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Paper Citation Record · LEDGER

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 50 inbound Pith citation observations for arXiv:2102.05918.

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

pith.paper-citation-record.v1
2102.05918 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 50 of 50 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:12:08.581177Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

1196
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation eb4228ba-fe36-47c9-87b6-027482e7a144 · inbound

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

LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 3

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arxiv_id, observed 2026-05-12T10:21:01.079608Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6085eebd-ed68-41ce-b8dc-6c865a7e665b · inbound

Florence: A New Foundation Model for Computer Vision cites this paper.

Florence: A New Foundation Model for Computer Vision Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 11

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arxiv_id, observed 2026-05-16T09:38:09.518303Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-16T09:38:09.427509Z digest=sha256:6e57408e0a3523769a286fdf0d0a88c7fae6361843dfae8d34a8701da1745347

Observation 7fd6cab6-82f1-4d96-a6d7-6e0c3bc84eb8 · inbound

Flamingo: a Visual Language Model for Few-Shot Learning cites this paper.

Flamingo: a Visual Language Model for Few-Shot Learning Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 51

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arxiv_id, observed 2026-05-12T04:22:30.583825Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2d8c5e76-6c40-44b1-b0b6-48f810cc2611 · inbound

DetailCLIP: Injecting Image Details into CLIP's Feature Space cites this paper.

DetailCLIP: Injecting Image Details into CLIP's Feature Space Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 9

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arxiv_id, observed 2026-05-24T11:09:22.398768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f0e83b57-fdfe-46bf-9ec6-98f03ef143af · 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 Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 28

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arxiv_id, observed 2026-05-13T14:22:17.247569Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-13T14:22:16.968028Z digest=sha256:8a93a934db3b2001dafa25cd4098e06352dfa2017cdbe04cb0f78cb916acaf6f

Observation 395f5349-5278-4d09-b17d-16c4222c7f42 · inbound

Editing Models with Task Arithmetic cites this paper.

Editing Models with Task Arithmetic Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 42

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arxiv_id, observed 2026-05-13T08:09:13.018298Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7e9cc680-71f9-4ce0-9e53-16054243c38d · inbound

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models cites this paper.

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 7

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arxiv_id, observed 2026-05-12T00:10:49.486795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T00:10:48.610351Z digest=sha256:556a418beac154fba488ffe78a9185d363ec3b6811ca72df6039490103c1fb72

Observation f433eb90-0de5-46e5-b917-1700b2cb27ab · inbound

OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models cites this paper.

OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 10

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arxiv_id, observed 2026-05-17T09:55:35.565340Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-17T09:55:35.452649Z digest=sha256:b88c661c9ace8efa8a583170172bc526ea40d75d479e1a4bcdad552e4cbc1433

Observation f58c1641-f862-48e3-b6c6-3f1f598e086f · inbound

MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost cites this paper.

MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 14

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source=arxiv_source observed=2026-08-12T04:34:52.512550Z digest=sha256:3b20f10dfa20cba49f63877f4462f5f718ef094d5d897042461e5eef5c120933

Observation 6e4539fe-dfb6-4e89-bea0-28536504ee53 · inbound

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension cites this paper.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 20

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source=pdf_text observed=2026-08-11T22:18:01.462379Z digest=sha256:aa08f2ad41d90a297283f8d891e72c1b9abd9c78a20e6a1be29b6096da51340c

Observation 9a703ba8-af43-4ffd-80e8-072317af3141 · inbound

RefSAM3D: Adapting SAM with Cross-modal Reference for 3D Medical Image Segmentation cites this paper.

RefSAM3D: Adapting SAM with Cross-modal Reference for 3D Medical Image Segmentation Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 22

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Observation 1d9c4445-c613-430a-8dc7-8b064178e0b1 · inbound

Foundation Models and Adaptive Feature Selection: A Synergistic Approach to Video Question Answering cites this paper.

Foundation Models and Adaptive Feature Selection: A Synergistic Approach to Video Question Answering Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 15

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Observation 421d0591-c9c0-4f80-bda5-516d35888bb2 · inbound

Does VLM Classification Benefit from LLM Description Semantics? cites this paper.

