TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning | Paper Citation Record

Observation e2d1f00e-0646-43dd-acc5-1fed87f12dd7 · outbound

This paper cites Mtlora: Low-rank adaptation approach for efficient multi-task learn- ing.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Mtlora: Low-rank adaptation approach for efficient multi-task learn- ing

Reference 1

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Observation 87283ebc-d1d8-46b5-b199-d4b8b63d9b3b · outbound

This paper cites Adversarial training for multi-context joint entity and relation extraction.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Adversarial training for multi-context joint entity and relation extraction

Reference 2

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Observation eaaea12c-dcf0-4db2-95be-133f8e715a79 · outbound

This paper cites Mult: An end-to-end multitask learning transformer.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Mult: An end-to-end multitask learning transformer

Reference 3

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Observation cea52191-b645-4a3b-978e-a5ea3eb6784a · outbound

This paper cites Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al

Reference 4

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Observation fa43d396-774e-40d5-8e91-b1dbc9adb2da · outbound

This paper cites End-to- end object detection with transformers.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning End-to- end object detection with transformers

Reference 5

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Observation 075574ab-7832-417d-974b-befbcb32eebe · outbound

This paper cites Adapter configuration: Both sequential and parallel configurations are possible in adapter-based PEFT framework [7].

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Adapter configuration: Both sequential and parallel configurations are possible in adapter-based PEFT framework [7]

Reference 6

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Observation 8b0ed744-c519-4181-866f-1200ec628f44 · outbound

This paper cites Adaptformer: Adapting vision transformers for scalable visual recogni- tion.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Adaptformer: Adapting vision transformers for scalable visual recogni- tion

Reference 7

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Observation b261d85d-9469-407c-83b5-0640b749b916 · outbound

This paper cites Improving Generative Pre-Training: An In-depth Study of Masked Image Modeling and Denoising Models.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Improving Generative Pre-Training: An In-depth Study of Masked Image Modeling and Denoising Models

Reference 8

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Observation ce28e600-562b-4201-bfc8-4667d1ec0a03 · outbound

This paper cites Emerging Property of Masked Token for Effective Pre-training.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Emerging Property of Masked Token for Effective Pre-training

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:44:33.437178Z

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Observation 555a42c4-dc00-4545-8245-51fe916e1ad6 · outbound

This paper cites Salience-based adaptive masking: revisit- ing token dynamics for enhanced pre-training.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Salience-based adaptive masking: revisit- ing token dynamics for enhanced pre-training

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.924859Z

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Observation 41fbb113-0e05-4434-b52b-6b5ef1085f4e · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Imagenet: A large-scale hierarchical image database

Reference 11

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Observation 1fac4f65-4f2d-4dd6-9b29-576d61659e19 · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Bert: Pre-training of deep bidirectional trans- formers for language understanding

Reference 12

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Observation 5d6d5b2a-78a9-4ecf-8a9a-5593179d2795 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 13

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Observation 27034311-7c15-4207-b1b6-cf20bab0cfe4 · outbound

This paper cites LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

Reference 14

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Observation 5b0ef349-aecc-491c-ad73-f91384e440d0 · outbound

This paper cites an unresolved cited work.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Unresolved cited work

Reference 15

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Observation 3493d7f9-08eb-4fa7-8170-a74528fdf578 · outbound

This paper cites Sensitivity-aware visual parameter-efficient fine-tuning.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Sensitivity-aware visual parameter-efficient fine-tuning

Reference 16

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Observation 33c166ef-c633-4a6b-82f8-c330d137feed · outbound

This paper cites Towards a Unified View of Parameter-Efficient Transfer Learning.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Towards a Unified View of Parameter-Efficient Transfer Learning

Reference 17

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Observation c996c90a-f3ed-49b2-8445-d829080af528 · outbound

This paper cites Masked autoencoders are scalable vision learners.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Masked autoencoders are scalable vision learners

Reference 18

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Observation f54d0176-5946-4be5-8790-29ee6acc9c70 · outbound

