb4e97f8212a5a6027afde5d

Observation 23eee2aa-5ff1-404e-9351-85fc2d7493fd · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning LLaMA: Open and Efficient Foundation Language Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:29.078509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:29.078509Z digest=sha256:9429ff45dbb34540abc4fd3da27757e8337ea5efdf0982239c3f9d3932c74bd8

Observation d4b8e00a-b35f-4360-b686-2ab00f27e59f · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:33.066821Z

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=2026-08-06T16:54:29.175597Z digest=sha256:5a99d4b125a0db659f5918cd1e580d963eb839be7346acce2f1289ff725e4d29

Observation 6a32e556-054c-46b4-ac60-eac0fe8a27ad · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:32.904128Z

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=2026-08-06T16:54:29.298509Z digest=sha256:954960d6337f8d7b3c34e2b86394d9b198a69d6d727cf81d922f730ba70797cb

Observation f438e3b8-bffa-462f-86ce-445d8341f032 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:32.658427Z

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=2026-08-06T16:54:29.391324Z digest=sha256:a4dfed30f9bcf3198799ac09194502b6c627bc64f645362fd1b2cf6f15c310ce

Observation e85e89b3-4781-4538-b153-56eca92263d8 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:29.470800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:29.470800Z digest=sha256:58d7b81c84ef2f6a787d6fb30dc3a6e699dcae442a65c17e0c57c5f02f5fdc61

Observation e66f0797-0b00-41c3-a8e8-2d520abead57 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:32.417336Z

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=2026-08-06T16:54:29.560158Z digest=sha256:0a3fc1d223b57fc1c0de68b6e72b7cf8bd4a661b93ae61c886e6ec92355c51e8

Observation 2a1520d2-c10f-4f66-a254-95f6c64b8ae3 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:54:32.235648Z

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=2026-08-06T16:54:29.624281Z digest=sha256:9edbd9608367f7e6e1093325aca74f0d2e1f615d723f9901f70ab72d27427337

Observation 2bc21424-e7e7-4801-a534-5b396e0b711b · outbound

This paper cites Qwen2 Technical Report.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Qwen2 Technical Report

Reference 35

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unresolved
no resolver link, observed 2026-08-06T16:54:29.696081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:29.696081Z digest=sha256:5d1018340b07a4c0d4ddc412394f450561b60cba887a4fcb3fd93da626d9da2e

Observation 084373b5-9dd5-484a-83a1-af8df1f99c39 · outbound

This paper cites Zhang, J.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Zhang, J

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:54:31.992601Z

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.

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Observation f2bba78c-4207-4016-9753-2eb7f1726fbd · outbound

This paper cites Zheng, R.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Zheng, R

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:54:31.768412Z

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.

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Observation 9c06241e-4886-497f-84d2-fc965b9a1d10 · outbound

This paper cites write newline.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning write newline

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:29.948653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:29.948653Z digest=sha256:9cfcf1090b7ec05a42be93dd77fb7447aed2c337250a2197a45c705b9f64f118

Observation b481338f-a42a-4174-bbf0-520c1966a5cf · outbound

This paper cites @esa (Ref.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning @esa (Ref

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:30.010395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:30.010395Z digest=sha256:1694bf7eb42c7b75ac3c5eed0839e106ded1e68c8f5c30b3cc459a5676b4b9ca

Observation 94a6de6b-3e78-4e1b-a403-c3d2d0d7bc06 · outbound

This paper cites an unresolved cited work.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:30.093229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:30.093229Z digest=sha256:8a807cefec6c8d5a2266fdd023e53947921adaea6a799588d1897e1a0b933283

Observation 9469ca55-e591-41bf-a5f4-e2a03710a7bd · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning , " * write output.state after.block = add.period write newline

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:54:31.515414Z

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=2026-08-06T16:54:30.191849Z digest=sha256:208e13ab5a8e221764058c8a92d5b1a7950d7c7ae29e5ff44ad8c4eb1b177fd7

Observation 37ab4773-d7ea-4833-8d47-43ced6d387b7 · outbound

This paper cites write newline.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning write newline

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T16:54:30.254554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:54:30.254554Z digest=sha256:967fca5bd45912b57cf7457ff7136c29824d5fbb454653f1451ad05562f841f9

Observation 4fa80da5-750e-4a4b-b253-ddfeecd5eea5 · outbound

This paper cites sibling model.

Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning sibling model

Reference 43

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T16:54:30.971305Z

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=2026-08-06T16:54:30.317387Z digest=sha256:f32825b9bec42e96237002442bc1e46f9fb489ebc8974fd4a37c429c35aaa15f

Pith citing papers

No inbound Pith citation observations are available.