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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-08T06:32:00.761636+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

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

source=arxiv_source observed=2026-08-06T16:54:25.810159Z digest=sha256:2f7cda7f09b982355eb653b61926aa72f1ddb7debe3a75d60b4850251dd051e8

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

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

source=arxiv_source observed=2026-08-06T16:54:25.885810Z digest=sha256:65723c2b271407f52f5ee36fe9fedc5f5872ae20e4a08c58a2f3f24cd56fb01f

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

source=arxiv_source observed=2026-08-06T16:54:26.041440Z digest=sha256:141e5052ef24ac8921f29a277315f3968559d35c30eefa385f1eee9ccf4066da

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

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

source=arxiv_source observed=2026-08-06T16:54:26.434940Z digest=sha256:f4058b159102f25c9c688771150f59cfba3a71974f7e6ba22e87ff1084aad32c

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

source=arxiv_source observed=2026-08-06T16:54:26.588710Z digest=sha256:215c3e777b0b91f611924c5d1597b0840c27942129b537f3ab78803d1be1c326

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
local_arxiv, observed 2026-08-06T16:54:31.248787Z

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=2026-08-06T16:54:26.744749Z digest=sha256:985a528315113187ea3da0d764cd3710b314f35e2bdf10b887725e4190104d49

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

source=arxiv_source observed=2026-08-06T16:54:26.885769Z digest=sha256:7942de483f221c87c4e4050b49c3ac67b8f13c38cdcdb0ff2fd3f81f53a87c41

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

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

source=arxiv_source observed=2026-08-06T16:54:27.185893Z digest=sha256:fd996a3ee9cc6cd3e46decc6ac664a9b8918e284c7b06857bdf5450bd789077a

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
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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=2026-08-06T16:54:27.317722Z digest=sha256:73f21711014eecdd32d2304ddc2c3eaf60757d0f6bc35b03eb695c9eea843fdd

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
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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=2026-08-06T16:54:27.438105Z digest=sha256:45c76bd802a6be1e6f41495703e066d6cce8ace13c2fdbaf45fe2fc7dab1e62c

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
raw_fallback, observed 2026-08-06T16:54:34.180438Z

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=2026-08-06T16:54:27.698857Z digest=sha256:0b8bfb0204ae021f48216565d390f875aab20e15c809d616fa043f6bc8aaff51

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=sha256:20943f2b9b6aec343b756cfa727a1c50f07bc48a93b6da07353125ca46b9b608

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

source=arxiv_source observed=2026-08-06T16:54:28.099799Z digest=sha256:6b96330cf73d4fd12c99adabe16e0d9a189024bdd8fc048b7c7b4acd22f6feaf

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
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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=2026-08-06T16:54:28.198450Z digest=sha256:610d44bcf6be875136ab868cf72d065aa156eaf9829566a4a4f9983d40565606

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
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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
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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 2026-08-08T06:32:00.761636+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

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

source=arxiv_source observed=2026-08-06T16:54:28.746369Z digest=sha256:86d36a4dca2343aef460b9215704e60142b8b3b5635f4831043ce122d68945ef

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

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

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

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

source=arxiv_source observed=2026-08-06T16:54:29.391324Z digest=sha256:ab3849aaa0e6062c56fcebe0034f0bde49bb7d31181cbaef584c23161bcbeb0b

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

source=arxiv_source observed=2026-08-06T16:54:29.560158Z digest=sha256:6639f73e4589b592de4bcd0bd52e02b6c1b856238c8de6120a1aa808851e0a7f

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

source=arxiv_source observed=2026-08-06T16:54:29.624281Z digest=sha256:bfec28111e9b18f64d6239c154cfe6180ee8fe21e38307679519a7c0837096ce

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

source=arxiv_source observed=2026-08-06T16:54:30.191849Z digest=sha256:c0d771a9b4a0c6bdd13d2b6727c77cfeac8be99f2b4866b149c298ef6b8bbefa

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

source=arxiv_source observed=2026-08-06T16:54:30.317387Z digest=sha256:35fae2f8f896658177a4598153ea5adf18c6a818e12a944e37271c5cd4e96de3

Pith citing papers

No inbound Pith citation observations are available.