This paper cites Masked autoencoders are scalable vision learners.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Masked autoencoders are scalable vision learners

Reference 19

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Observation e8c28877-36eb-4d7e-869b-1eae4960b62b · outbound

This paper cites Parameter-efficient transfer learning for nlp.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Parameter-efficient transfer learning for nlp

Reference 20

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Observation 654463ab-93e2-4e88-b3ab-9950baf6b770 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning LoRA: Low-Rank Adaptation of Large Language Models

Reference 21

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Observation 49b4a238-22af-435d-8a9d-877ff443d298 · outbound

This paper cites LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 22

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Observation d79c3bc3-6db3-4b66-aad2-11ef8c954419 · outbound

This paper cites Going beyond multi-task dense pre- diction with synergy embedding models.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Going beyond multi-task dense pre- diction with synergy embedding models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.829620Z

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Observation 5e3fb4b0-2761-4e30-9651-f509bcd29c17 · outbound

This paper cites Vi- sual prompt tuning.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Vi- sual prompt tuning

Reference 24

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Observation 5f2c2645-5f9f-4a44-ac15-f40f0ff3323f · outbound

This paper cites Dynamic filter networks.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Dynamic filter networks

Reference 25

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Observation 829b335d-b16e-439a-bfc0-54863158029f · outbound

This paper cites Compacter: Efficient low-rank hypercomplex adapter layers.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Compacter: Efficient low-rank hypercomplex adapter layers

Reference 26

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Observation 15a87927-17bf-4e22-8138-0e7f0c7667e3 · outbound

This paper cites Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks

Reference 27

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Observation c2a34e9a-260c-4a73-867a-b08e281c89a9 · outbound

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

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Multi-task learning using uncertainty to weigh losses for scene geome- try and semantics

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.781222Z

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Observation c72ee683-931d-4e3d-93f8-21a82280ae4f · outbound

This paper cites Sequen- tial cross attention based multi-task learning.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Sequen- tial cross attention based multi-task learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.768633Z

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Observation f0e530d7-e891-4799-97cf-010bf783ae7d · outbound

This paper cites Knn local attention for image restoration.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Knn local attention for image restoration

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.757153Z

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Observation f487e660-ab56-488d-be40-9379ec438ab9 · outbound

This paper cites Cross-scale knn image transformer for image restoration.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Cross-scale knn image transformer for image restoration

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.744970Z

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Observation d11cd5f5-7135-4812-82ef-1bdca13d4403 · outbound

This paper cites Conditional adapters: Parameter-efficient transfer learning with fast in- ference.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Conditional adapters: Parameter-efficient transfer learning with fast in- ference

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.732218Z

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Observation 1b33c386-37d1-4c01-a8b8-94506c2eab00 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 33

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Observation 3e5cff21-5c60-432c-9458-d6227622cf97 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 34

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Observation 9132a85f-5357-4a7f-a2a8-bb3cc21d0857 · outbound

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

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Polyhistor: Parameter-efficient multi-task adap- tation for dense vision tasks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.720914Z

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Observation 16cbf5fb-05ed-4364-b196-b5a60e783ba1 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Swin transformer: Hierarchical vision transformer using shifted windows

Reference 36

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Observation fe578684-1556-49f1-8b4c-044f16a982e4 · outbound

This paper cites Swin trans- former: Hierarchical vision transformer using shifted win- dows, 2021.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Swin trans- former: Hierarchical vision transformer using shifted win- dows, 2021

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.698323Z

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Observation 592d777f-cbcb-448a-ac25-e80e599d4213 · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolution.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Swin transformer v2: Scaling up capacity and resolution

Reference 38

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Observation 26731d1a-e4ef-4f5a-8330-b99eaf0593cd · outbound

This paper cites Vi- sion transformers for dense prediction.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Vi- sion transformers for dense prediction

Reference 39

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Observation 55e87337-4db2-4f50-8977-36dacefb5e80 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 40

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Observation eee3afc1-f5e6-4a57-a1c5-1d5ee5fd387a · outbound

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

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Multi-task learning as multi-objective optimization

