Paper Citation Record · LEDGER

How Much Can CLIP Benefit Vision-and-Language Tasks?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2107.06383.

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

pith.paper-citation-record.v1
2107.06383 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:56:16.603472Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T00:36:53.284895Z

Reference resolution

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 06c965ac-515d-47b0-8d86-5a13fd5e9f36 · inbound

Hierarchical Text-Conditional Image Generation with CLIP Latents cites this paper.

Hierarchical Text-Conditional Image Generation with CLIP Latents How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-10T16:55:57.884737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 63e1a544-2b76-4f2d-8f94-10bb981776a0 · inbound

CoCa: Contrastive Captioners are Image-Text Foundation Models cites this paper.

CoCa: Contrastive Captioners are Image-Text Foundation Models How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-15T10:53:08.501105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 257b8609-2703-419d-bd7f-42cc87b29625 · inbound

GIT: A Generative Image-to-text Transformer for Vision and Language cites this paper.

GIT: A Generative Image-to-text Transformer for Vision and Language How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:54:07.701830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 13ebeee1-ad8b-49bf-9ba1-1854afecb28b · inbound

LAION-5B: An open large-scale dataset for training next generation image-text models cites this paper.

LAION-5B: An open large-scale dataset for training next generation image-text models How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-13T14:22:17.404806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cb05c3d7-b7f6-4b6a-aace-20d7ebb73939 · inbound

InternVideo: General Video Foundation Models via Generative and Discriminative Learning cites this paper.

InternVideo: General Video Foundation Models via Generative and Discriminative Learning How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:36:53.287756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7825d19f-eb53-4f0d-bfd3-6f58d4a5bcf9 · inbound

VideoChat: Chat-Centric Video Understanding cites this paper.

VideoChat: Chat-Centric Video Understanding How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:30:00.616454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c46e81a1-d775-4997-a9d0-c1b7f6d1e4f4 · inbound

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation cites this paper.

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:30:22.567453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7c908abb-08bd-4fef-9f0e-19a196ab2a6e · inbound

GPT-4V(ision) is a Generalist Web Agent, if Grounded cites this paper.

GPT-4V(ision) is a Generalist Web Agent, if Grounded How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T19:40:13.975612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7f51676e-46bc-46ab-a39e-c9b364ed7332 · inbound

Visual Question Answering on Multiple Remote Sensing Image Modalities cites this paper.

Visual Question Answering on Multiple Remote Sensing Image Modalities How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T15:21:57.738692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30a20d7a-f05e-4890-8a86-9b15808cf933 · inbound

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward cites this paper.

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T12:06:27.824016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 755b5c06-7c0f-48b4-8ccb-8c29caa83c8e · inbound

(Almost) Free Modality Stitching of Foundation Models cites this paper.

(Almost) Free Modality Stitching of Foundation Models How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T17:47:23.698001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ed88d33-cd88-4c23-a33b-68593143e07b · inbound

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction cites this paper.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T14:52:30.367048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cb8275f-7210-4586-be21-74a5ec661e98 · inbound

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts cites this paper.

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-16T15:23:01.929185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a78330c6-8c21-4bbd-967d-f7cc685ce06c · inbound

A Survey on Semantic Communication for Vision: Categories, Frameworks, Enabling Techniques, and Applications cites this paper.

A Survey on Semantic Communication for Vision: Categories, Frameworks, Enabling Techniques, and Applications How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-03T06:46:15.177735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40fb61f7-08b2-490e-be4c-f1f62cb27ab2 · inbound

ReVision : A Post-Hoc, Vision-Based Technique for Replacing Unacceptable Concepts in Image Generation Pipeline cites this paper.

ReVision : A Post-Hoc, Vision-Based Technique for Replacing Unacceptable Concepts in Image Generation Pipeline How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T21:46:44.409774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5663d9a4-57a4-438f-9d8d-96596ad24329 · inbound

Stealthy and Adjustable Text-Guided Backdoor Attacks on Multimodal Pretrained Models cites this paper.

Stealthy and Adjustable Text-Guided Backdoor Attacks on Multimodal Pretrained Models How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:15:51.382771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c5b00289-6703-4814-b945-2178383806fe · inbound

Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation cites this paper.

Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:15:58.886998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3be7cf25-66f4-452c-ad79-910c97532f0b · inbound

UniMesh: Unifying 3D Mesh Understanding and Generation cites this paper.

UniMesh: Unifying 3D Mesh Understanding and Generation How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:56:47.284701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f8bb81e6-b1e9-46d1-9b9b-5215e824a818 · inbound

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning cites this paper.

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 82

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T07:01:12.086179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 808ed0c4-435b-46a9-a0b0-dbec6a5eae76 · inbound

Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis cites this paper.

Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis How Much Can CLIP Benefit Vision-and-Language Tasks?

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T00:56:16.603472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.