Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T13:06:04.651711Z
Paper Citation Record · LEDGER
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning
As of 9 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2507.21049.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
69 of 69 outbound references displayed
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- verified fuzzy56
- unresolved8
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- malformed identifier0
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 70c8d044-001b-40e6-9c73-e94ad130882b · outbound
This paper cites Saliency-regularized deep multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Saliency-regularized deep multi-task learning
Reference 1
- Resolution
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Source-reported events for the cited work
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Observation eaf335c2-0b7b-4f46-9815-9dc6a8334d3c · outbound
This paper cites Fair resource allocation in multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Fair resource allocation in multi-task learning
Reference 2
- Resolution
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Source-reported events for the cited work
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Observation 8dbb8dc9-b794-4595-a539-4d20ba5c0283 · outbound
This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Sparks of Artificial General Intelligence: Early experiments with GPT-4
Reference 3
- Resolution
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Source-reported events for the cited work
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Observation 458abd22-113e-4052-a2d4-3d4400a678d8 · outbound
This paper cites Multitask learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Multitask learning
Reference 4
- Resolution
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Source-reported events for the cited work
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Observation ac0cc310-cf94-4a1c-b2b5-90ebb87e72c7 · outbound
This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Encoder-decoder with atrous separable convolution for semantic image segmentation
Reference 5
- Resolution
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Source-reported events for the cited work
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Observation 7168f82a-9cc6-463b-93a1-6e9851471e4d · outbound
This paper cites A simple framework for contrastive learning of visual representations.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning A simple framework for contrastive learning of visual representations
Reference 6
- Resolution
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Source-reported events for the cited work
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Observation 99b1524c-3cbb-427b-a120-810eab379af1 · outbound
This paper cites Big self-supervised mod- els are strong semi-supervised learners.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Big self-supervised mod- els are strong semi-supervised learners
Reference 7
- Resolution
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Source-reported events for the cited work
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Observation 812651c6-1d67-45ee-8a3a-4ffbf6d8222e · outbound
This paper cites GradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning GradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks
Reference 8
- Resolution
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Source-reported events for the cited work
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Observation c747eb76-14ab-45fe-a6cd-c50b0ee10e66 · outbound
This paper cites Just pick a sign: Optimizing deep multitask models with gra- dient sign dropout.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Just pick a sign: Optimizing deep multitask models with gra- dient sign dropout
Reference 9
- Resolution
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Source-reported events for the cited work
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Observation 0609e573-5a57-4893-af9d-8c87dedcaf88 · outbound
This paper cites MultiNet++: Multi-stream feature ag- gregation and geometric loss strategy for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning MultiNet++: Multi-stream feature ag- gregation and geometric loss strategy for multi-task learning
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 46ec7f74-a2ef-480e-b154-734a567a5445 · outbound
This paper cites The cityscapes dataset for semantic urban scene understanding.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning The cityscapes dataset for semantic urban scene understanding
Reference 11
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7ad4849a-7203-4c31-9914-510a3a7e3432 · outbound
This paper cites Improvable gap bal- ancing for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Improvable gap bal- ancing for multi-task learning
Reference 12
- Resolution
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Source-reported events for the cited work
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Observation 5ea4d751-8f80-464a-a72c-d06d61ae9cab · outbound
This paper cites Multiple-gradient descent algorithm (MGDA) for multiobjective optimization.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Multiple-gradient descent algorithm (MGDA) for multiobjective optimization
Reference 13
- Resolution
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Source-reported events for the cited work
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Observation cb099413-6861-4af2-a8a9-4be0cef9e938 · outbound
This paper cites Multi-task self- supervised visual learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Multi-task self- supervised visual learning
Reference 14
- Resolution
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Source-reported events for the cited work
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Observation 066b446b-5ad5-487e-8b6d-aec0828e3687 · outbound
This paper cites Miti- gating gradient bias in multi-objective learning: A provably convergent approach.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Miti- gating gradient bias in multi-objective learning: A provably convergent approach
Reference 15
- Resolution
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Source-reported events for the cited work
