Paper Citation Record · LEDGER

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation

As of 19 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 1 inbound Pith citation observation for arXiv:2501.15377.

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

pith.paper-citation-record.v1
2501.15377 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

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measured 69 of 69 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:45:37.994333Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T10:45:38.818003Z

Reference resolution

68 of 68 outbound references displayed

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External citation measurements

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Outbound references

Observation ed720ae1-480b-46b8-974e-239e8d6ee8db · outbound

This paper cites Agiza, Marina Neseem, and Sherief Reda.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Agiza, Marina Neseem, and Sherief Reda

Reference 1

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Observation d974947f-55bc-4f6f-86e7-029b7ffc68d4 · outbound

This paper cites data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language

Reference 2

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Observation b91850d9-7194-4ba9-abd2-42ca387c0535 · outbound

This paper cites Parameter efficient fine-tuning of self-supervised vits without catastrophic forgetting.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Parameter efficient fine-tuning of self-supervised vits without catastrophic forgetting

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.864422Z

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Observation d0c7a15b-c92a-475a-a60b-7faf4462b3c2 · outbound

This paper cites Tenenbaum, and Boris Katz.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Tenenbaum, and Boris Katz

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.846565Z

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Observation 6fc6886f-6e60-434a-88e7-b9cdd56a0da1 · outbound

This paper cites LoRA Learns Less and Forgets Less.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation LoRA Learns Less and Forgets Less

Reference 5

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Observation bf723bb8-2e96-4475-a4ad-84a2409d4483 · outbound

This paper cites Food-101 - mining discriminative components with random forests.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Food-101 - mining discriminative components with random forests

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.827861Z

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Observation 9704d95f-6aff-46d0-a26e-d51c120fbdf5 · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Emerg- ing properties in self-supervised vision transformers

Reference 7

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Observation a9e9d000-2c70-4b74-9f35-4a8d47e8ba76 · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation A Simple Framework for Contrastive Learning of Visual Representations

Reference 8

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This paper cites Describing textures in the wild.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Describing textures in the wild

Reference 9

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Observation ed839f95-b496-43da-b09f-2b0030806ac8 · outbound

This paper cites Ng, and Honglak Lee.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Ng, and Honglak Lee

Reference 10

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Observation 82a3de65-8e77-40fa-86fd-9542854a24c5 · outbound

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

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Compacter: Efficient low-rank hypercomplex adapter layers

Reference 11

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Observation d78ce34e-3269-46f9-a550-f7e0271dd1de · outbound

This paper cites Li, and Li Fei-Fei.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Li, and Li Fei-Fei

Reference 12

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Observation d29194a5-05cd-4053-9acd-5a9529c1b4b7 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research [best of the web].

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation The mnist database of handwritten digit images for machine learning research [best of the web]

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.704421Z

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Observation 51bbb2be-2321-49ed-ac00-61eb4c02b7fa · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 14

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Observation c2a693c4-12db-4ca7-8238-f2d0944d3b03 · outbound

This paper cites Data determines distributional robustness in contrastive language image pre-training (clip).

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Data determines distributional robustness in contrastive language image pre-training (clip)

Reference 15

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Observation b75f3985-0494-467c-b4c2-b37725c3de4d · outbound

This paper cites Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models

Reference 16

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Observation 502dc62b-9ddc-47e5-bd6b-6df15ea09202 · outbound

This paper cites Finetune like you pretrain: Im- proved finetuning of zero-shot vision models.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Finetune like you pretrain: Im- proved finetuning of zero-shot vision models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.658058Z

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Observation 363db8ae-4f0c-48b7-9c2b-fb66e430bac5 · outbound

This paper cites Bootstrap your own latent: A new approach to self-supervised Learning.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Bootstrap your own latent: A new approach to self-supervised Learning

Reference 18

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Observation 9b5b6029-be12-419c-9cad-26e4d17c7643 · outbound

This paper cites Anchor- based robust finetuning of vision-language models.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Anchor- based robust finetuning of vision-language models

Reference 19

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Observation bd92a768-0542-4331-94a0-830155822e3d · outbound

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

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Towards a Unified View of Parameter-Efficient Transfer Learning

Reference 20

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Observation 66dec24e-d5b6-4009-b01b-21fc6a47060e · outbound

This paper cites Zhang, Shaoqing Ren, and Jian Sun.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Zhang, Shaoqing Ren, and Jian Sun

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.619161Z

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Observation d60f78ba-1358-4d11-b6c2-c81d13ad1e79 · outbound

This paper cites Natural adversarial exam- ples.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Natural adversarial exam- ples

Reference 22

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Observation f7fddeb0-3fd1-4edc-85bc-dc936bfc170f · outbound

This paper cites The many faces of robust- ness: A critical analysis of out-of-distribution generalization.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation The many faces of robust- ness: A critical analysis of out-of-distribution generalization

