Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:17:59.706415Z
Paper Citation Record · LEDGER
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
As of 14 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2506.02882.
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 2026-08-14T06:32:32.682623+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
61 of 61 outbound references displayed
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- verified fuzzy36
- unresolved24
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation cf496bde-e413-4e9e-a870-8c5e559ed9f1 · outbound
This paper cites LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image Restoration.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image Restoration
Reference 1
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b3bad26-2330-4614-8342-0ede8ba249e9 · outbound
This paper cites Revisiting neural scaling laws in language and vision.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Revisiting neural scaling laws in language and vision
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0e02b274-b4ad-401e-85c2-d2ad45842e01 · outbound
This paper cites Generalized foggy-scene semantic segmentation by frequency decoupling.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Generalized foggy-scene semantic segmentation by frequency decoupling
Reference 3
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 681ae574-c6ac-4887-9846-3a72e1cd364f · outbound
This paper cites ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning
Reference 4
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7126410b-cac6-4b49-9528-c72566a7d91f · outbound
This paper cites Instance segmentation in the dark.International Journal of Computer Vision, 2023.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Instance segmentation in the dark.International Journal of Computer Vision, 2023
Reference 5
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b56c91c6-48e7-4645-857d-a0aebb7f169f · outbound
This paper cites Adaptformer: Adapting vision transformers for scalable visual recognition.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Adaptformer: Adapting vision transformers for scalable visual recognition
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:05.802853Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2ccb4bfd-6a0d-43b0-b7e7-12898b58b7ba · outbound
This paper cites Rvsl: Robust vehicle similarity learning in real hazy scenes based on semi-supervised learning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Rvsl: Robust vehicle similarity learning in real hazy scenes based on semi-supervised learning
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:05.680225Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2eea0386-6b91-4302-81e3-aaff1ed21cd4 · outbound
This paper cites RobustSAM: segment anything robustly on degraded images.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation RobustSAM: segment anything robustly on degraded images
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:05.553252Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 3ce11227-8953-400d-bc8b-92bb451df181 · outbound
This paper cites Mitra, Xiaolei Huang, Philip H.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Mitra, Xiaolei Huang, Philip H
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:05.436389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2957dfde-6ead-442c-8d06-0d62c662f394 · outbound
This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation QLoRA: Efficient Finetuning of Quantized LLMs
Reference 10
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78e9b36e-0e48-40fc-baf4-5de62c2dadab · outbound
This paper cites Dirty pixels: Towards end-to-end image processing and perception.ACM Transactions on Graphics (TOG), 2021.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Dirty pixels: Towards end-to-end image processing and perception.ACM Transactions on Graphics (TOG), 2021
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:05.282439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation f157d3e9-1ccf-4958-8f93-8f67d9fbda39 · outbound
This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation An image is worth 16x16 words: Transformers for image recognition at scale
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:05.138024Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 6686fbe0-a66f-4e0b-a779-d5e789e9ea7d · outbound
This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23 (120):1–39, 2022.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23 (120):1–39, 2022
Reference 13
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1614474-21ed-4205-9d1d-0bc10cced9a2 · outbound
This paper cites Lvis: A dataset for large vocabulary instance segmentation.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Lvis: A dataset for large vocabulary instance segmentation
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 40e3f879-a194-470e-a1e5-76fa5228ddfb · outbound
This paper cites Towards a Unified View of Parameter-Efficient Transfer Learning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Towards a Unified View of Parameter-Efficient Transfer Learning
Reference 15
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d65ff26a-8eda-461d-b947-3e278d19761a · outbound
This paper cites Deep residual learning for image recognition.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Deep residual learning for image recognition
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:04.845472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation ed65dd05-4a87-4cd4-927e-1e2475376569 · outbound
This paper cites Parameter-efficient transfer learning for nlp.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Parameter-efficient transfer learning for nlp
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:04.694477Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2d4f002e-746f-4946-9a0c-81d8f82bed16 · outbound
This paper cites LoRA: Low-Rank Adaptation of Large Language Models.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation LoRA: Low-Rank Adaptation of Large Language Models
Reference 18
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3a1949d-cd96-4a4b-80ea-d37911f387b0 · outbound
This paper cites LoRA: Low-rank adaptation of large language models.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation LoRA: Low-rank adaptation of large language models
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d96dac15-463c-414a-94ac-10ce6eb2f64d · outbound
This paper cites Tutel: Adaptive mixture-of-experts at scale.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Tutel: Adaptive mixture-of-experts at scale
