Paper Citation Record · LEDGER

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

As of 18 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 9 inbound Pith citation observations for arXiv:2411.16828.

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

pith.paper-citation-record.v1
2411.16828 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:57:12.054681Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:29:57.356586Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:39:50.707139Z

Reference resolution

55 of 55 outbound references displayed

verified exact0
verified fuzzy19
unresolved36
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 87a9bce5-8af8-4d75-aece-df6652e9943c · outbound

This paper cites GPT-4 Technical Report.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation 5d27400c-8ca4-4ae7-9221-91b6b7517cc0 · outbound

This paper cites nocaps: novel object caption- ing at scale.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions nocaps: novel object caption- ing at scale

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:13.393647Z

Source-reported events for the cited work

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Observation 9c7aa08c-03a6-4128-be0d-7933828bdbe0 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

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Source-reported events for the cited work

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Observation d0a64e86-c10a-46ae-b785-ac4b59bec140 · outbound

This paper cites Contrastive Localized Language-Image Pre-Training.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Contrastive Localized Language-Image Pre-Training

Reference 4

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Source-reported events for the cited work

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Observation d865697b-4c7d-4f3d-8ded-4c99fe4736f3 · outbound

This paper cites PixArt-\Sigma: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions PixArt-\Sigma: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T12:57:11.689555Z

Source-reported events for the cited work

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Observation 2fa93cab-c879-401a-93bf-f6af44de8b9a · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T12:57:11.695395Z

Source-reported events for the cited work

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Observation a6c63e58-115e-4a5c-9fcf-14d6cd4b683c · outbound

This paper cites PaLI: A Jointly-Scaled Multilingual Language-Image Model.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions PaLI: A Jointly-Scaled Multilingual Language-Image Model

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T12:57:11.701555Z

Source-reported events for the cited work

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Observation 31d3cbf0-4c91-43ab-b5ec-87d41022b000 · outbound

This paper cites Uniter: Universal image-text representation learning.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Uniter: Universal image-text representation learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T12:57:11.710436Z

Source-reported events for the cited work

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Observation 856507f4-b276-45cd-b87d-591fca256d3d · outbound

This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 9

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Source-reported events for the cited work

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Observation 19eac34b-3930-450a-a17e-cc60b3b72e55 · outbound

This paper cites MobileVLM V2: Faster and Stronger Baseline for Vision Language Model.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions MobileVLM V2: Faster and Stronger Baseline for Vision Language Model

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T12:57:11.727721Z

Source-reported events for the cited work

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Observation f8190cd5-b06b-4614-854d-11611a82aa61 · outbound

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

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Imagenet: A large-scale hierarchical image database

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T12:57:11.734320Z

Source-reported events for the cited work

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Observation f2ebdab8-4d15-4188-a959-e3da8492db67 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 12

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Source-reported events for the cited work

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Observation b9f5d061-4bfd-406c-acde-9f0c709a33cf · outbound

This paper cites The Llama 3 Herd of Models.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions The Llama 3 Herd of Models

Reference 13

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Source-reported events for the cited work

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Observation 82a20a60-25b5-4c7f-a116-bb3244b52271 · outbound

This paper cites Improving clip training with language rewrites.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Improving clip training with language rewrites

Reference 14

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Source-reported events for the cited work

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Observation 23714bab-d68e-4368-b4ad-f8eb6dbd2213 · outbound

This paper cites Data Filtering Networks.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Data Filtering Networks

Reference 15

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Source-reported events for the cited work

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Observation d164bd10-f6a1-4f7e-a598-75097867be19 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 16

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Observation 675b36ef-7343-423b-a2b9-774c7b581dac · outbound

This paper cites Dat- acomp: In search of the next generation of multimodal datasets.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Dat- acomp: In search of the next generation of multimodal datasets

Reference 17

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Source-reported events for the cited work

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Observation c0e496eb-6e35-46fc-8f0d-99aa2501f4af · outbound

This paper cites SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?