Does VLM Classification Benefit from LLM Description Semantics? Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 17

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Observation 51ccd206-bab0-4b0f-9913-00968d7d84b7 · inbound

Visualizing the Invisible: A Generative AR System for Intuitive Multi-Modal Sensor Data Presentation cites this paper.

Visualizing the Invisible: A Generative AR System for Intuitive Multi-Modal Sensor Data Presentation Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 2021

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source=pdf_text observed=2026-08-11T13:08:48.345454Z digest=sha256:317812bf31f6682aa10f1942f00a3a3953841e24aaf593645183cef846d5426b

Observation d4e31344-cc47-4f90-869d-a5e383d9a828 · inbound

A Decade of Deep Learning: A Survey on The Magnificent Seven cites this paper.

A Decade of Deep Learning: A Survey on The Magnificent Seven Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 21

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Observation cdcd0b62-1ac9-42fd-beca-718e10dd8200 · inbound

ViPCap: Retrieval Text-Based Visual Prompts for Lightweight Image Captioning cites this paper.

ViPCap: Retrieval Text-Based Visual Prompts for Lightweight Image Captioning Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 15

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Observation 7869bfb3-e5ba-4c1e-9e0a-18871455f695 · inbound

Probing Visual Language Priors in VLMs cites this paper.

Probing Visual Language Priors in VLMs Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 30

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source=arxiv_source observed=2026-08-10T22:55:53.964888Z digest=sha256:6a05a22d7113ae882330c31ea26838c11a522d5d93cd16775979748ae5621810

Observation f46d9fff-300a-4c40-8208-ad430b63b1f4 · inbound

Efficient Domain Adaptation of Multimodal Embeddings using Constrastive Learning cites this paper.

Efficient Domain Adaptation of Multimodal Embeddings using Constrastive Learning Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 9

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Observation 2598b6c4-70af-436b-a084-1e18ef239996 · inbound

Mirai: A Wearable Proactive AI "Inner-Voice" for Contextual Nudging cites this paper.

Mirai: A Wearable Proactive AI "Inner-Voice" for Contextual Nudging Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 21

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Observation c3fd3fae-5c19-434f-930b-fbb8d099ae27 · inbound

Color in Visual-Language Models: CLIP deficiencies cites this paper.

Color in Visual-Language Models: CLIP deficiencies Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 5

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Observation a180953a-5e8a-4335-8ac2-2759aeb5e62c · inbound

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards cites this paper.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 2021

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Observation 5cfe1e3e-0b47-40c5-be01-dc4a7d0c8ca6 · inbound

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models cites this paper.

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 189

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Observation 1e961784-7c43-4a20-a059-1805906fdc6f · inbound

Computer Vision Models Show Human-Like Sensitivity to Geometric and Topological Concepts cites this paper.

Computer Vision Models Show Human-Like Sensitivity to Geometric and Topological Concepts Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 21

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Observation 1ffc0213-69d9-479c-9df5-8ce397816749 · inbound

A Survey on Training-free Open-Vocabulary Semantic Segmentation cites this paper.

A Survey on Training-free Open-Vocabulary Semantic Segmentation Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 26

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Observation f51deee5-ada3-4f9b-867c-8f0d56956134 · inbound

WisWheat: A Three-Tiered Vision-Language Dataset for Wheat Management cites this paper.

WisWheat: A Three-Tiered Vision-Language Dataset for Wheat Management Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 19

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Observation c4c8289e-bd1a-4e81-8b09-344fef440dec · inbound

Visual Pre-Training on Unlabeled Images using Reinforcement Learning cites this paper.

Visual Pre-Training on Unlabeled Images using Reinforcement Learning Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 35

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Observation 02c019f0-7f4e-4b7e-b6b5-d13924477716 · inbound

CF-VLM:CounterFactual Vision-Language Fine-tuning cites this paper.

CF-VLM:CounterFactual Vision-Language Fine-tuning Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 26

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Observation 6b9a24a1-bcfe-45ed-99ca-0c0b7e41e17d · inbound

AME: Aligned Manifold Entropy for Robust Vision-Language Distillation cites this paper.

AME: Aligned Manifold Entropy for Robust Vision-Language Distillation Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 19

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Observation 69f0053e-9912-4700-8fda-4e1262126377 · inbound

PaCo-FR: Patch-Pixel Aligned End-to-End Codebook Learning for Facial Representation Pre-training cites this paper.

