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Paper Citation Record · LEDGER

Multi-Task Learning as a Bargaining Game

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2202.01017.

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

pith.paper-citation-record.v1
2202.01017 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:39:32.905572Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T13:49:51.448499Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dad9d799-b8bb-48cc-9ceb-d2cb4ec2927c · inbound

Multi-objective Deep Learning: Taxonomy and Survey of the State of the Art cites this paper.

Multi-objective Deep Learning: Taxonomy and Survey of the State of the Art Multi-Task Learning as a Bargaining Game

Reference 129

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:19:51.757645Z digest=sha256:aa4135de68d9005b76b67e977d543512fb64a3cca76709aac8c30094d07854a6

Observation ff101f43-c81a-4150-b1aa-52733e410d7a · inbound

Diffusion-based Visual Anagram as Multi-task Learning cites this paper.

Diffusion-based Visual Anagram as Multi-task Learning Multi-Task Learning as a Bargaining Game

Reference 37

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no resolver link, observed 2026-08-11T23:15:26.592385Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:15:26.592385Z digest=sha256:7b7800aa07da5b4fab81e8998327e734ce3528b2593d6f86128a0d1c81cf6495

Observation 66d38833-64b3-4c8b-a16b-3c9d9499e18b · inbound

PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization cites this paper.

PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization Multi-Task Learning as a Bargaining Game

Reference 36

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source=arxiv_source observed=2026-08-11T15:34:30.291436Z digest=sha256:4a634e4efbfe8ad4fae50885f65d01c3c268f07dc57fbb590f222c618b34eb7b

Observation 306839fb-82f1-4450-9832-ed3f89d9d14e · inbound

Semi-Supervised Learning for AVO Inversion with Strong Spatial Feature Constraints cites this paper.

Semi-Supervised Learning for AVO Inversion with Strong Spatial Feature Constraints Multi-Task Learning as a Bargaining Game

Reference 45

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no resolver link, observed 2026-08-10T14:21:46.939066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:21:46.939066Z digest=sha256:13e68460d6f57c7e353dbaecac6e71a5ba9c676b35381d1f26476e2259dbb556

Observation b7ab6734-944b-49c7-b94a-00b79bdac299 · inbound

Fantastic Multi-Task Gradient Updates and How to Find Them In a Cone cites this paper.

Fantastic Multi-Task Gradient Updates and How to Find Them In a Cone Multi-Task Learning as a Bargaining Game

Reference 17

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no resolver link, observed 2026-08-09T19:55:16.872799Z

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source=arxiv_source observed=2026-08-09T19:55:16.872799Z digest=sha256:258aae9169879508b6744c31a42459404bc151d24579fdff990836bbda359a74

Observation 9a1e5879-c521-45b6-917c-5dbe6f8d4c9c · inbound

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts cites this paper.

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts Multi-Task Learning as a Bargaining Game

Reference 45

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no resolver link, observed 2026-08-08T16:20:38.309736Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:20:38.309736Z digest=sha256:de4aedd20b3284399c7ecb98f0eec8e278c2089b0ce90c42baa79ddeb49b0eed

Observation 1fa80b2f-9c0c-4312-ad17-8504c1af612b · inbound

GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining cites this paper.

GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining Multi-Task Learning as a Bargaining Game

Reference 28

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no resolver link, observed 2026-08-07T14:04:24.809400Z

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source=arxiv_source observed=2026-08-07T14:04:24.809400Z digest=sha256:f78ef4c5c5410e8626ac3c0b352b9002a261d26399dd09ca0539ec5d3402f1b8

Observation cb43ef4e-dd2a-4a6f-8eef-ad44859374ce · inbound

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class cites this paper.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Multi-Task Learning as a Bargaining Game

Reference 33

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no resolver link, observed 2026-08-07T12:14:51.309084Z

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source=pdf_text observed=2026-08-07T12:14:51.309084Z digest=sha256:cfbf7c75f8a84cc4dfc4fe029b8f6e2ecdea9a07ec502a730b6631dd6313e9b1

Observation b91981d5-0b12-4548-ad16-4ee0feea8301 · inbound

AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs cites this paper.

AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs Multi-Task Learning as a Bargaining Game

Reference 34

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:08:31.464747Z digest=sha256:7fb2cd4aaffb29ee1976d4261bc7f76995dfb2a20a2de082efd9c7019723762b

Observation 3a885e73-e46e-44de-937d-a8f1211fb382 · inbound

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping cites this paper.

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping Multi-Task Learning as a Bargaining Game

Reference 74

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source=pdf_text observed=2026-08-07T11:32:10.907531Z digest=sha256:05fd91a3a369bc74e58a47f675b1ec090b11556c0c3433d1d64d1977e5d03729

Observation 8cd3df7d-aa35-4f24-bdaa-c5837a359043 · inbound

Control and Realism: Best of Both Worlds in Layout-to-Image without Training cites this paper.