Reference 18

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Source-reported events for the cited work

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Observation d0e9be35-437e-48ee-be88-39a63aab6713 · outbound

This paper cites Gqa: A new dataset for real-world visual reasoning and compositional question answering.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:13.247902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7e1d1dc0-b2cb-4289-961c-7305b5a4e58e · outbound

This paper cites Open- clip.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Open- clip

Reference 20

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Source-reported events for the cited work

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Observation 4e663a27-f256-4864-8de8-a8110ad34162 · outbound

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

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 21

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Source-reported events for the cited work

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Observation e77d857e-3b87-4a6d-9e35-25bcd6e60d66 · outbound

This paper cites Vilt: Vision- and-language transformer without convolution or region su- pervision.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Vilt: Vision- and-language transformer without convolution or region su- pervision

Reference 22

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Source-reported events for the cited work

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Observation 2fafa437-3385-432e-ad67-33adf7348b28 · outbound

This paper cites Veclip: Improving clip training via visual-enriched captions.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Veclip: Improving clip training via visual-enriched captions

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:13.164438Z

Source-reported events for the cited work

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Observation 9299736a-f2b8-4ea5-9d26-fa4dbc5a0f44 · outbound

This paper cites Modeling Caption Diversity in Contrastive Vision-Language Pretraining.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Modeling Caption Diversity in Contrastive Vision-Language Pretraining

Reference 24

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Observation 94c672f7-5eae-4a63-a2d5-3b53ef73108d · outbound

This paper cites Align before fuse: Vision and language representation learn- ing with momentum distillation.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Align before fuse: Vision and language representation learn- ing with momentum distillation

Reference 25

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Observation c46fb3ea-2ed2-4ca7-a8c7-00abf378e968 · outbound

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

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 26

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Observation fed288c3-f5a6-467a-aa17-970573b7dd0f · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 27

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Observation d1171e4b-2022-4e26-9bcf-245de887639f · outbound

This paper cites VisualBERT: A Simple and Performant Baseline for Vision and Language.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions VisualBERT: A Simple and Performant Baseline for Vision and Language

Reference 28

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Observation 4886e482-f71b-40e5-baa4-cff250d1c4af · outbound

This paper cites CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy

Reference 29

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Observation 40b79ca7-7d68-4d30-ae59-f2fc638f8802 · outbound

This paper cites What If We Recaption Billions of Web Images with LLaMA-3?.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions What If We Recaption Billions of Web Images with LLaMA-3?

Reference 30

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Observation 118f6ee0-5eb3-442b-834f-a3b6a43de51f · outbound

This paper cites An inverse scal- ing law for clip training.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions An inverse scal- ing law for clip training

Reference 31

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Observation 3d6e3517-fe59-4b9f-8675-3d1cd0181484 · outbound

This paper cites Evaluating object hallucination in large vision-language models.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Evaluating object hallucination in large vision-language models

Reference 32

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Observation 2e13e9a0-7ba8-4341-8a23-3029afa06591 · outbound

This paper cites MoE-LLaVA: Mixture of Experts for Large Vision-Language Models.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Reference 33

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This paper cites Microsoft coco: Common objects in context.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Microsoft coco: Common objects in context

Reference 34

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Observation 4c7bcbe9-72e3-4cc9-a67d-2f9137696731 · outbound

This paper cites Improved baselines with visual instruction tuning.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Improved baselines with visual instruction tuning

Reference 35

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Observation 974a6fed-75b7-42fe-a859-4a80f5947e52 · outbound

This paper cites Visual instruction tuning.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Visual instruction tuning

Reference 36

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Observation 2def70fc-4104-4b95-9f14-89fd72aaa89d · outbound

This paper cites MLLMs-Augmented Visual-Language Representation Learning.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions MLLMs-Augmented Visual-Language Representation Learning

Reference 37

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This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks

Reference 38

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This paper cites ChartQA: A benchmark for question answer- ing about charts with visual and logical reasoning.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions ChartQA: A benchmark for question answer- ing about charts with visual and logical reasoning

Reference 39

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Observation 1f25dc0d-99d3-4021-8a8e-2ab38f1d389f · outbound

This paper cites Introducing meta llama 3: The most capable openly available llm to date.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Introducing meta llama 3: The most capable openly available llm to date

Reference 40

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Observation 95029b9b-1135-47f5-9d57-a8d123894450 · outbound

This paper cites Improving multimodal datasets with image captioning.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Improving multimodal datasets with image captioning

Reference 41

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Observation 864f0c83-36d8-4123-8902-435d856882bb · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Representation Learning with Contrastive Predictive Coding

Reference 42

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This paper cites Introducing chatgpt.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Introducing chatgpt

Reference 43

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Observation 7bc454e2-6576-4262-a68c-d1ddbcdcf4b4 · outbound

This paper cites Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models

Reference 44

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

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Learning transferable visual models from natural language supervi- sion

