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Paper Citation Record · LEDGER

Active Learning via Vision-Language Model Adaptation with Open Data

As of 8 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2506.01724.

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

pith.paper-citation-record.v1
2506.01724 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

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measured 59 of 59 standing notices

One-hop event checks from named stored sources.

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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

59 of 59 outbound references displayed

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External citation measurements

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Outbound references

Observation c7f7aa62-21d5-4ed3-b3fa-6e15f7107b28 · outbound

This paper cites Gone fishing: Neural active learning with fisher embeddings.

Active Learning via Vision-Language Model Adaptation with Open Data Gone fishing: Neural active learning with fisher embeddings

Reference 1

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Observation b6d7fac5-4113-41e5-9e8b-9a7e65a967b3 · outbound

This paper cites Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, and Alekh Agarwal.

Active Learning via Vision-Language Model Adaptation with Open Data Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, and Alekh Agarwal

Reference 2

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This paper cites Active prompt learning in vision language models.

Active Learning via Vision-Language Model Adaptation with Open Data Active prompt learning in vision language models

Reference 3

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This paper cites Retrieval-augmented diffusion models.

Active Learning via Vision-Language Model Adaptation with Open Data Retrieval-augmented diffusion models

Reference 4

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Observation 539146d8-67cb-4150-8b34-2bbf77adf740 · outbound

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

Active Learning via Vision-Language Model Adaptation with Open Data Food-101 - mining discriminative components with random forests

Reference 5

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This paper cites Visualgpt: Data-efficient adaptation of pretrained language models for image captioning.

Active Learning via Vision-Language Model Adaptation with Open Data Visualgpt: Data-efficient adaptation of pretrained language models for image captioning

Reference 6

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Observation 4182c797-f4c8-4782-bbbe-97892e608eed · outbound

This paper cites Re-imagen: Retrieval-augmented text-to-image generator.

Active Learning via Vision-Language Model Adaptation with Open Data Re-imagen: Retrieval-augmented text-to-image generator

Reference 7

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Observation 8909df83-3541-4f77-ae33-c55468748035 · outbound

This paper cites Reproducible scaling laws for contrastive language-image learning.

Active Learning via Vision-Language Model Adaptation with Open Data Reproducible scaling laws for contrastive language-image learning

Reference 9

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Active Learning via Vision-Language Model Adaptation with Open Data Unresolved cited work

Reference 10

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This paper cites Deep bayesian active learning with image data.

Active Learning via Vision-Language Model Adaptation with Open Data Deep bayesian active learning with image data

Reference 11

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

Active Learning via Vision-Language Model Adaptation with Open Data Finetune like you pretrain: Improved finetuning of zero-shot vision models

Reference 12

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Observation 1e797bf9-fb26-420f-a9ed-19516a088146 · outbound

This paper cites From images to textual prompts: Zero-shot visual question answering with frozen large language models.

Active Learning via Vision-Language Model Adaptation with Open Data From images to textual prompts: Zero-shot visual question answering with frozen large language models

Reference 13

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Observation 8ab377c0-9b66-473f-93ed-bc7777ce63da · outbound

This paper cites Retrieval augmented language model pre-training.

Active Learning via Vision-Language Model Adaptation with Open Data Retrieval augmented language model pre-training

Reference 14

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Observation 2f27950f-b69f-405a-9153-644e33a64273 · outbound

This paper cites Using trusted data to train deep networks on labels corrupted by severe noise.

Active Learning via Vision-Language Model Adaptation with Open Data Using trusted data to train deep networks on labels corrupted by severe noise

Reference 15

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Observation c74d45b5-c5a5-4a6c-b805-00d4621df0a9 · outbound

This paper cites Entropy-based active learning for object recognition.

Active Learning via Vision-Language Model Adaptation with Open Data Entropy-based active learning for object recognition

Reference 16

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Observation 71ff839e-743b-4b14-a51d-d37b0f4156be · outbound

This paper cites Active learning by learning.

Active Learning via Vision-Language Model Adaptation with Open Data Active learning by learning

Reference 17

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Observation 96e1a8ee-fa29-4a8a-b32a-741d03d627f8 · outbound

This paper cites Active learning by querying informative and representative examples.