Reference 41

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Observation f0fd44b8-e465-4a6d-8fdd-c5fccb23a8d9 · outbound

This paper cites Deep high-resolution representation learning for human pose es- timation.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Deep high-resolution representation learning for human pose es- timation

Reference 42

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Observation a49f63ed-5c77-482b-a032-71dab6fc3c09 · outbound

This paper cites VL-Adapter: Parameter-efficient transfer learning for vision-and-language tasks.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning VL-Adapter: Parameter-efficient transfer learning for vision-and-language tasks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.644102Z

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Observation 1195d158-0309-4247-95a7-a605555280fd · outbound

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

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Mti-net: Multi-scale task interaction networks for multi-task learning

Reference 44

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Observation af29ca17-6569-4923-aaba-82189cd99f28 · outbound

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

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Multi-task learning for dense prediction tasks: A survey

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.619412Z

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Observation 62a542c8-c89a-471f-b77b-ac02f7129884 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transform- ers.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Segformer: Simple and efficient design for semantic segmentation with transform- ers

Reference 46

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Observation 56b35b73-892e-44f5-8c60-3c8b6532b94e · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transform- ers.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Segformer: Simple and efficient design for semantic segmentation with transform- ers

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.599977Z

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Observation efd18738-0a02-414b-a0aa-81c03144752b · outbound

This paper cites Simmim: A simple framework for masked image modeling.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Simmim: A simple framework for masked image modeling

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.589213Z

Source-reported events for the cited work

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Observation e29a2e57-eb5e-4691-af41-58ac49d67cce · outbound

This paper cites Vmt-adapter: Parameter-efficient transfer learning for multi- task dense scene understanding.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Vmt-adapter: Parameter-efficient transfer learning for multi- task dense scene understanding

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.578096Z

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Observation 8465666e-ed9d-4b86-8356-d69254683b4e · outbound

This paper cites Multi-task dense prediction via mixture of low-rank experts.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Multi-task dense prediction via mixture of low-rank experts

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.564843Z

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Observation 4a7d19c2-0954-47e5-894f-276d545fd622 · outbound

This paper cites Taskprompter: Spatial-channel multi-task prompting for dense scene understanding.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Taskprompter: Spatial-channel multi-task prompting for dense scene understanding

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.553237Z

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Observation 0aa5d2fa-0c72-458b-8763-fde84cdde5c8 · outbound

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

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Taskexpert: Dynamically assem- bling multi-task representations with memorial mixture-of- experts

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.541000Z

Source-reported events for the cited work

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Observation 70a5b5e3-faa7-4cb3-b202-6f1468d9c7d7 · outbound

This paper cites Masked Image Modeling with Denoising Contrast.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Masked Image Modeling with Denoising Contrast

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T21:44:33.135128Z

Source-reported events for the cited work

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Observation efcfc607-14ec-468b-948a-801ad3b280cf · outbound

This paper cites 1% vs 100%: Parameter-efficient low rank adapter for dense predictions.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning 1% vs 100%: Parameter-efficient low rank adapter for dense predictions

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.529080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 78b2a88e-60a9-4d74-a99a-edafbf65bb5f · outbound

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

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T21:44:33.142442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc0dc39e-e00d-43f4-a4c5-e18dca891d6e · outbound

This paper cites Zamir, Alexander Sax, William Shen, Leonidas J.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Zamir, Alexander Sax, William Shen, Leonidas J

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.516120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4f778180-523b-45d9-8200-5057bbcba6f7 · outbound

This paper cites A survey on multi-task learning.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning A survey on multi-task learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.505276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 94016eea-a49f-4e2b-937f-f6dfa3923419 · outbound

This paper cites Convolution meets lora: Parameter efficient finetuning for segment anything model.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Convolution meets lora: Parameter efficient finetuning for segment anything model

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.493070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5bc86606-f49c-4615-b901-9b274a398e08 · outbound

This paper cites Decoupled dynamic filter networks.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning Decoupled dynamic filter networks

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:44:33.481549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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