Control and Realism: Best of Both Worlds in Layout-to-Image without Training Multi-Task Learning as a Bargaining Game

Reference 28

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no resolver link, observed 2026-08-15T19:39:32.905572Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:39:32.905572Z digest=sha256:fc997857ac9dcce9ff37014875335c1d2f837adc5eb9bfbb75bc24c532582939

Observation e164a951-0045-472d-889a-e6d041845cc0 · inbound

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models cites this paper.

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models Multi-Task Learning as a Bargaining Game

Reference 31

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no resolver link, observed 2026-08-06T20:29:50.887993Z

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source=pdf_text observed=2026-08-06T20:29:50.887993Z digest=sha256:7621fb8d109f3b6bae5842816a2241ec9ab9ab865c6a4e553d41197810ac6ffd

Observation b74c2b27-86ee-4837-8382-7abd244cdc7d · inbound

Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planning cites this paper.

Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planning Multi-Task Learning as a Bargaining Game

Reference 45

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no resolver link, observed 2026-08-06T19:44:54.197062Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:44:54.197062Z digest=sha256:b44a129435c8f7418f42ad994e6e0b7370984ecc71ebf5394913b1e1fce0a36d

Observation 5c2ef916-3732-4d8a-8444-c2fe7656f3e6 · inbound

Resolving Token-Space Gradient Conflicts: Token Space Manipulation for Transformer-Based Multi-Task Learning cites this paper.

Resolving Token-Space Gradient Conflicts: Token Space Manipulation for Transformer-Based Multi-Task Learning Multi-Task Learning as a Bargaining Game

Reference 45

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no resolver link, observed 2026-08-06T18:48:35.755632Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:48:35.755632Z digest=sha256:7167535ae8a3553944a679bafec711fd6077ac224f4aed812245fb095fdafaf4

Observation 8e7df026-1ebd-4a3a-b7dd-49624783a986 · inbound

Synchronizing Task Behavior: Aligning Multiple Tasks during Test-Time Training cites this paper.

Synchronizing Task Behavior: Aligning Multiple Tasks during Test-Time Training Multi-Task Learning as a Bargaining Game

Reference 35

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source=pdf_text observed=2026-08-06T18:38:50.707754Z digest=sha256:2c085267d65bb261a8536968e5f089b7cd2b3783bced407ea8e400c93e055b18

Observation 87b76ee2-2401-4d95-b3d9-4bdc3e77cafe · inbound

AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics cites this paper.

AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics Multi-Task Learning as a Bargaining Game

Reference 34

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no resolver link, observed 2026-08-05T18:54:01.498708Z

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source=pdf_text observed=2026-08-05T18:54:01.498708Z digest=sha256:1d90a1f9de45b2df05bfa11a16cab31ab6b4af0070782c4393bc2c7cbeb20635

Observation cf4b89d2-fd4f-4837-b675-481645e88131 · inbound

Enhancing Mamba Decoder with Bidirectional Interaction in Multi-Task Dense Prediction cites this paper.

Enhancing Mamba Decoder with Bidirectional Interaction in Multi-Task Dense Prediction Multi-Task Learning as a Bargaining Game

Reference 23

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no resolver link, observed 2026-08-15T16:50:25.112828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:50:25.112828Z digest=sha256:5280ba8d18f7bbd3e785c66801b96f53a45755f42fde5041ce4cb8bd6fe55f43

Observation 0bd565d1-b27f-49aa-bf7f-c56b1d80d968 · inbound

Simple Optimizers for Convex Aligned Multi-Objective Optimization cites this paper.

Simple Optimizers for Convex Aligned Multi-Objective Optimization Multi-Task Learning as a Bargaining Game

Reference 29

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no resolver link, observed 2026-08-05T05:05:47.756478Z

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source=arxiv_source observed=2026-08-05T05:05:47.756478Z digest=sha256:1a31e35a94199dd27a6aa75ae2f82bb55503d26b3ff359f542aaa7b2d4587f57

Observation a002396a-c5d9-4947-9abf-d73bc374588d · inbound

Constraint-Aware Reinforcement Learning via Adaptive Action Scaling cites this paper.

Constraint-Aware Reinforcement Learning via Adaptive Action Scaling Multi-Task Learning as a Bargaining Game

Reference 20

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verified exact
arxiv_id, observed 2026-05-18T07:41:03.389911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-18T07:36:28.841586Z digest=sha256:285c58570be750b74ff0ab8e2ca1a3151d72ad4321569dae044f975782615b32

Observation 4c21e61d-c0cc-44d9-8b55-5d6f09c4e70f · inbound

Expert Merging in Sparse Mixture of Experts with Nash Bargaining cites this paper.