Reference 23

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Observation b6276ec0-733e-4f1b-b550-4786bb22eb2e · outbound

This paper cites Parameter-Efficient Transfer Learning for NLP.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Parameter-Efficient Transfer Learning for NLP

Reference 24

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

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation LoRA: Low-Rank Adaptation of Large Language Models

Reference 25

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This paper cites Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig

Reference 26

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Observation 6de94124-d0a9-46bb-a946-3e5d75e15266 · outbound

This paper cites Visual Prompt Tuning.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Visual Prompt Tuning

Reference 27

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This paper cites MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Reference 28

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Observation 524ae0c7-da29-41d0-95f5-c5f62fc3ddec · outbound

This paper cites VeRA: Vector-based Random Matrix Adaptation.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation VeRA: Vector-based Random Matrix Adaptation

Reference 29

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Observation 76438f68-80e4-4a0c-889b-9df7f9b7b70a · outbound

This paper cites Learning multiple layers of features from tiny images.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Learning multiple layers of features from tiny images

Reference 30

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Observation 6b415cff-2590-4d8f-8e20-59b9a8db9012 · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 31

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This paper cites The power of scale for parameter-efficient prompt tuning.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation The power of scale for parameter-efficient prompt tuning

Reference 32

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Observation 6b2df048-99db-4888-91f1-e485d429078c · outbound

This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll ´ar, and C.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll ´ar, and C

Reference 33

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Observation 3ce26968-e723-46f2-91ba-c580d4a6aa0c · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 34

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Observation 17375174-04a4-48f8-8cf9-2878ce5c2fe1 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Fine-Grained Visual Classification of Aircraft

Reference 35

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This paper cites SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning

Reference 36

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Observation f5ccdedd-87b6-4c11-9582-e6f1323fcf24 · outbound

This paper cites Continual vision-language representation learning with off-diagonal information.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Continual vision-language representation learning with off-diagonal information

Reference 37

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Observation 77da8661-79db-496b-9541-53899b176ba7 · outbound

This paper cites Automated flower classification over a large number of classes.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Automated flower classification over a large number of classes

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.471476Z

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Observation 0f710ab5-bf15-439c-83d5-c67f948c018e · outbound

This paper cites Parkhi, Andrea Vedaldi, Andrew Zisserman, and C.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Parkhi, Andrea Vedaldi, Andrew Zisserman, and C

Reference 39

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Observation 4ecabc01-0878-42e3-9eff-94b6be17cd9a · outbound

This paper cites Girshick, Piotr Doll ´ar, Trevor Dar- rell, and Bharath Hariharan.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Girshick, Piotr Doll ´ar, Trevor Dar- rell, and Bharath Hariharan

Reference 40

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Observation 1001e89a-edc1-49f5-9024-5f44e10fafcd · outbound

This paper cites Plummer, Liwei Wang, Christopher M.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Plummer, Liwei Wang, Christopher M

Reference 41

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Source-reported events for the cited work

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Observation 51edc068-311a-426a-b893-8ac4e8db1f3f · outbound

This paper cites Learning transferable visual models from natural language supervision.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Learning transferable visual models from natural language supervision

Reference 42

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Observation af3ad57a-8a3b-4b87-882a-b782db10ade0 · outbound

This paper cites Residual prompt tuning: Improving prompt tuning with residual reparameterization.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Residual prompt tuning: Improving prompt tuning with residual reparameterization

Reference 43

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Observation 45c86392-5d3c-4dfb-999c-cb0b90495290 · outbound

This paper cites Do imagenet classifiers generalize to im- agenet? In International Conference on Machine Learning,.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Do imagenet classifiers generalize to im- agenet? In International Conference on Machine Learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.350637Z

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Observation dd70b2b8-e40d-49a3-a297-752e9c75b7ec · outbound

This paper cites Tied-lora: Enhancing parameter efficiency of lora with weight tying.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Tied-lora: Enhancing parameter efficiency of lora with weight tying

Reference 45

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Observation 58bec305-acfc-4d8a-855f-c51f4cf19180 · outbound

This paper cites LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 46

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Observation 62e484ad-d1d2-445c-bd9a-3830f8c81d5d · outbound

This paper cites Ziplora: Any subject in any style by effectively merging loras.ArXiv, abs/2311.13600, 2023.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Ziplora: Any subject in any style by effectively merging loras.ArXiv, abs/2311.13600, 2023

Reference 47

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Observation dac5b137-a5ea-4329-bb0e-ee665d4ec61d · outbound

This paper cites Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.303625Z

Source-reported events for the cited work

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Observation cfce7068-7c99-493f-a752-5d01e4ab05b1 · outbound

This paper cites Improved deep metric learning with multi- class n-pair loss objective.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Improved deep metric learning with multi- class n-pair loss objective

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.283238Z

Source-reported events for the cited work

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Observation 973780cd-962e-4618-86a0-a54b30066fba · outbound

This paper cites A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP).