PaCo-FR: Patch-Pixel Aligned End-to-End Codebook Learning for Facial Representation Pre-training Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 29

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arxiv_id, observed 2026-05-18T22:56:53.171154Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-18T22:53:23.271423Z digest=sha256:06b593c46ae5cd266e71d574f41a0f669618d1bbf41cc8b873f36d3be6145e4b

Observation 09f374f6-ef52-41bd-ba6e-19edde942969 · inbound

UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion cites this paper.

UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 9

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Observation b07fa155-e0df-4e0b-9d51-b6569f4a917e · inbound

Robust and Label-Efficient Deep Waste Detection cites this paper.

Robust and Label-Efficient Deep Waste Detection Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 18

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Observation 2504c725-81df-4bb4-873e-cf83c4670f93 · inbound

VLMs-in-the-Wild: Bridging the Gap Between Academic Benchmarks and Enterprise Reality cites this paper.

VLMs-in-the-Wild: Bridging the Gap Between Academic Benchmarks and Enterprise Reality Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 2

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Observation 0f60d7bd-3257-4cc5-bc51-5fb93d32a14c · inbound

Rate-Distortion Limits for Multimodal Retrieval: Theory, Optimal Codes, and Finite-Sample Guarantees cites this paper.

Rate-Distortion Limits for Multimodal Retrieval: Theory, Optimal Codes, and Finite-Sample Guarantees Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 23

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no resolver link, observed 2026-08-04T17:18:53.610342Z

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source=pdf_text observed=2026-08-04T17:18:53.610342Z digest=sha256:95fc3b3f7879a94713786cf535113a73b18560203feea0a519739386684caa3d

Observation 8fa62d87-4c65-4139-9306-84d709e30d4f · inbound

The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems cites this paper.

The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 31

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source=arxiv_source observed=2026-08-02T22:58:07.375228Z digest=sha256:f77aa2cee897fbb09425852a4b121f51ecccba4230a12a09d611210b28a03a38

Observation 79e88e60-3b7d-44f2-a561-87a2df459541 · inbound

WikiCLIP: An Efficient Contrastive Baseline for Open-domain Visual Entity Recognition cites this paper.

WikiCLIP: An Efficient Contrastive Baseline for Open-domain Visual Entity Recognition Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 16

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arxiv_id, observed 2026-05-15T13:15:50.553661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-15T13:11:54.384284Z digest=sha256:e7b699ec0422446434559e9a743d22c08e447fb999120b60d5853ae5924886fb

Observation 456e6001-3639-4c05-8ea9-b06b04fc89fe · inbound

WikiCLIP: An Efficient Contrastive Baseline for Open-domain Visual Entity Recognition cites this paper.

WikiCLIP: An Efficient Contrastive Baseline for Open-domain Visual Entity Recognition Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-14T23:55:24.006436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T23:55:24.006436Z digest=sha256:319ad936b61f855e960e6f6876d76c4fde9cfd9cbcd3d74438082fd18249456d

Observation be20fb00-f225-4467-92b9-931a212c9bb9 · inbound

Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks cites this paper.

Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-21T11:10:02.024909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-21T11:09:51.816554Z digest=sha256:105323f530446bf04e492c3530fc26464b990ee13f07b12ff06c0e106b9b9d44

Observation 3d153cec-cc76-4407-83ec-879e1681f651 · inbound

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection cites this paper.

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T20:33:16.707134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-13T20:30:16.163179Z digest=sha256:250c6f21639729c84158ac3beff0b3064421ce7c6f1ca0a6429505939e77cc63

Observation a5243118-073a-4d3d-9ff6-355111f88bfb · inbound

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection cites this paper.

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T21:49:29.323542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-14T21:48:49.892964Z digest=sha256:54b617dba0aaa45bb765c8c709703100a2390505d78871089d29bc3971f32fa3

Observation 2eac7ce6-23f4-4ea8-ba63-a6293d0feb53 · inbound

Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models cites this paper.

Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T06:51:16.216373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T17:25:34.942028Z digest=sha256:9056441964b5990b0a5ac4f97d574fb1205d2abe6f30764cdc56df5b873f19d4

Observation 4e82d205-e315-41a4-97c8-1d0208ad0f87 · inbound

Compared to What? Baselines and Metrics for Counterfactual Prompting cites this paper.

