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Paper Citation Record · LEDGER

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model

As of 7 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2509.03895.

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

pith.paper-citation-record.v1
2509.03895 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:38:34.814963Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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  • verified fuzzy21
  • unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c64cae44-341b-48af-9c39-8e383e2a19ac · outbound

This paper cites Accelerating Conditional Prompt Learning via Masked Image Modeling for Vision-Language Models.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Accelerating Conditional Prompt Learning via Masked Image Modeling for Vision-Language Models

Reference 1

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Source-reported events for the cited work

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Observation 927e97d4-882e-47f4-8c91-8b7ffc8a0ea9 · outbound

This paper cites Describing textures in the wild.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Describing textures in the wild

Reference 2

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Observation 9c9aed4e-c2e6-4597-9fec-342c0318bb34 · outbound

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

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Imagenet: A large-scale hierarchical image database

Reference 3

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Observation 2f457c9d-4bca-46b9-beac-83389e1cdf0c · outbound

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

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a6297866-f22b-4ff5-b0d8-6ae6134742ea · outbound

This paper cites Learning to prompt for open-vocabulary object Table 5.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Learning to prompt for open-vocabulary object Table 5

Reference 5

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Source-reported events for the cited work

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Observation aa37dac8-bd51-4f7d-95d2-147ac5bb7db0 · outbound

This paper cites Learning gener- ative visual models from few training examples: An incre- mental bayesian approach tested on 101 object categories.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Learning gener- ative visual models from few training examples: An incre- mental bayesian approach tested on 101 object categories

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2a6c4d74-0d82-42b3-95e9-63219634dfb2 · outbound

This paper cites CLIP-Adapter: Better Vision-Language Models with Feature Adapters.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model CLIP-Adapter: Better Vision-Language Models with Feature Adapters

Reference 7

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Observation f96d96d8-24ed-4363-96a4-5eb9f0b40f26 · outbound

This paper cites Open-vocabulary Object Detection via Vision and Language Knowledge Distillation.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Open-vocabulary Object Detection via Vision and Language Knowledge Distillation

Reference 8

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Observation 364d720d-35d1-4801-8e5f-a87468f5e535 · outbound

This paper cites Deep residual learning for image recognition.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Deep residual learning for image recognition

Reference 9

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Source-reported events for the cited work

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Observation 45badd11-c3b5-4e3e-9509-230eea41ef7b · outbound

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

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 10

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Observation 7ff0dfd4-383d-43c9-8fbf-ac20997db6d9 · outbound

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

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model The many faces of robust- ness: A critical analysis of out-of-distribution generalization

Reference 11

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Observation eef1642c-d45a-4bff-a340-363b0fc09342 · outbound

This paper cites Natural adversarial examples.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Natural adversarial examples

Reference 12

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Source-reported events for the cited work

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Observation 475eee5d-f078-4db4-8b66-4a662618bee9 · outbound

This paper cites Gallop: Learning global and local prompts for vision-language models.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Gallop: Learning global and local prompts for vision-language models

Reference 13

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Source-reported events for the cited work

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Observation 39f7addb-e785-4132-af11-6de6a3e685aa · outbound

This paper cites Decoupled Weight Decay Regularization.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Decoupled Weight Decay Regularization

Reference 14

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Observation 63dbc736-73a6-4fd6-a0fa-75b9ca7f5455 · outbound

This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks

Reference 15

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Observation c26a6630-fe86-4095-83ca-233e3c4dd86c · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Fine-Grained Visual Classification of Aircraft

Reference 16

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Observation d48385e4-5bfc-465a-94aa-193f94775e20 · outbound

This paper cites Locoop: Few-shot out-of-distribution detection via prompt learning.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Locoop: Few-shot out-of-distribution detection via prompt learning

Reference 17

Resolution
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Observation 1d0422c1-e8a4-4eb8-ba97-6b024ddce208 · outbound

This paper cites Debiasing, calibrating, and improving semi-supervised learning performance via simple ensemble projector.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Debiasing, calibrating, and improving semi-supervised learning performance via simple ensemble projector