Expert Merging in Sparse Mixture of Experts with Nash Bargaining Multi-Task Learning as a Bargaining Game

Reference 46

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no resolver link, observed 2026-08-04T09:21:49.346348Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:21:49.346348Z digest=sha256:39ef8b7418593fee5333a586d80662a879a257e265ae0fa30d43a95f6a25c137

Observation 16410133-b044-457e-95c4-5ea6f41d3b07 · inbound

GreenRFM: Learning a resource-efficient radiology vision-language foundation model via supervision-centric pre-training cites this paper.

GreenRFM: Learning a resource-efficient radiology vision-language foundation model via supervision-centric pre-training Multi-Task Learning as a Bargaining Game

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T13:49:27.721549Z digest=sha256:d0c366e6b028493c41134e7c51e42f9fa033e8e5458ec121dc19f8d73e206dc4

Observation 6829bdf3-132d-4900-b8fd-8c072007da90 · inbound

Delve into the Applicability of Advanced Optimizers for Multi-Task Learning cites this paper.

Delve into the Applicability of Advanced Optimizers for Multi-Task Learning Multi-Task Learning as a Bargaining Game

Reference 7

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verified exact
arxiv_id, observed 2026-05-11T08:20:59.030964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T16:42:48.902337Z digest=sha256:aba02b51c63f2f10c91511e621ab1e3b3a7b0eeaefc9f2590ca9f029919fd0e3

Observation 249538d1-35c6-44cc-8325-ee0258d57a20 · inbound

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling cites this paper.

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling Multi-Task Learning as a Bargaining Game

Reference 223

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metadata mismatch
arxiv_id, observed 2026-05-15T03:08:59.521004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-15T03:05:36.871497Z digest=sha256:635801b89464a12482d028b4b79c7db296b6e4af1ec38f43ffdb8d611676cb00

Observation f28aad78-5198-4f9d-ae1d-08459564cf46 · inbound

When Robots Sleep: Offline Skill Consolidation for Shared-Policy Robot Learning cites this paper.

When Robots Sleep: Offline Skill Consolidation for Shared-Policy Robot Learning Multi-Task Learning as a Bargaining Game

Reference 4

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arxiv_id, observed 2026-07-03T20:58:57.551497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-27T01:04:01.317563Z digest=sha256:180ca5399682ea4912c9fe191892d1e50371ff41ad1bc59dc450b44928d82723

Observation 01f90d3e-fc03-4092-8a41-2b236980bec0 · inbound

DanceOPD: On-Policy Generative Field Distillation cites this paper.

DanceOPD: On-Policy Generative Field Distillation Multi-Task Learning as a Bargaining Game

Reference 70

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verified exact
arxiv_id, observed 2026-07-04T13:49:51.450413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-26T04:55:42.018348Z digest=sha256:7aaefd0a49f9d3571a3aa95ca3aba5d563a1a010120241b597cdd066536b494b

Observation 01c3f9cd-48c5-486a-a6f1-31517dc91c21 · inbound

DanceOPD: On-Policy Generative Field Distillation cites this paper.

DanceOPD: On-Policy Generative Field Distillation Multi-Task Learning as a Bargaining Game

Reference 70

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source=pdf_text observed=2026-07-12T11:44:54.717393Z digest=sha256:c3b0c1eb41bc329a40620c222f5f437c733b16e7eac50e346218a962a8e1c6a4

Observation 7ec51da7-6473-4494-bb2f-6e007ad2372d · inbound

Rosetta: Composable Native Multimodal Pretraining cites this paper.

Rosetta: Composable Native Multimodal Pretraining Multi-Task Learning as a Bargaining Game

Reference 44

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verified exact
arxiv_id, observed 2026-07-02T15:47:05.746292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-02T15:41:13.556849Z digest=sha256:a2d8868129680af248c75b7aa1972b95cc1d9377a218254728b5cc964cbdea4f

Observation 21c71261-88d4-4fa8-b19b-c396ef0f6bd3 · inbound

S2T-RLHF: Hierarchical Credit Assignment for Stable Preference-Based RLHF cites this paper.

S2T-RLHF: Hierarchical Credit Assignment for Stable Preference-Based RLHF Multi-Task Learning as a Bargaining Game

Reference 40

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source=pdf_text observed=2026-08-02T13:58:44.111762Z digest=sha256:2d456c6389af0c0116b9bc15258af217e7518a78181e2965e60d29ebf3112919

Observation 8a52db67-5f6b-420f-b96a-be36983ea991 · inbound

IntHQ: Task-Interactive Hierarchical Query on Dual-Stream Representations for Generative Recommendation cites this paper.

IntHQ: Task-Interactive Hierarchical Query on Dual-Stream Representations for Generative Recommendation Multi-Task Learning as a Bargaining Game

Reference 2018

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no resolver link, observed 2026-08-11T13:48:29.326750Z

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source=pdf_text observed=2026-08-11T13:48:29.326750Z digest=sha256:016480d9afe95f31ee8318afe292987f6469e928124c1c7d82dc7d733201c1e8