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:04.538256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 523c5311-19bd-4a74-bc59-ab3a721a0b54 · outbound
This paper cites Categorical Reparameterization with Gumbel-Softmax.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Categorical Reparameterization with Gumbel-Softmax
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:56.529530Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c110f38-9512-416d-8889-cc88e3a01eb8 · outbound
This paper cites Visual prompt tuning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Visual prompt tuning
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:04.432711Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 016a4201-8bf5-4d65-9ca6-95122506a135 · outbound
This paper cites Scaling Laws for Neural Language Models.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Scaling Laws for Neural Language Models
Reference 23
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99a37cdd-d9f2-4f42-8a1d-5c3adcf7df9d · outbound
This paper cites Segment anything in high quality.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Segment anything in high quality
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:04.311760Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 8edd993d-312c-4a27-b259-8a0a7225828c · outbound
This paper cites Efficient and versatile robust fine-tuning of zero-shot models.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Efficient and versatile robust fine-tuning of zero-shot models
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:04.155053Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a72f74e8-34a1-4d9d-a537-ea7755eb8e22 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Adam: A Method for Stochastic Optimization
Reference 26
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cda47fc-37ed-4575-b913-e68ebd2ab08d · outbound
This paper cites Segment anything.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Segment anything
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:57.033496Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db7789a5-5738-4aa8-9ab7-9a8111a85676 · outbound
This paper cites Big transfer (bit): General visual representation learning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Big transfer (bit): General visual representation learning
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:03.970783Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 6afb74f5-e746-4552-a63c-b5924d1e1b91 · outbound
This paper cites Fifo: Learning fog-invariant features for foggy scene segmentation.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Fifo: Learning fog-invariant features for foggy scene segmentation
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:03.803273Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a58ebbb1-4221-471c-80de-c9d6fd2aa25d · outbound
This paper cites The power of scale for parameter-efficient prompt tuning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation The power of scale for parameter-efficient prompt tuning
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:03.622395Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4fde4c19-773b-4b63-8173-11c5b4e79383 · outbound
This paper cites All-In-One Image Restoration for Unknown Corruption.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation All-In-One Image Restoration for Unknown Corruption
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:03.470391Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 13af6f22-22be-432d-940e-edc8a6c1cfdd · outbound
This paper cites Single image deraining: A comprehensive benchmark analysis.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Single image deraining: A comprehensive benchmark analysis
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:03.179464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b792fb63-56a3-4154-bf87-ab6be06faee9 · outbound
This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Prefix-Tuning: Optimizing Continuous Prompts for Generation
Reference 33
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ab061e0-77e3-4791-b696-49ffe8c5753f · outbound
This paper cites Scaling & shifting your features: A new baseline for efficient model tuning.Advances in Neural Information Processing Systems, 35:109–123, 2022.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Scaling & shifting your features: A new baseline for efficient model tuning.Advances in Neural Information Processing Systems, 35:109–123, 2022
Reference 34
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc58c537-d7a3-4ba4-8528-960734db9b06 · outbound
This paper cites Deep interactive thin object selection.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Deep interactive thin object selection
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:02.981778Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b05e130c-fd0e-4202-b315-046e576ec5ba · outbound
This paper cites MoE-LLaVA: Mixture of Experts for Large Vision-Language Models.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:57.760977Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 624d1b06-176e-4794-ab99-6a0eb15adf61 · outbound
This paper cites NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:57.848691Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 50372993-270f-4e75-9a0e-664c7078f22f · outbound
This paper cites Microsoft coco: Common objects in context.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Microsoft coco: Common objects in context
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:02.825049Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 6265c30e-27f3-4374-adb6-1398719283f3 · outbound
This paper cites ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation
Reference 39
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c67038e3-4ca0-4152-80e4-5f4d96739072 · outbound
This paper cites Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:02.657902Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 54e28fee-0aa4-4e9d-9d6b-59cdc5cf74f2 · outbound
This paper cites Both style and fog matter: Cumulative domain adaptation for semantic foggy scene understanding.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Both style and fog matter: Cumulative domain adaptation for semantic foggy scene understanding
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:02.485943Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 1d3e11b6-d18b-494d-b2c8-e48b34f1b651 · outbound
This paper cites AdapterFusion: Non-Destructive Task Composition for Transfer Learning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation AdapterFusion: Non-Destructive Task Composition for Transfer Learning