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Observation a159cafd-9b9b-4de4-861d-e7120a4f71ee · outbound
This paper cites Bootstrap your own latent-a new approach to self-supervised learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Bootstrap your own latent-a new approach to self-supervised learning
Reference 16
- Resolution
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Source-reported events for the cited work
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Observation aee67976-9ec9-4695-bbd2-3468b88f9e2c · outbound
This paper cites Deep residual learning for image recognition.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Deep residual learning for image recognition
Reference 17
- Resolution
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Source-reported events for the cited work
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Observation 2833ab4d-444a-4679-bea2-9fb17d2a6540 · outbound
This paper cites Momentum contrast for unsupervised visual rep- resentation learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Momentum contrast for unsupervised visual rep- resentation learning
Reference 18
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 89792c8a-1355-49e1-890f-60dc670e4069 · outbound
This paper cites MetaBalance: improving multi-task recommendations via adapting gradient magnitudes of aux- iliary tasks.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning MetaBalance: improving multi-task recommendations via adapting gradient magnitudes of aux- iliary tasks
Reference 19
- Resolution
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Source-reported events for the cited work
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Observation 5868a15f-9246-4d0e-9ca8-e97e4ebef714 · outbound
This paper cites Position: The platonic representation hypothesis.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Position: The platonic representation hypothesis
Reference 20
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a055c6bb-bb11-468d-bb17-53bfc9807090 · outbound
This paper cites Rotograd: Gradient ho- mogenization in multitask learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Rotograd: Gradient ho- mogenization in multitask learning
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation 03845565-cf20-4203-b2a4-3c1c9796f89a · outbound
This paper cites Multi-task learning using uncertainty to weigh losses for scene geome- try and semantics.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Multi-task learning using uncertainty to weigh losses for scene geome- try and semantics
Reference 22
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6afb9c1a-5143-4dab-a45e-0a349ebf9912 · outbound
This paper cites Segment any- thing.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Segment any- thing
Reference 23
- Resolution
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Source-reported events for the cited work
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Observation 8ed50528-8bea-4c67-ba9b-62b05ae32d1e · outbound
This paper cites In defense of the uni- tary scalarization for deep multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning In defense of the uni- tary scalarization for deep multi-task learning
Reference 24
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation a007f4db-a894-417c-b65b-f8cd0ecca8be · outbound
This paper cites Unveiling the Backbone-Optimizer Coupling Bias in Visual Representation Learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Unveiling the Backbone-Optimizer Coupling Bias in Visual Representation Learning
Reference 25
- Resolution
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Source-reported events for the cited work
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Observation 4173551a-7989-4ac1-bfaa-8454da9cb1ab · outbound
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Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Unresolved cited work
Reference 26
- Resolution
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Source-reported events for the cited work
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Observation 05d0b028-0eb5-4744-b50f-471d184d1128 · outbound
This paper cites Libmtl: A python library for deep multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Libmtl: A python library for deep multi-task learning
Reference 27
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 7e0ae034-bcdf-463b-8dfa-27ea4660fa44 · outbound
This paper cites Rea- sonable effectiveness of random weighting: A litmus test for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Rea- sonable effectiveness of random weighting: A litmus test for multi-task learning
Reference 28
- Resolution
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Source-reported events for the cited work
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Observation 3d6801e5-8b82-4ee3-a82d-57a86ec44efd · outbound
This paper cites Rea- sonable effectiveness of random weighting: A litmus test for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Rea- sonable effectiveness of random weighting: A litmus test for multi-task learning
Reference 29
- Resolution
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Source-reported events for the cited work
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Observation 095f5c26-23d1-469e-882b-ffe51b30351a · outbound
This paper cites Dual-balancing for multi-task learning, 2024.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Dual-balancing for multi-task learning, 2024
Reference 30
- Resolution
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Source-reported events for the cited work
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Observation 85e2ef15-2544-4723-8039-ff6d0a847c21 · outbound
This paper cites Smooth tchebycheff scalarization for multi-objective optimization.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Smooth tchebycheff scalarization for multi-objective optimization
Reference 31
- Resolution
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Source-reported events for the cited work
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Observation f9c69a3f-8c5d-48ca-9664-2c786ddb77ed · outbound
This paper cites Conflict-averse gradient descent for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Conflict-averse gradient descent for multi-task learning
