Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T10:38:34.814963Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T10:38:34.814963Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
35 of 35 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation c64cae44-341b-48af-9c39-8e383e2a19ac · outbound
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
Source-reported events for the cited work
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Observation 927e97d4-882e-47f4-8c91-8b7ffc8a0ea9 · outbound
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
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
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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Observation a6297866-f22b-4ff5-b0d8-6ae6134742ea · outbound
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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Observation aa37dac8-bd51-4f7d-95d2-147ac5bb7db0 · outbound
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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Observation 2a6c4d74-0d82-42b3-95e9-63219634dfb2 · outbound
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
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
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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Observation 45badd11-c3b5-4e3e-9509-230eea41ef7b · outbound
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
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
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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Observation 475eee5d-f078-4db4-8b66-4a662618bee9 · outbound
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
Source-reported events for the cited work
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Observation 39f7addb-e785-4132-af11-6de6a3e685aa · outbound
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
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
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
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
Source-reported events for the cited work
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Observation 1d0422c1-e8a4-4eb8-ba97-6b024ddce208 · outbound
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
Source-reported events for the cited work
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Observation dd54a4a5-a189-499d-b406-ae87affec971 · outbound
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
Source-reported events for the cited work
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Observation 71e44c00-43b3-46a0-8145-2f20455dfdae · outbound
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
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
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
Source-reported events for the cited work
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Observation 1fdc48bd-61f5-4ab4-b6b0-d5c68ea7b6e1 · outbound
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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Observation dcada900-7b6c-48dd-8750-d0ddc8f6a822 · outbound
Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model Cats and dogs
Reference 24
Source-reported events for the cited work
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Observation bba2293a-8aa4-44d2-a09a-2922e6660ce9 · outbound
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
Source-reported events for the cited work
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Observation 6cd70bbb-8f11-4819-9454-42b8499834d5 · outbound
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
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.
Observation 336a9857-7861-44f0-a4d2-eda70d8c088d · outbound
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
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
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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Observation 507ddd6c-cf86-41f8-9526-93532de6227a · outbound
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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Observation 912eaa99-f8fb-4333-bf0e-b90a5e13a0af · outbound
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
Source-reported events for the cited work
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Observation cdca2cc4-7826-4ef8-bc17-84f86d4e290f · outbound
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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Observation 014ff591-b180-43fb-8ecb-b479a7f57ed1 · outbound
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
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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Observation 2291968b-3534-41b4-9342-705809ab650d · outbound
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
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.
No inbound Pith citation observations are available.