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:25:39.575133Z

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Observation 2ff76208-be26-4a79-9334-ccc4b0735e02 · outbound

This paper cites Continual Learning and Catastrophic Forgetting.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Continual Learning and Catastrophic Forgetting

Reference 51

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Observation bb1f76cc-2f08-40d8-87a5-224a1c58e721 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Representation Learning with Contrastive Predictive Coding

Reference 52

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This paper cites Fowlkes, Rahul Bhotika, and Ste- fan 0 Soatto.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Fowlkes, Rahul Bhotika, and Ste- fan 0 Soatto

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.263826Z

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Observation 095e9663-256b-44fc-bca1-a304d920ac89 · outbound

This paper cites Xing, and Zachary Chase Lipton.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Xing, and Zachary Chase Lipton

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.243856Z

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Observation 427454fa-9b29-4f1f-86cc-0878d67e7550 · outbound

This paper cites A Sober Look at the Robustness of CLIPs to Spurious Features.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation A Sober Look at the Robustness of CLIPs to Spurious Features

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T14:25:39.318837Z

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Observation b7587dbd-9ebf-45fe-8444-0f65a8416f83 · outbound

This paper cites Robust fine-tuning of zero-shot models.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Robust fine-tuning of zero-shot models

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.222340Z

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Observation 018a4023-0dec-4da9-9a62-6e3f5ec0e19f · outbound

This paper cites A practi- cal contrastive learning framework for single-image super- resolution.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation A practi- cal contrastive learning framework for single-image super- resolution

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.204527Z

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Observation a0cd753c-4946-4276-be21-9379db751317 · outbound

This paper cites Ehinger, Aude Oliva, and Antonio Torralba.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Ehinger, Aude Oliva, and Antonio Torralba

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.185748Z

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Observation 1d981020-da38-42b3-af93-2cb2d76caccc · outbound

This paper cites Detco: Unsuper- vised contrastive learning for object detection.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Detco: Unsuper- vised contrastive learning for object detection

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.163494Z

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Observation 819cf56c-0917-4a79-8987-0e6908836864 · outbound

This paper cites In- stance localization for self-supervised detection pretraining.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation In- stance localization for self-supervised detection pretraining

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.144354Z

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Observation 84b4a480-b5a4-45c9-a8bb-f9d999f1712e · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T14:25:39.353227Z

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Observation ad8d69d8-fa3b-415f-857e-912ffdbfae4c · outbound

This paper cites Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T14:25:39.358975Z

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Observation f6aaf1bb-4093-4275-b5e6-bf9e7843ce27 · outbound

This paper cites Low-rank few-shot adaptation of vision-language models.2024 IEEE/CVF Con- ference on Computer Vision and Pattern Recognition Work- shops (CVPRW), pages 1593–1603, 2024.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Low-rank few-shot adaptation of vision-language models.2024 IEEE/CVF Con- ference on Computer Vision and Pattern Recognition Work- shops (CVPRW), pages 1593–1603, 2024

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.121442Z

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Observation ddd08483-817e-4a61-82c2-a52e2d4e9a4f · outbound

This paper cites Adalora: Adaptive budget allocation for parameter-efficient fine-tuning.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Adalora: Adaptive budget allocation for parameter-efficient fine-tuning

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.103178Z

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Observation b0fd2492-91db-4a46-ab93-858c3c7137c8 · outbound

This paper cites Preventing zero-shot transfer degradation in continual learning of vision-language mod- els.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Preventing zero-shot transfer degradation in continual learning of vision-language mod- els

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:25:40.083209Z

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Observation d651653a-364d-4c2a-a185-7ec55bec5e08 · outbound

This paper cites Multi-LoRA Composition for Image Generation.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Multi-LoRA Composition for Image Generation

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-10T14:25:39.383666Z

Source-reported events for the cited work

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Observation e528a77e-c804-420a-9956-708e6e6719f6 · outbound

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Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:25:40.056840Z

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Observation 464e9e62-abd0-466a-80b8-1e2966879e1a · outbound

This paper cites an unresolved cited work.

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation Unresolved cited work

Reference 68

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T14:25:40.036865Z

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Pith citing papers

Observation b6d2361c-e728-48cd-a8b3-9f88bfe0ffb2 · inbound

Fine-tune Smarter, Not Harder: Parameter-Efficient Fine-Tuning for Geospatial Foundation Models cites this paper.

Fine-tune Smarter, Not Harder: Parameter-Efficient Fine-Tuning for Geospatial Foundation Models Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-08-16T10:45:38.824484Z

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