Active Learning via Vision-Language Model Adaptation with Open Data Active learning by querying informative and representative examples

Reference 18

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Observation e2384fec-4f94-4356-8f10-06b5f3867f02 · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision.

Active Learning via Vision-Language Model Adaptation with Open Data Scaling up visual and vision-language representation learning with noisy text supervision

Reference 19

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Observation 29d7ce26-ed8c-42d2-8d90-edd0658540e0 · outbound

This paper cites Maple: Multi-modal prompt learning.

Active Learning via Vision-Language Model Adaptation with Open Data Maple: Multi-modal prompt learning

Reference 20

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Observation 8ed6b6d6-7bc7-4fc4-9a7c-a80212f138a0 · outbound

This paper cites Re-thinking federated active learning based on inter-class diversity.

Active Learning via Vision-Language Model Adaptation with Open Data Re-thinking federated active learning based on inter-class diversity

Reference 21

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This paper cites Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning.

Active Learning via Vision-Language Model Adaptation with Open Data Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning

Reference 22

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This paper cites 3d object representations for fine-grained categorization.

Active Learning via Vision-Language Model Adaptation with Open Data 3d object representations for fine-grained categorization

Reference 23

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This paper cites Fine-tuning can distort pretrained features and underperform out-of-distribution.

Active Learning via Vision-Language Model Adaptation with Open Data Fine-tuning can distort pretrained features and underperform out-of-distribution

Reference 24

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This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks.

Active Learning via Vision-Language Model Adaptation with Open Data Retrieval- augmented generation for knowledge-intensive nlp tasks

Reference 25

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Observation fd448916-406a-46df-bc41-a6d2aedbddbb · outbound

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Active Learning via Vision-Language Model Adaptation with Open Data Internet explorer: Targeted representation learning on the open web

Reference 26

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This paper cites Align before fuse: Vision and language representation learning with momentum distillation.

Active Learning via Vision-Language Model Adaptation with Open Data Align before fuse: Vision and language representation learning with momentum distillation

Reference 27

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This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

Active Learning via Vision-Language Model Adaptation with Open Data Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 28

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Active Learning via Vision-Language Model Adaptation with Open Data Active learning with multi-label svm classification

Reference 29

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This paper cites Multimodality helps unimodality: Cross-modal few-shot learning with multimodal models.

Active Learning via Vision-Language Model Adaptation with Open Data Multimodality helps unimodality: Cross-modal few-shot learning with multimodal models

Reference 30

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This paper cites Learn- ing customized visual models with retrieval-augmented knowledge.

Active Learning via Vision-Language Model Adaptation with Open Data Learn- ing customized visual models with retrieval-augmented knowledge

Reference 31

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Observation 3ee9f2b2-d9df-46a3-bf11-48000a22fb29 · outbound

This paper cites Few-shot recognition via stage-wise retrieval- augmented finetuning.

Active Learning via Vision-Language Model Adaptation with Open Data Few-shot recognition via stage-wise retrieval- augmented finetuning

Reference 32

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Active Learning via Vision-Language Model Adaptation with Open Data Influence selection for active learning

Reference 33

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Observation a313219d-e432-4f26-b52c-f62a65eba7a7 · outbound

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Active Learning via Vision-Language Model Adaptation with Open Data Fine-Grained Visual Classification of Aircraft

Reference 34

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This paper cites A study of the effect of different types of noise on the precision of supervised learning techniques.

Active Learning via Vision-Language Model Adaptation with Open Data A study of the effect of different types of noise on the precision of supervised learning techniques

Reference 35

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Observation 28e7cf55-e37a-4ad5-a88d-8894d2dfbfd9 · outbound

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Active Learning via Vision-Language Model Adaptation with Open Data The neglected tails in vision-language models

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ded3561f-714e-45cb-8e54-9d4f2493e9eb · outbound

This paper cites Cats and dogs.

Active Learning via Vision-Language Model Adaptation with Open Data Cats and dogs

Reference 37

Resolution
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raw_fallback, observed 2026-08-07T11:41:45.646486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.309275Z digest=sha256:928e4a570779c48ab14d5ab72e7211e98add443d814c0e64f02d59d54e1f7eaa

Observation 655f4209-2914-4a95-8fe0-1df578532bc6 · outbound

This paper cites Active learning by feature mixing.