Compared to What? Baselines and Metrics for Counterfactual Prompting Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 93

Resolution
verified exact
arxiv_id, observed 2026-05-09T19:05:10.548305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-09T19:02:46.991897Z digest=sha256:afba034ccd34d930e10c87f067b8ea8632d85ed6a39dca99a9f4828f2519656f

Observation ef87c4ca-e90d-4d07-a1d1-47f52356d4dc · inbound

Vision Harnessing Agent for Open Ad-hoc Segmentation cites this paper.

Vision Harnessing Agent for Open Ad-hoc Segmentation Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-20T05:53:04.439800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-20T05:52:40.429412Z digest=sha256:2532ff176795ac45cf9209b0a6a4a992a5be643581f10f50ee46b297406f4a26

Observation 44908e21-1cef-439e-b18d-57458df842c3 · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 266

Resolution
verified exact
arxiv_id, observed 2026-06-28T07:11:45.290744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-28T07:05:18.026601Z digest=sha256:e1695f7056bb30a1970e5ef5d1ab303b0dbd7dcef3a715fb21ea2811adf166e4

Observation 11c0e04f-f341-4fa2-9ced-cdeb5eab031b · inbound

Modeling Complex Behaviors: Multi-Personality Composition and Dynamic Switching in Vision-Language Models cites this paper.

Modeling Complex Behaviors: Multi-Personality Composition and Dynamic Switching in Vision-Language Models Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 74

Resolution
verified exact
arxiv_id, observed 2026-07-03T05:47:41.829444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-27T13:04:14.886733Z digest=sha256:1616bc775088f0c11917f253c191419a49825181d0e86a216b4e08d3c946cd4f

Observation 887c66e1-1378-4117-a8ea-35b4aad639d3 · inbound

Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation cites this paper.

Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 140

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T17:18:43.932557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-27T04:19:26.332718Z digest=sha256:c716062ab4502504bd79c26021117f1aca82d1a1a6460d54dba425dc77bda3d1

Observation daa1c166-07ec-40c9-b3f6-4c193ffb0d88 · inbound

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning cites this paper.

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T14:48:32.368383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-03T14:47:35.377391Z digest=sha256:44ec6c006831b74e9ddcdca87f14d68f08577b4991f7f9166ddbc494dcba997c

Observation 2a4df5d4-58ff-4181-a3bd-baefb693cf78 · inbound

Qwen-Audio-VAE Technical Report cites this paper.

Qwen-Audio-VAE Technical Report Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 155

Resolution
unresolved
no resolver link, observed 2026-07-14T03:31:19.309532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T03:31:19.309532Z digest=sha256:42be05d0ad6c28f5115fe24488376832a5871c0dc25a924271bbda3db447f8ee

Observation d4b3338b-8b46-4a9c-a9ae-6a354c1cdbcc · inbound

Theia: Large-Scale Multimodal Captioning and Automated Validation of the Incidents1M Dataset for Data-Free Distillation cites this paper.

Theia: Large-Scale Multimodal Captioning and Automated Validation of the Incidents1M Dataset for Data-Free Distillation Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-31T12:44:13.340533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T12:44:13.340533Z digest=sha256:a50a9fd623fd5baf46d359f98d9ae9fe177d8894da4a8203b31a1e1c999fb520

Observation a91ac6c3-9552-4fed-ae18-c46aa3d840f3 · inbound

Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression cites this paper.

Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T15:05:38.990379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:05:38.990379Z digest=sha256:9d8a37580e112b3ce53c5ba12922b1ccae67fd77173176fdd07f003a4000d9d9

Observation e59a47cb-8137-4931-a00c-1b059f3e6e87 · inbound

MASCOT: Model-Aware Submodular Coverage for Composite-Attribute Text-to-Image Retrieval cites this paper.

MASCOT: Model-Aware Submodular Coverage for Composite-Attribute Text-to-Image Retrieval Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-16T00:12:08.581177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:12:08.581177Z digest=sha256:176c5e1847f0adf7e68c251ac844d591f7755b5ff21bc06e04e46af7610a2924