Reference 32
- Resolution
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Source-reported events for the cited work
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Observation 2034c07b-7bd7-4492-b189-20e165e30469 · outbound
This paper cites Famo: Fast adaptive multitask optimization.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Famo: Fast adaptive multitask optimization
Reference 33
- Resolution
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Source-reported events for the cited work
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Observation 8d1f6183-3f5e-42c5-ab82-95335a8064ff · outbound
This paper cites Towards impartial multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Towards impartial multi-task learning
Reference 34
- Resolution
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- raw_fallback, observed 2026-08-06T13:06:05.979830Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 1705f94e-40ae-44ac-86e7-966be3759ad5 · outbound
This paper cites an unresolved cited work.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Unresolved cited work
Reference 35
- Resolution
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Source-reported events for the cited work
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Observation 544d8e17-f3e9-4b1c-b387-2075f43790cb · outbound
This paper cites Auto-lambda: Disentangling dynamic task relation- ships.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Auto-lambda: Disentangling dynamic task relation- ships
Reference 36
- Resolution
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Source-reported events for the cited work
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Observation bcc27948-1f03-413f-92fd-8b64f7244fad · outbound
This paper cites Unified-io: A unified model for vision, language, and multi-modal tasks.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Unified-io: A unified model for vision, language, and multi-modal tasks
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.910406Z
Source-reported events for the cited work
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Observation 2f9f0d25-7148-46ba-ba9e-94bacbce6dfc · outbound
This paper cites Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.880650Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7c1bbaea-efa4-4d56-b9ad-27836ac4c882 · outbound
This paper cites Modeling task relationships in multi-task learning with multi-gate mixture-of-experts.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Modeling task relationships in multi-task learning with multi-gate mixture-of-experts
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.856128Z
Source-reported events for the cited work
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Observation 8f764880-56a3-48e2-a7ea-aa85796485a1 · outbound
This paper cites Entire space multi-task model: An effective approach for estimating post-click conversion rate.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Entire space multi-task model: An effective approach for estimating post-click conversion rate
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.824364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 879bc8b7-d5f3-428b-82e1-42400dae6fe6 · outbound
This paper cites Traditional and heavy tailed self regularization in neural network models.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Traditional and heavy tailed self regularization in neural network models
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.796684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 2f37445e-2977-4c60-9d39-fa57ea70953e · outbound
This paper cites MTAdam: Automatic balancing of multiple training loss terms.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning MTAdam: Automatic balancing of multiple training loss terms
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.773089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 431dcaf0-f583-461c-8f6c-d4529a33d158 · outbound
This paper cites Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on Light-Weighed Backbones and Effective Measurement of Multi-Task Learning Challenges by Feature Disentanglement.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on Light-Weighed Backbones and Effective Measurement of Multi-Task Learning Challenges by Feature Disentanglement
Reference 43
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:06:04.937343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 75edee3c-b404-45b6-8376-38cc090780e5 · outbound
This paper cites Martin and Michael W.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Martin and Michael W
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.748990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 90262e68-190e-465d-8252-1f50f7d7b534 · outbound
This paper cites Implicit self- regularization in deep neural networks: Evidence from ran- dom matrix theory and implications for learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Implicit self- regularization in deep neural networks: Evidence from ran- dom matrix theory and implications for learning
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.719501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 617b2596-c013-4c16-8582-f4d13c4f73ff · outbound
This paper cites Predicting trends in the quality of state-of-the-art neural net- works without access to training or testing data.Nature Com- munications, 12(1):4122, 2021.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Predicting trends in the quality of state-of-the-art neural net- works without access to training or testing data.Nature Com- munications, 12(1):4122, 2021
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.686626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d94c159e-186c-4d94-af8f-3145589da572 · outbound
This paper cites Cross-stitch networks for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Cross-stitch networks for multi-task learning
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.651790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation cb9c1ac4-02fd-44c1-a01e-72d23da6ba78 · outbound
This paper cites Can Optimization Trajectories Explain Multi-Task Transfer?.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Can Optimization Trajectories Explain Multi-Task Transfer?