Active Learning via Vision-Language Model Adaptation with Open Data Active learning by feature mixing

Reference 38

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.312428Z digest=sha256:c9a049062399dcdcfe0eee6c3d0fa5f0e23c68ca8e1fbc1147066e1ff090dd41

Observation 2e27cafc-ec4b-4031-8f77-f9882795037d · outbound

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

Active Learning via Vision-Language Model Adaptation with Open Data Learning transferable visual models from natural language supervision

Reference 39

Resolution
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no resolver link, observed 2026-08-07T11:41:45.315789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ce15670e-62c3-451b-a85c-0e60288eb4e2 · outbound

This paper cites A survey of deep active learning.

Active Learning via Vision-Language Model Adaptation with Open Data A survey of deep active learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T11:41:45.318921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4a3db938-cc8f-4af3-965e-c5421d4e1493 · outbound

This paper cites Margin-based active learning for structured output spaces.

Active Learning via Vision-Language Model Adaptation with Open Data Margin-based active learning for structured output spaces

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.614244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.322507Z digest=sha256:f4382b2256773cb1a8bfd752904dec6a282e8a63c7013257b4daba6a42c1a3c0

Observation 446e8fcd-a9e7-400e-bf5b-e9e7a73c190e · outbound

This paper cites Consistency-guided prompt learning for vision-language models.

Active Learning via Vision-Language Model Adaptation with Open Data Consistency-guided prompt learning for vision-language models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.604355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.325685Z digest=sha256:8c9cae363efc025c9c2383d940ba0d72d737fbfcfd452b9914e643edf089a001

Observation aa926a14-4e28-4c5a-8c69-08bcdc1ecb40 · outbound

This paper cites an unresolved cited work.

Active Learning via Vision-Language Model Adaptation with Open Data Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:41:45.594997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.328535Z digest=sha256:e3cee9d77a2562a9c2978e5aea83560ad9f7fd0239ef61aa1e9adb4ac90acd4c

Observation a8282701-4202-4672-b04a-4e8de5fdd667 · outbound

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

Active Learning via Vision-Language Model Adaptation with Open Data LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T11:41:45.332344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:41:45.332344Z digest=sha256:28c38a980492eca10c4f717bc6c3dff3b564ae8db67deb032e2510579f5fbd37

Observation f926d6c6-6569-4687-8289-e09230c348eb · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Active Learning via Vision-Language Model Adaptation with Open Data Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 45

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.335986Z digest=sha256:ae530b0b1d70a30340a9f4ec1e7ee4f5d8fb227f4f9f1b756342c89c02f38cc6

Observation 6a0cd5ab-2e3d-406c-a82e-58f95e7b88be · outbound

This paper cites Active learning for convolutional neural networks: A core-set approach.

Active Learning via Vision-Language Model Adaptation with Open Data Active learning for convolutional neural networks: A core-set approach

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.577559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.338756Z digest=sha256:9ddbee33a918c032a34a8da455ca2e334c62e8027c7696cdfa7a1daffd3fb614

Observation c60b462a-40f6-46a8-949e-154e5b03b488 · outbound

This paper cites Active learning literature survey.

Active Learning via Vision-Language Model Adaptation with Open Data Active learning literature survey

Reference 47

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 89babf7b-b40b-499a-9fd6-5d5fcb1cf8bd · outbound

This paper cites Get another label? improving data quality and data mining using multiple, noisy labelers.

Active Learning via Vision-Language Model Adaptation with Open Data Get another label? improving data quality and data mining using multiple, noisy labelers

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.559936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.344265Z digest=sha256:1be0ee2e961cd284a1e1b0b59cf86b5183ad8adba6e4c95cde827d6372de44a7

Observation a55fd671-2900-42b6-9621-d4f8595f4a9e · outbound

This paper cites The Semi-Supervised iNaturalist-Aves Challenge at FGVC7 Workshop.

Active Learning via Vision-Language Model Adaptation with Open Data The Semi-Supervised iNaturalist-Aves Challenge at FGVC7 Workshop

Reference 49

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 63174898-27a3-4c16-8c88-e2bc206104f0 · outbound

This paper cites Alpha-clip: A clip model focusing on wherever you want.