Reference 18

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Source-reported events for the cited work

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Observation dd54a4a5-a189-499d-b406-ae87affec971 · outbound

This paper cites Sequencematch: Revisiting the design of weak-strong augmentations for semi-supervised learning.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Sequencematch: Revisiting the design of weak-strong augmentations for semi-supervised learning

Reference 19

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Source-reported events for the cited work

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Observation 71e44c00-43b3-46a0-8145-2f20455dfdae · outbound

This paper cites On calibration of prompt learning using temperature scaling.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model On calibration of prompt learning using temperature scaling

Reference 20

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Observation 136539b0-c43e-4e54-a688-f587770705b9 · outbound

This paper cites Boosting semi- supervised learning by bridging high and low-confidence predictions.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Boosting semi- supervised learning by bridging high and low-confidence predictions

Reference 21

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Observation 097340f0-c97d-4a0f-a2fd-795e761b79db · outbound

This paper cites Adaptive cache enhancement for test- time adaptation of vision-language models.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Adaptive cache enhancement for test- time adaptation of vision-language models

Reference 22

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Observation 1fdc48bd-61f5-4ab4-b6b0-d5c68ea7b6e1 · outbound

This paper cites Proto-clip: Vision-language prototypical network for few-shot learning.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Proto-clip: Vision-language prototypical network for few-shot learning

Reference 23

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation dcada900-7b6c-48dd-8750-d0ddc8f6a822 · outbound

This paper cites Cats and dogs.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Cats and dogs

Reference 24

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation bba2293a-8aa4-44d2-a09a-2922e6660ce9 · outbound

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

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Learning transferable visual models from natural language supervision

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6cd70bbb-8f11-4819-9454-42b8499834d5 · outbound

This paper cites Meta-adapter: An online few-shot learner for vision-language model.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Meta-adapter: An online few-shot learner for vision-language model

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 336a9857-7861-44f0-a4d2-eda70d8c088d · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 27

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Observation e494f152-e49b-4c76-85be-fa7ec22e0c33 · outbound

This paper cites LXMERT: Learning Cross-Modality Encoder Representations from Transformers.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model LXMERT: Learning Cross-Modality Encoder Representations from Transformers

Reference 28

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Observation 2d2d8eea-96c3-46cd-aa4c-20444bb25c7c · outbound

This paper cites Attention is all you need.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Attention is all you need

Reference 29

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Unavailable: canonical work link unavailable.

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Observation 507ddd6c-cf86-41f8-9526-93532de6227a · outbound

This paper cites Learning robust global representations by penalizing local predictive power.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Learning robust global representations by penalizing local predictive power

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 912eaa99-f8fb-4333-bf0e-b90a5e13a0af · outbound

This paper cites Sun database: Large-scale scene recog- nition from abbey to zoo.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Sun database: Large-scale scene recog- nition from abbey to zoo

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation cdca2cc4-7826-4ef8-bc17-84f86d4e290f · outbound

This paper cites Dual Modality Prompt Tuning for Vision-Language Pre-Trained Model.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Dual Modality Prompt Tuning for Vision-Language Pre-Trained Model

Reference 32

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Unavailable: canonical work link unavailable.

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Observation 014ff591-b180-43fb-8ecb-b479a7f57ed1 · outbound

This paper cites Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Reference 33

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Observation 0c062390-4ed8-4422-987b-69003325eb7c · outbound

This paper cites Conditional prompt learning for vision-language models.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Conditional prompt learning for vision-language models

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-05T10:38:35.752900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T10:38:34.754654Z digest=sha256:3321c8f18c38efca6d118c57f82f12b4d77d77324ae91073504aeb834f2d1160

Observation 2291968b-3534-41b4-9342-705809ab650d · outbound

This paper cites Learning to prompt for vision-language models.

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Learning to prompt for vision-language models

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:38:35.634444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T10:38:34.814963Z digest=sha256:0370935a7ff33d4ad1c03587820800af37030456063ab84caf0129f506d0586c

Pith citing papers

No inbound Pith citation observations are available.