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:06:04.870268Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0343d8ac-98d2-4db4-84b1-e262347322fd · outbound
This paper cites Multi- task learning as a bargaining game.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Multi- task learning as a bargaining game
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.622864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9d1d22f3-58e6-4eda-83be-18da664c06ec · outbound
This paper cites Language models are unsu- pervised multitask learners.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Language models are unsu- pervised multitask learners
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.574005Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 5c8947db-27f3-44dc-abf4-09f3d7fb45ee · outbound
This paper cites Latent multi-task architecture learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Latent multi-task architecture learning
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.535648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 88771dcc-f67f-4ded-81a2-37a77a7a1527 · outbound
This paper cites Adapting visual category models to new domains.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Adapting visual category models to new domains
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.495439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c5d8959f-31f3-4f7a-914f-c256f4dba19c · outbound
This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Grad-cam: Visual explanations from deep networks via gradient-based localization
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:06:04.489443Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 61e86221-88e4-4513-aaf8-7a2337dc1d74 · outbound
This paper cites Multi-task learning as multi-objective optimization.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Multi-task learning as multi-objective optimization
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.400700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ea5d10d6-7cf1-40be-8132-b9971c612fad · outbound
This paper cites Independent component alignment for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Independent component alignment for multi-task learning
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.353616Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 66e3c54e-52e4-4130-bda3-19497df7d3ad · outbound
This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:06:04.521076Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9957492c-597b-4d8e-8b6b-40dc31ed30ca · outbound
This paper cites GO4Align: Group Optimization for Multi-Task Alignment.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning GO4Align: Group Optimization for Multi-Task Alignment
Reference 57
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:06:04.786699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9d29d92b-c17e-4e1a-b65a-71154682e705 · outbound
This paper cites Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:06:04.533911Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation add72438-13ab-465e-8258-be3b8f7d7b8a · outbound
This paper cites Indoor segmentation and support inference from RGBD images.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Indoor segmentation and support inference from RGBD images
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.315388Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation bbd4a819-4655-4b18-a747-64dd731eb8e5 · outbound
This paper cites Which tasks should be learned together in multi-task learning? In International conference on machine learning, pages 9120–9132.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Which tasks should be learned together in multi-task learning? In International conference on machine learning, pages 9120–9132
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.283789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f63a16f0-3b70-4cac-a56f-af21a82344e0 · outbound
This paper cites Progressive layered extraction (ple): A novel multi-task learning (mtl) model for personalized recommendations.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Progressive layered extraction (ple): A novel multi-task learning (mtl) model for personalized recommendations
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.258411Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 082f0a24-1017-4c7f-831a-878be9ba166f · outbound
This paper cites Deep hashing network for unsupervised domain adaptation.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Deep hashing network for unsupervised domain adaptation
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.220897Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 67737ff5-5b94-4a9c-998a-a23aa5517b77 · outbound
This paper cites Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.188074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d29815b6-c9bc-4bdf-a355-6950be5657f7 · outbound
This paper cites Do current multi-task optimization methods in deep learning even help? Advances in neural information processing systems, 35:13597–13609, 2022.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Do current multi-task optimization methods in deep learning even help? Advances in neural information processing systems, 35:13597–13609, 2022
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.153888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ff39cf77-5cdf-4b23-a5c7-ed3ef6692f63 · outbound
This paper cites Cross-task knowledge distil- lation in multi-task recommendation.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Cross-task knowledge distil- lation in multi-task recommendation
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.128069Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 524f9f35-a96a-434b-841f-5858c8977066 · outbound
This paper cites Gradient surgery for multi-task learning.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Gradient surgery for multi-task learning
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.099716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d56f3ba5-7ca3-4dcc-ac48-d8f5d9add21d · outbound
This paper cites A survey on negative transfer.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning A survey on negative transfer
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.063704Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 719da8d5-07f3-4fc8-bc30-811e4ec7cb52 · outbound
This paper cites Rep-MTL w/o CA.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Rep-MTL w/o CA
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:06:05.038689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 1299cea7-3ad3-4982-9a4a-c0f9b3367ac5 · outbound
This paper cites an unresolved cited work.
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Unresolved cited work
Reference 2022
- Resolution
- parse uncertain
- raw_fallback, observed 2026-08-06T13:06:05.601707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.