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:58.200905Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71bf7ab9-4759-4ed4-9849-6da89814a3ec · outbound
This paper cites PromptIR: Prompting for all-in-one image restoration.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation PromptIR: Prompting for all-in-one image restoration
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:02.327347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 77ac5fbf-70ec-4374-9bd8-4d50002d1fc3 · outbound
This paper cites ACDC: The adverse conditions dataset with correspondences for semantic driving scene understanding.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation ACDC: The adverse conditions dataset with correspondences for semantic driving scene understanding
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:02.156439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 60c4bf5e-8022-4d50-9373-311b8950dba6 · outbound
This paper cites Robustness analysis on foundational segmentation models.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Robustness analysis on foundational segmentation models
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:02.014452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation ecd782f8-8cc6-4f68-a81f-b2dab42a458d · outbound
This paper cites Outrageously large neural networks: The sparsely-gated mixture- of-experts layer.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Outrageously large neural networks: The sparsely-gated mixture- of-experts layer
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:01.809983Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 47280692-36af-4999-8725-82fe3b5bf8fc · outbound
This paper cites Multitask vision-language prompt tuning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Multitask vision-language prompt tuning
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:01.649431Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation f93ab9e8-2c4e-440f-ab4c-f796687c400e · outbound
This paper cites Streets: A novel camera network dataset for traffic flow.Advances in Neural Information Processing Systems, 2019.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Streets: A novel camera network dataset for traffic flow.Advances in Neural Information Processing Systems, 2019
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:01.496685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b497544b-0f5e-4be4-9a3e-3266b519190e · outbound
This paper cites Urie: Universal image enhancement for visual recognition in the wild.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Urie: Universal image enhancement for visual recognition in the wild
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:01.351304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation f8b64305-7fb7-45ec-ba26-3128534cc1ac · outbound
This paper cites EfficientNet: Rethinking model scaling for convolutional neural networks.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation EfficientNet: Rethinking model scaling for convolutional neural networks
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:01.202334Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a99311e0-9f55-42c7-a896-00d0bc7279be · outbound
This paper cites NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:58.958623Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1dad2fb7-3742-46c4-98e2-f10c0388e679 · outbound
This paper cites DyLoRA: Parameter- efficient tuning of pre-trained models using dynamic search-free low-rank adaptation.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation DyLoRA: Parameter- efficient tuning of pre-trained models using dynamic search-free low-rank adaptation
Reference 52
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-07T11:17:59.120874Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23400480-b8ac-4580-9eca-dd531ba6b8e0 · outbound
This paper cites Ugˆ 2: A video benchmark for assessing the impact of image restoration and enhancement on automatic visual recognition.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Ugˆ 2: A video benchmark for assessing the impact of image restoration and enhancement on automatic visual recognition
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:00.855182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d18c4cfa-7977-4ed9-a654-bd8575a6e826 · outbound
This paper cites AdaMix: Mixture-of-adaptations for parameter-efficient model tuning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation AdaMix: Mixture-of-adaptations for parameter-efficient model tuning
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:59.249838Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b6b1f12-c26b-44b4-ad24-37fe461fe5ab · outbound
This paper cites Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:59.334061Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f853e7d2-ded4-45b9-bc21-be75e1a55a5f · outbound
This paper cites 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:59.404572Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7e83bbbf-eb31-4730-b34a-315f8da8bed7 · outbound
This paper cites BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:59.471177Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d186925-7e21-4ffa-b9bd-cce896bfbf15 · outbound
This paper cites Scaling vision transform- ers.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Scaling vision transform- ers
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:17:59.535727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a383ceb-e20e-4bd9-9940-5559c0c353b0 · outbound
This paper cites Adaptive budget allocation for parameter-efficient fine-tuning.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Adaptive budget allocation for parameter-efficient fine-tuning
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:00.660934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 52848613-87d2-47fa-8f1f-8d39b3fad717 · outbound
This paper cites Mixture-of-experts with expert choice routing.Advances in Neural Information Processing Systems, 35:7103–7114, 2022.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Mixture-of-experts with expert choice routing.Advances in Neural Information Processing Systems, 35:7103–7114, 2022
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:18:00.460518Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0b31834b-b701-4aee-87d9-9ca153a29f17 · outbound
This paper cites an unresolved cited work.
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Unresolved cited work
Reference 2020
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:18:00.994526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Pith citing papers
No inbound Pith citation observations are available.