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:12.850186Z

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Observation d2d1b4a7-cc30-46b9-b26b-46a15f778456 · outbound

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

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 46

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Observation 717c274e-ca7c-44aa-9a32-90881f0de1df · outbound

This paper cites Towards vqa models that can read.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Towards vqa models that can read

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:12.805935Z

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Observation 35637afb-a9e7-457d-99da-76ec8784bc20 · outbound

This paper cites Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:12.778594Z

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Observation d8bc428a-7b52-45df-a683-b0a6d8981a14 · outbound

This paper cites MOFI: Learning Image Representations from Noisy Entity Annotated Images.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions MOFI: Learning Image Representations from Noisy Entity Annotated Images

Reference 49

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Observation b9f44da5-3e99-4cbb-80f9-d7d23d07b23e · outbound

This paper cites Alip: Adaptive language-image pre-training with synthetic cap- tion.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Alip: Adaptive language-image pre-training with synthetic cap- tion

Reference 50

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Observation dbd676ce-f04c-43ee-944b-1e300a7a59b0 · outbound

This paper cites FILIP: Fine-grained Interactive Language-Image Pre-Training.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions FILIP: Fine-grained Interactive Language-Image Pre-Training

Reference 51

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Observation f5cf8247-e0e0-49ea-a7ce-7f2cacd0fc0f · outbound

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

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 52

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Observation 86a5d4ed-52e1-4694-9baa-893666e4f0ce · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understand- ing and reasoning benchmark for expert agi.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Mmmu: A massive multi-discipline multimodal understand- ing and reasoning benchmark for expert agi

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:12.744561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b7a435bc-b58a-4d30-bb5b-a618fd2e5103 · outbound

This paper cites Sigmoid loss for language image pre-training.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Sigmoid loss for language image pre-training

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:12.724421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0d5b9789-3e86-4abd-b014-b6b57742864a · outbound

This paper cites Dreamlip: Language- image pre-training with long captions.

CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions Dreamlip: Language- image pre-training with long captions

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:57:12.695816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation ffcd5aec-4fd6-4615-9460-aa3aa72f2de1 · inbound

OpenVision: A Fully-Open, Cost-Effective Family of Advanced Vision Encoders for Multimodal Learning cites this paper.

OpenVision: A Fully-Open, Cost-Effective Family of Advanced Vision Encoders for Multimodal Learning CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T23:29:57.356586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94e9f23b-b96e-4e8a-a73a-bc3f5e4dfeb2 · inbound

Mining Contextualized Visual Associations from Images for Creativity Understanding cites this paper.

Mining Contextualized Visual Associations from Images for Creativity Understanding CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T18:09:27.053527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f876f1b0-ae10-46cd-b18b-7130a3aece66 · inbound

MobileCLIP2: Improving Multi-Modal Reinforced Training cites this paper.

MobileCLIP2: Improving Multi-Modal Reinforced Training CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T14:59:19.577024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd5172db-a689-4111-ae86-087c771bf7ab · inbound

OpenVision 2: A Family of Generative Pretrained Visual Encoders for Multimodal Learning cites this paper.

OpenVision 2: A Family of Generative Pretrained Visual Encoders for Multimodal Learning CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T12:22:35.606923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f7bbdb0-2b4d-4391-9dce-876277e74df8 · inbound

Let ViT Speak: Generative Language-Image Pre-training cites this paper.

Let ViT Speak: Generative Language-Image Pre-training CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:01:07.255186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e7a00b24-9bbb-4774-a8e9-96d0caa49fbf · inbound

Let ViT Speak: Generative Language-Image Pre-training cites this paper.

Let ViT Speak: Generative Language-Image Pre-training CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-01T07:35:28.764723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c35d4c3c-47fc-4f60-bc6e-2dff7871274c · inbound

Investigating Adversarial Robustness of Multi-modal Large Language Models cites this paper.

Investigating Adversarial Robustness of Multi-modal Large Language Models CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:06:27.577528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 66670d96-e570-4654-bdfa-0efce984068c · inbound

Beyond False Stability: High-Noise Drift Gating for Test-Time Adversarial Defenses in Vision-Language Models cites this paper.

Beyond False Stability: High-Noise Drift Gating for Test-Time Adversarial Defenses in Vision-Language Models CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:16:26.830996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 46823c8a-a6ee-4e93-945b-adc5fa8d4ea2 · inbound

ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP cites this paper.

ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:39:50.708849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.