Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2307.13770.
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
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:57:09.874642Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
10
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 49068d3d-1a59-4457-90f7-f5b0520dd710 · inbound
SMART-Vision: Survey of Modern Action Recognition Techniques in Vision E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 165
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2992cd3a-5a34-457e-8f78-b939bcfa6f7e · inbound
Token Coordinated Prompt Attention is Needed for Visual Prompting E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 924ec6b3-02ec-4cbe-80b2-63a42601cc5f · inbound
Vision Graph Prompting via Semantic Low-Rank Decomposition E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 77a4a302-746c-4f4a-b635-0e337b623cec · inbound
DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 24
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 583cd4d4-a83d-4a5f-9dcb-a898bbf56e1e · inbound
Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 648900b7-6414-47fd-a963-7f0abcdc65d5 · inbound
Visual Instance-aware Prompt Tuning E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5150e9b7-143c-4500-82cb-3923394dd43f · inbound
Visual prompting reimagined: The power of the Activation Prompts E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 76
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2bc504f4-aa6b-49e2-bb2d-e946d3ca3ad4 · inbound
MNAFT: modality neuron-aware fine-tuning of multimodal large language models for image translation E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 563825e5-841f-4272-a261-2725d5a0bb28 · inbound
Compared to What? Baselines and Metrics for Counterfactual Prompting E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 98
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 10920560-a95b-4911-897a-c43864d1ac1f · inbound
Exposing Functional Fusion: A New Class of Strategic Backdoor in Dynamic Prompt Architectures E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a71bad50-c6a4-4139-a28f-76d034784a70 · inbound
Timage: A Generative Text-in-Image Paradigm for Fine-Tuning Vision-Language Models E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e3ad8cc2-fbd0-4dab-9c9f-f730021edb71 · inbound
Structured Hyperedge Adaptation for Parameter-Efficient Fine-Tuning of Vision Transformers E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e17aaac1-8b82-4ba0-a645-e0432dc272a5 · inbound
Mitigating Visual Degradation in MLLMs via Spatial-Spectral Visual Anchor Learning E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e26df252-12cd-4732-a043-8c423901b5b2 · inbound
Adapting Vision Foundation Models with Cascaded Semantics E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Reference 2017
Source-reported events for the cited work
Unavailable: canonical work link unavailable.