Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning | Paper Citation Record

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This paper cites Multi-task learning as multi-objective optimization.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multi-task learning as multi-objective optimization

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This paper cites Gradient surgery for multi-task learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Gradient surgery for multi-task learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Conflict-averse gradient descent for multi-task learning

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This paper cites M3vit: Mixture-of-experts vision transformer for efficient multi-task learning with model-accelerator co-design.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning M3vit: Mixture-of-experts vision transformer for efficient multi-task learning with model-accelerator co-design

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multi-task dense prediction via mixture of low-rank experts

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This paper cites An erudite fine-grained visual classification model.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning An erudite fine-grained visual classification model

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This paper cites The kalai- smorodinsky solution for many-objective bayesian optimization.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning The kalai- smorodinsky solution for many-objective bayesian optimization

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Self-supervised generalisation with meta auxiliary learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Auxiliary learning by implicit differentiation

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This paper cites Adamerging: Adaptive model merging for multi-task learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Adamerging: Adaptive model merging for multi-task learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Towards impartial multi-task learning

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This paper cites Modeling task relationships in multi-task learning with multi-gate mixture-of-experts.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Modeling task relationships in multi-task learning with multi-gate mixture-of-experts

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Mod-squad: Designing mixtures of experts as modular multi-task learners

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This paper cites When moe meets llms: Parameter efficient fine-tuning for multi-task medical ap- plications.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning When moe meets llms: Parameter efficient fine-tuning for multi-task medical ap- plications

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This paper cites Adaptive mixtures of local experts.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Adaptive mixtures of local experts

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This paper cites Learning piecewise control strategies in a modular neural network architecture.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Learning piecewise control strategies in a modular neural network architecture

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This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

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This paper cites Belongie, Bharath Hariha- ran, and Ser-Nam Lim.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Belongie, Bharath Hariha- ran, and Ser-Nam Lim

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This paper cites Scaling & shifting your features: A new baseline for efficient model tuning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Scaling & shifting your features: A new baseline for efficient model tuning

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This paper cites Efficient adaptation of large vision transformer via adapter re-composing.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Efficient adaptation of large vision transformer via adapter re-composing

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This paper cites Compressed video prompt tuning.Advances in Neural Information Processing Systems, 36:31895–31907, 2023.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Compressed video prompt tuning.Advances in Neural Information Processing Systems, 36:31895–31907, 2023

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This paper cites Gradnorm: Gra- dient normalization for adaptive loss balancing in deep multitask networks.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Gradnorm: Gra- dient normalization for adaptive loss balancing in deep multitask networks

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This paper cites Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multi-task learning as a bargaining game

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Independent component alignment for multi-task learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multinet++: Multi-stream feature aggregation and geometric loss strategy for multi-task learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Unresolved cited work

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning End-to-end multi-task learning with attention

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Achievement-based training progress balancing for multi-task learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Moefication: Transformer feed-forward layers are mixtures of experts

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning An image is worth 16x16 words: Transformers for image recognition at scale

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Gomez, Lukasz Kaiser, and Illia Polosukhin

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Transformer feed-forward layers are key-value memories

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Knowledge neurons in pretrained transformers

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Balanced k-means for clustering

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Distilling the Knowledge in a Neural Network

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning The caltech-ucsd birds-200-2011 dataset

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Fine- grained car detection for visual census estimation

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Fine-Grained Visual Classification of Aircraft

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Automated flower classification over a large number of classes

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Indoor segmentation and support inference from rgbd images

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Taskprompter: Spatial-channel multi-task prompting for dense scene understanding

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Learning to prompt for vision-language models

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Neural Prompt Search

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Decoupled weight decay regularization

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Dualprompt: Complementary prompting for rehearsal-free continual learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Parameter-efficient transfer learning for NLP

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Sensitivity-aware visual parameter-efficient fine-tuning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Unresolved cited work

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multitask learning

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multi-Task Learning with Deep Neural Networks: A Survey

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Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning An Overview of Multi-Task Learning in Deep Neural Networks

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This paper cites Multi-task learning for dense prediction tasks: A survey.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multi-task learning for dense prediction tasks: A survey