Active Learning via Vision-Language Model Adaptation with Open Data Alpha-clip: A clip model focusing on wherever you want

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.549752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.351191Z digest=sha256:af7646278e80c5f26c2831b7a82295387e3edc6ad32291c1bfb875bb9ebb0865

Observation 51b82251-8813-432a-8fcd-58629209fda1 · outbound

This paper cites Neural priming for sample-efficient adaptation.

Active Learning via Vision-Language Model Adaptation with Open Data Neural priming for sample-efficient adaptation

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.540822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.354292Z digest=sha256:0976d94548368c87709ebe49f683d8c3ca0c8306dcd5e648bea0c43724b015fd

Observation 5ce25162-e551-4104-b291-b0a47722b421 · outbound

This paper cites A new active labeling method for deep learning.

Active Learning via Vision-Language Model Adaptation with Open Data A new active labeling method for deep learning

Reference 52

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation da65fe80-8679-4e63-869e-8355373b1541 · outbound

This paper cites Cogvlm: Visual expert for pretrained language models.

Active Learning via Vision-Language Model Adaptation with Open Data Cogvlm: Visual expert for pretrained language models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.522059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.360743Z digest=sha256:aa360d8244f774b941d4a872d1c79d0fe3bbe3b86dcbea80bb56db24e490a025

Observation bea61144-3f35-4fe3-bc64-6447bf0c16f1 · outbound

This paper cites Debiased learning from naturally imbalanced pseudo-labels.

Active Learning via Vision-Language Model Adaptation with Open Data Debiased learning from naturally imbalanced pseudo-labels

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.511602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f814479d-0bdf-4492-a253-f0783f594661 · outbound

This paper cites Aligning pretraining for detection via object-level contrastive learning.

Active Learning via Vision-Language Model Adaptation with Open Data Aligning pretraining for detection via object-level contrastive learning

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.501442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.366687Z digest=sha256:1e770625b325ffc6ec3f028eea1a54e65ba3b839e71bd8743f8a1c735d653826

Observation eb59e3d3-ac0a-4ba1-ae2b-83106250d893 · outbound

This paper cites Using active learning to expand training data for implicit discourse relation recognition.

Active Learning via Vision-Language Model Adaptation with Open Data Using active learning to expand training data for implicit discourse relation recognition

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.490940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.369989Z digest=sha256:0d448624432bdec8a73811adba610bd6f47c4b50ea389b9b2fa045f0906b8950

Observation e59fffd7-8530-428e-a9f9-9e1143a74345 · outbound

This paper cites Multi-class active learning by uncertainty sampling with diversity maximization.

Active Learning via Vision-Language Model Adaptation with Open Data Multi-class active learning by uncertainty sampling with diversity maximization

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.480768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.372764Z digest=sha256:ad0c126c0e7559e7dd3b1aee231ce070973021008c96916b489997199763bfb7

Observation 62906a95-d74c-43a7-b605-f42113334afe · outbound

This paper cites Learning loss for active learning.

Active Learning via Vision-Language Model Adaptation with Open Data Learning loss for active learning

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.471194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.375730Z digest=sha256:3e9127cf6b197f19a7ce04999a868c1dbc86d04ca07a8c3227dfb11c41bd7b84

Observation b56ba36e-1009-4930-bf80-b20ce4c6ac73 · outbound

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

Active Learning via Vision-Language Model Adaptation with Open Data Conditional prompt learning for vision-language models

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:41:45.461243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.378527Z digest=sha256:b6d4cbb7b032a950ddd04c3b1603f19690b81bb2f392c0eeba774a9a946c43cf

Observation 4ad0daf1-b5b2-48d6-b416-30f24629fbd0 · outbound

This paper cites 727-200" (Aircraft dataset) retrieves an eBay product listing titled.

Active Learning via Vision-Language Model Adaptation with Open Data 727-200" (Aircraft dataset) retrieves an eBay product listing titled

Reference 60

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T11:41:45.451299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:41:45.381538Z digest=sha256:e8596f8e057195212c25fb14945a343e30cc87b289bf78a8667444ea0da0753b

Pith citing papers

No inbound Pith citation observations are available.