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Paper Citation Record · LEDGER

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

As of 19 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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:25.810159Z digest=sha256:2ce8bd1f97a32948d3382c113049ec42c3bffb684ab287180b8f4c3dcaf69ad1

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:25.885810Z digest=sha256:e0a80e1622b000d24ef9849328d3de8418fd39fec7807c81e5b2bac7c1d0df62

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:26.041440Z digest=sha256:501824fe5fbf4441c9fc57c1a5c234eb308dc679e50ba1ed24d571dbe56b9ab8

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:dd172fd358ff5d120de174d68e4d5cc4c5e38af6ef52aa62a953686e87bcb35e

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=sha256:46dfea6d424c83615e690e068deaa901b5c6b814a8857eb4dc1e289ab06dc727

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:26.434940Z digest=sha256:4b6e49282055d1de3d700e893d9f8cd4afb2d290612952dfee86cccecbc73fad

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:26.588710Z digest=sha256:e2979ae70d70d7dd6a57d0223b00eab7a22fa4da311e54085388665af0389d3e

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:26.744749Z digest=sha256:34f1c4f34c0b2499588cdc283f2f0f3116f704eedd8f56dabf6337b09f5636f4

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:26.885769Z digest=sha256:50344173c86706e22b5784e8adb894da6db4e8d890fd12aff1cbb2e4b7b8c16c

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:27.014573Z digest=sha256:1615ec6aec3000f047f15e506ba45c2a6b3bb6c2c69b4464edf80d23270c3910

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:27.185893Z digest=sha256:66dfb7012a9fb9a3af689dc50125ce4b6bc70a42fbb343940e7352a8fb7d0ee1

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:27.317722Z digest=sha256:ec3da953917ce58dc4bdbe43f3a619e9324c160af8860312a8b7eb5d6783797b

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:27.438105Z digest=sha256:43a1551f6ef13bbb582a7f0f0f26cd229fa4341720b28a78e774db08b1d0c5a6

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=sha256:82c49ea658036aef83f331204225f7c7995b3ede1c49c88ca6b07ec8df820712

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:27.698857Z digest=sha256:6c0f08df793fbc04082754fe3f07baca4a7563324fc11e35c9bf44bdd5298568

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.

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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.

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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=sha256:6cb00ef5afd6cd2e4c88e46d141945e0e85615ea5ef42742a86b9c24181e8fd3

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:28.099799Z digest=sha256:4884c5f77f054dca8dffd8b09092a079144d3967fa143e1204ea4b70d43ca6fd

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:28.198450Z digest=sha256:87f62b6fc0925b0238fb353e21cd8f7c982743c09a40be3857048eaab30e2bce

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:caa2dc610cdc7bafc4ad609555bfd0dc41659a3d857e0b3cdc06ca89cca90b76

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=sha256:6bb5fd5d1b090e409c8156590228b4c02c45e36c96d59b286c94f4d75bc35533

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 2026-08-18T06:34:40.430872+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:a5b75e1af466074fa26e0bdbe11acc63cb604ddc05fc1e16902e367f1fb8f334

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=sha256:6c03477e497fd536763d3674896ccdd020bb98af94431b099a92b4b15b4bbc4a

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:28.746369Z digest=sha256:5c608c579f0d9f1a9ada153b3e4b9eef6c9a70454ae26c471a2fc790531b8bb5

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
raw_fallback, observed 2026-08-06T16:54:33.215210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:28.930033Z digest=sha256:91eda0fe74cda3f7bb29221a23b4635bd52329db13fac3730bfcd498f5da6669

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:a8f0da47788bf4d3a38813554e181d7c525690a89435dec9206563976053bf71

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:29.175597Z digest=sha256:8307972e5e262dd921b2f37c1dabc1fe742c6fa603596ba8b801faa4ee3cda68

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:29.298509Z digest=sha256:d28064a9ad87565a1ccada2b8f4b5ad54cad9e5cdaf61cf0d0644962c3b1cdd1

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:29.391324Z digest=sha256:a592aeaaf9503211442c2d1f1a77d5d757251066c9befd21ea19e7ead1348207

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

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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:e8473c63cc910b83836503b3f315006e0c68a0006e137af95ce424b85f1a298e

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:29.560158Z digest=sha256:bd8ba0d3c86273c58dbf165b54dbf81acf84f098c24036c10f633f92432c7785

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:29.624281Z digest=sha256:a5b23b95b43fde38c02ba8b1db196d2d089c7a0f248f928351178711f1d86363

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:a9d4daef1f5dd10e4118822a097b4d617a7ab0614baa8ea029255934f12714f3

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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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=sha256:5af467d9299e14bed3922d4e96ff30e164e725016581d7a199bf6f09d42e5771

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:dd112f24d67906a589bd19d1d4ef5d0efbb53c6e9df436da57679f6e28d9c236

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=sha256:3c4778e5a8e4b2cd250a4e3cf9700f7fcde21fe81346fe731cf40196fb09fdc2

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:30.191849Z digest=sha256:c0a29eacef91098c3cbaacea5a50e14d7f4309c4f93acbcba3b432cff579deb9

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=sha256:68afe8a856baa7f0a7281dfc99b1243061ed02e4d76a90a056278a9f03127fa9

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:54:30.317387Z digest=sha256:7fee046f850190ea980b3c71735e68902b751ed7acfd47d009782d7fdeecad87

Pith citing papers

No inbound Pith citation observations are available.