Paper Citation Record · LEDGER

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning

As of 11 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2412.16956.

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

pith.paper-citation-record.v1
2412.16956 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T06:02:33.456917Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

46 of 46 outbound references displayed

verified exact0
verified fuzzy38
unresolved8
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3bfb9588-3736-471c-a7d9-810529d7981e · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 1

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Source-reported events for the cited work

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Observation 442a3f6a-7188-44b0-ad77-701517cdb9fd · outbound

This paper cites Learning transferable visual models from natural language supervi- sion,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Learning transferable visual models from natural language supervi- sion,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.189003Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 46887a49-4c42-4801-b4e9-c7d937f7313a · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning High- resolution image synthesis with latent diffusion models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.173485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 40152de4-07e8-4af1-84b7-4194e6318880 · outbound

This paper cites Dual cross- attention learning for fine-grained visual categorization and object re- identification,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Dual cross- attention learning for fine-grained visual categorization and object re- identification,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.158312Z

Source-reported events for the cited work

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Observation 50c9ff26-5912-4e00-aa00-720e42956830 · outbound

This paper cites Distribution-aware data expansion with diffusion models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Distribution-aware data expansion with diffusion models,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.143181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 14113b3a-6b95-474c-86cf-f0072a6988af · outbound

This paper cites Dip-go: A diffusion pruner via few-step gradient optimization,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Dip-go: A diffusion pruner via few-step gradient optimization,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.127592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 69fa2f2f-2f50-4c2d-a795-c150b904dd7d · outbound

This paper cites Visual prompt tuning,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Visual prompt tuning,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2f3386be-9a9a-4d8e-b17e-310325481e84 · outbound

This paper cites Sensitivity-aware visual parameter-efficient fine-tuning,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Sensitivity-aware visual parameter-efficient fine-tuning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.097663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 11151b22-fb58-45b5-8435-d0ce3cf9487f · outbound

This paper cites Neural Prompt Search.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Neural Prompt Search

Reference 9

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Source-reported events for the cited work

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Observation 9b60d207-c985-4138-8b17-34d420463cdd · outbound

This paper cites E2vpt: An effective and efficient approach for visual prompt tuning,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning E2vpt: An effective and efficient approach for visual prompt tuning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.082474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b36e0d65-08c1-47e3-a38a-21eb5a9e9eed · outbound

This paper cites Convolutional Bypasses Are Better Vision Transformer Adapters.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T06:02:33.274732Z

Source-reported events for the cited work

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Observation 0e79d7e7-5f2f-4bbb-8a9e-4106ca3cde60 · outbound

This paper cites Adapt- former: Adapting vision transformers for scalable visual recognition,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Adapt- former: Adapting vision transformers for scalable visual recognition,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.066985Z

Source-reported events for the cited work

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Observation 47ffcd57-208f-4b6a-abde-e6650a8ae911 · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning LoRA: Low-rank adaptation of large language models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.050999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0cafaea2-f387-4c6f-a38a-228d67ad5ce9 · outbound

This paper cites Side-tuning: a baseline for network adaptation via additive side networks,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Side-tuning: a baseline for network adaptation via additive side networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.035847Z

Source-reported events for the cited work

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Observation 7df72a8f-4335-40c6-bd3c-921c3dfda6ba · outbound

This paper cites Sct: A simple baseline for parameter-efficient fine-tuning via salient channels,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Sct: A simple baseline for parameter-efficient fine-tuning via salient channels,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.020311Z

Source-reported events for the cited work

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Observation 06e1e111-315a-41f1-a294-ed8f2fe3203d · outbound

This paper cites Sa 2vp: Spatially aligned-and-adapted visual prompt,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Sa 2vp: Spatially aligned-and-adapted visual prompt,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:34.004892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9373e8fb-cf07-4e24-af38-1229717c636e · outbound

This paper cites Lion: Implicit vision prompt tuning,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Lion: Implicit vision prompt tuning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.989757Z

Source-reported events for the cited work

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Observation 93a076ee-fa33-403b-b940-b66f5f0e9505 · outbound

This paper cites Argue: Attribute-guided prompt tuning for vision-language models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Argue: Attribute-guided prompt tuning for vision-language models,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.974300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9ea15752-bfc9-4da8-85af-364621142827 · outbound

This paper cites Aapl: Adding attributes to prompt learning for vision-language models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Aapl: Adding attributes to prompt learning for vision-language models,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.959632Z

Source-reported events for the cited work

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Observation d0897e2e-19e0-4d76-9844-a701809bbe3d · outbound

This paper cites Tinytl: Reduce memory, not pa- rameters for efficient on-device learning,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Tinytl: Reduce memory, not pa- rameters for efficient on-device learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.944810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4a9c55bf-d0e3-4bfe-986b-fce519bdbfeb · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Parameter-efficient transfer learning for nlp,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.929603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d4bafd1f-c76d-400b-9875-4e2e457f0850 · outbound