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This paper cites Nddr-cnn: Layerwise feature fusing in multi-task cnns by neural discriminative dimensionality reduction.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Nddr-cnn: Layerwise feature fusing in multi-task cnns by neural discriminative dimensionality reduction

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This paper cites Cross-stitch networks for multi-task learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Cross-stitch networks for multi-task learning

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This paper cites Latent multi- task architecture learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Latent multi- task architecture learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.637251Z

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Observation b42b3d24-48a9-4b5c-be10-94ab3a0b90c8 · outbound

This paper cites Automated Search for Resource-Efficient Branched Multi-Task Networks.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Automated Search for Resource-Efficient Branched Multi-Task Networks

Reference 60

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Observation d00baac8-3dac-4c5d-ba30-e7167e70840c · outbound

This paper cites Learning to branch for multi-task learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Learning to branch for multi-task learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.615489Z

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Observation 4cd496a5-a504-4f96-8cc7-692fdefbb952 · outbound

This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multi-task learning using uncertainty to weigh losses for scene geometry and semantics

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.590153Z

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Observation 30572065-d442-4699-bc33-9e7ceeb2a7b2 · outbound

This paper cites Exploring relational context for multi-task dense prediction.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Exploring relational context for multi-task dense prediction

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.568445Z

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Observation 0f891b12-0e9c-4307-a0fd-418e388c41b3 · outbound

This paper cites Mti-net: Multi-scale task interaction networks for multi-task learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Mti-net: Multi-scale task interaction networks for multi-task learning

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.549629Z

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Observation 913aed75-2a7f-421a-9e1d-ef4d2fa616ec · outbound

This paper cites Pattern-structure diffusion for multi-task learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Pattern-structure diffusion for multi-task learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.533017Z

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Observation fa6d4565-664c-4ed0-9273-3b642c234553 · outbound

This paper cites Pattern-affinitive propagation across depth, surface normal and semantic segmentation.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Pattern-affinitive propagation across depth, surface normal and semantic segmentation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.512615Z

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Observation 997421fc-42da-4662-a4ef-fe65d46c0392 · outbound

This paper cites Joint task- recursive learning for semantic segmentation and depth estimation.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Joint task- recursive learning for semantic segmentation and depth estimation

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.491946Z

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Observation a253e6fb-6b7a-4c8f-903b-a688907af030 · outbound

This paper cites Robust learning through cross-task consistency.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Robust learning through cross-task consistency

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.473498Z

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Observation b7e408b3-2c70-456b-ac4b-4ae8a887caa2 · outbound

This paper cites Learning to prompt for continual learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Learning to prompt for continual learning

Reference 69

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This paper cites Just pick a sign: Optimizing deep multitask models with gradient sign dropout.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Just pick a sign: Optimizing deep multitask models with gradient sign dropout

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.444934Z

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Observation 10888fbc-39a3-41da-9efb-e82e67fb7b76 · outbound

This paper cites Dynamic task prioritization for multitask learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Dynamic task prioritization for multitask learning

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.429116Z

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Observation 80aa96eb-949b-4efb-b73e-f4d87165ed39 · outbound

This paper cites A modulation module for multi-task learning with applications in image retrieval.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning A modulation module for multi-task learning with applications in image retrieval

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.410524Z

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Observation fb67c2d1-88e9-43d7-8a0d-75886a80eb14 · outbound

This paper cites Contrastive multi-task dense prediction.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Contrastive multi-task dense prediction

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.394460Z

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Observation af52bdfa-2f91-4895-8610-b9beba3f0f6e · outbound

This paper cites Learning multiple dense prediction tasks from partially annotated data.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Learning multiple dense prediction tasks from partially annotated data

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.377637Z

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Observation b047b2df-6d1e-41f0-a4b0-39d12b6a2cd1 · outbound

This paper cites Asynchronous convergence in multi-task learning via knowledge distillation from converged tasks.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Asynchronous convergence in multi-task learning via knowledge distillation from converged tasks

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.356990Z

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Observation 0dd57eb4-6937-4ab4-b9cb-356baf85f74c · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.892560Z

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This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.900952Z

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This paper cites Taming Sparsely Activated Transformer with Stochastic Experts.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Taming Sparsely Activated Transformer with Stochastic Experts