This paper cites Tip-adapter: Training-free clip-adapter for better vision-language modeling,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Tip-adapter: Training-free clip-adapter for better vision-language modeling,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.914174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 39a8024e-506c-4293-adae-27a1e9b7ce7d · outbound

This paper cites Revisiting the parameter efficiency of adapters from the perspective of precision redundancy,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Revisiting the parameter efficiency of adapters from the perspective of precision redundancy,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.898849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 63cbdab1-9b30-4b54-a5eb-5d2384a8bdc5 · outbound

This paper cites Learning multiple visual domains with residual adapters,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Learning multiple visual domains with residual adapters,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.884024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1fc05c77-8407-42c8-a0aa-c7c9371842a5 · outbound

This paper cites AdapterHub: A Framework for Adapting Transformers.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning AdapterHub: A Framework for Adapting Transformers

Reference 25

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Source-reported events for the cited work

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Observation b63ee76e-480e-435c-8d03-a7166060ee46 · outbound

This paper cites Caps-adapter: Caption-based multi- modal adapter in zero-shot classification,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Caps-adapter: Caption-based multi- modal adapter in zero-shot classification,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.868345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1e91cccf-116f-4600-bd13-b062c2329db1 · outbound

This paper cites Distribution-aware prompt tuning for vision-language models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Distribution-aware prompt tuning for vision-language models,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.853598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 30f82720-1ab7-4fdb-8a1f-4cbfc36504b3 · outbound

This paper cites Understanding and improving visual prompting: A label-mapping perspective,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Understanding and improving visual prompting: A label-mapping perspective,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.838444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b8eab316-f3cb-462b-9211-7c95c545b264 · outbound

This paper cites Autovp: An au- tomated visual prompting framework and benchmark,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Autovp: An au- tomated visual prompting framework and benchmark,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.823264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bcbb9368-8555-4405-87c3-1fc0b63937c0 · outbound

This paper cites Progressive Visual Prompt Learning with Contrastive Feature Re-formation.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Progressive Visual Prompt Learning with Contrastive Feature Re-formation

Reference 31

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Source-reported events for the cited work

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Observation 8eef9bff-d902-49ad-b923-e01c2d3c120f · outbound

This paper cites Hierarchical Side-Tuning for Vision Transformers.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Hierarchical Side-Tuning for Vision Transformers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T06:02:33.382208Z

Source-reported events for the cited work

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Observation 38476415-6dae-43eb-8773-bed6e9c58852 · outbound

This paper cites Exploring Visual Prompts for Adapting Large-Scale Models.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Exploring Visual Prompts for Adapting Large-Scale Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T06:02:33.387616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3f9f079-4dfc-4ec9-b06d-5737efd5944e · outbound

This paper cites Diversity-aware meta visual prompting,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Diversity-aware meta visual prompting,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.807785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7d09e14e-b3d5-4199-a69a-fea6de943232 · outbound

This paper cites Apollo: Unified adapter and prompt learning for vision language models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Apollo: Unified adapter and prompt learning for vision language models,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.792479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5a804154-c674-4a9e-9cec-2a33896cd1e4 · outbound

This paper cites Dynamic focus-aware positional queries for semantic segmentation,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Dynamic focus-aware positional queries for semantic segmentation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.775921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e0ba85c8-a811-4251-bab6-f1292d104634 · outbound

This paper cites Adept: Adapter-based efficient prompt tuning approach for language models,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Adept: Adapter-based efficient prompt tuning approach for language models,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.760022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dca2173a-3d2d-4671-8fee-fba4e1736994 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.744591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7b0d159d-d1b4-4b67-a9e1-f32679408ef7 · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.728021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 49d1621b-d6b4-4ec9-89dd-fbdee810205a · outbound

This paper cites Some methods for classification and analysis of multi- variate observations,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Some methods for classification and analysis of multi- variate observations,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.711944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c7581f7f-93fb-4d80-b1dd-c1380c4b611b · outbound

This paper cites A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T06:02:33.427453Z

Source-reported events for the cited work

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Observation a2ad7aa8-8e83-439f-bd69-451fe952535a · outbound

This paper cites Fixing weight decay regularization in adam,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Fixing weight decay regularization in adam,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.695128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 85d33aa0-fa3e-4ac6-9797-cf83f017fb8d · outbound

This paper cites Diversity-aware meta visual prompting,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Diversity-aware meta visual prompting,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.676626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 47ec2f35-066d-4e38-84db-ebbd7d05cdc2 · outbound

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

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Imagenet: A large-scale hierarchical image database,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.660933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 00628907-1ad7-4c98-876f-bc77a07e026d · outbound

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

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Learning multiple layers of features from tiny images,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.644836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 788cfeac-d60b-4844-9b52-9c7155923631 · outbound

This paper cites Sun database: Large-scale scene recognition from abbey to zoo,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Sun database: Large-scale scene recognition from abbey to zoo,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.628519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1c7f5bb0-7ba7-4cb5-88c4-cbe84c23ea9d · outbound

This paper cites Cats and dogs,.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Cats and dogs,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T06:02:33.611273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

No inbound Pith citation observations are available.