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.906572Z

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This paper cites Taskexpert: Dynamically assembling multi-task representations with memorial mixture-of-experts.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Taskexpert: Dynamically assembling multi-task representations with memorial mixture-of-experts

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.334689Z

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Observation 6be9bc2d-3ccf-4562-a2a8-f0c05d6ca3ef · outbound

This paper cites Fact: Factor-tuning for lightweight adaptation on vision transformer.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Fact: Factor-tuning for lightweight adaptation on vision transformer

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.320191Z

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Observation 1961d210-4d1d-40a4-b38c-a704c3403a0e · outbound

This paper cites Polyhistor: Parameter- efficient multi-task adaptation for dense vision tasks.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Polyhistor: Parameter- efficient multi-task adaptation for dense vision tasks

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.304651Z

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Observation 5048beed-6556-46d9-8b93-aa90b8f84a11 · outbound

This paper cites Vl-adapter: Parameter-efficient transfer learning for vision-and-language tasks.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Vl-adapter: Parameter-efficient transfer learning for vision-and-language tasks

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.289895Z

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Observation 92b66a43-03a2-4428-9e1c-e5d8a30b9cc9 · outbound

This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.942847Z

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Observation 3733cf8e-811f-47fd-b0c9-aa58c35dfb55 · outbound

This paper cites Low-rank compression of neural nets: Learning the rank of each layer.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Low-rank compression of neural nets: Learning the rank of each layer

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.272767Z

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Observation 769460c3-ab03-4634-baee-83b3d1ae54e7 · outbound

This paper cites Multi-task learning with low rank attribute embedding for person re-identification.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Multi-task learning with low rank attribute embedding for person re-identification

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.256981Z

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Observation 983e16c0-70e8-4e3b-98ad-63d39fa292cd · outbound

This paper cites Generalized low rank models.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Generalized low rank models

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.243345Z

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Observation 941da6c2-cbad-42f4-8a71-55a4b589fc43 · outbound

This paper cites Trace Norm Regularised Deep Multi-Task Learning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Trace Norm Regularised Deep Multi-Task Learning

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.963481Z

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This paper cites LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.971267Z

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This paper cites Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.978828Z

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This paper cites LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:41.985202Z

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Observation 95dbaa5b-eea2-43ef-96b5-fa21cb49bb3e · outbound

This paper cites Octavius: Mitigating task interference in mllms via lora-moe.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Octavius: Mitigating task interference in mllms via lora-moe

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.225343Z

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Observation 5dd71e32-1b31-40ee-96b8-8155d664af6b · outbound

This paper cites Dinov2: Learning robust visual features without supervision.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Dinov2: Learning robust visual features without supervision

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.207153Z

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Observation f87e99d8-e117-4521-a725-66a3a16de4c6 · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.191158Z

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Observation efb56053-6460-4c73-8c1b-35ccb0220635 · outbound

This paper cites One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:42.021963Z

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Observation e505fc9e-b0e3-4767-b864-888fdaeacf05 · outbound

This paper cites Controlling text-to-image diffusion by orthogonal finetuning.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Controlling text-to-image diffusion by orthogonal finetuning

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.174794Z

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Observation 28e3861d-9b5e-47a4-8b7d-ab648063990a · outbound

This paper cites Parameter-efficient orthogonal finetuning via butterfly factorization.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Parameter-efficient orthogonal finetuning via butterfly factorization

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.159533Z

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Observation a93ac864-5626-4186-b822-1bdcd7a1331b · outbound

This paper cites Rota- tion equivariant cnns for digital pathology.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Rota- tion equivariant cnns for digital pathology

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.142968Z

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Observation 1213e20d-3c1f-44db-8899-84c2a762218b · outbound

This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:54:43.128472Z

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Observation d86c7d48-1876-43c3-bfa6-2f0204a79627 · outbound

This paper cites Remote sensing image scene classification: Benchmark and state of the art.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Remote sensing image scene classification: Benchmark and state of the art

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:42.059676Z

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This paper cites Kaggle diabetic retinopathy detection, July 2015.

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning Kaggle diabetic retinopathy detection, July 2015

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-10T20:54:42.066284Z

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