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Paper Citation Record · LEDGER

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2606.22220.

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

pith.paper-citation-record.v1
2606.22220 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T11:59:16.070464Z

measured 40 of 40 standing notices

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

40 of 40 outbound references displayed

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  • verified fuzzy0
  • unresolved34
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  • malformed identifier1
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 874b6b50-1645-4cff-adb7-24d55a34dfbb · outbound

This paper cites Conditioned and composed image retrieval combining and partially fine-tuning clip-based features.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Conditioned and composed image retrieval combining and partially fine-tuning clip-based features

Reference 1

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Observation 28d82fbb-844c-47af-924a-96cea6bf77fa · outbound

This paper cites Effective conditioned and composed image retrieval combining clip-based features.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Effective conditioned and composed image retrieval combining clip-based features

Reference 2

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Observation c5903131-7380-4944-b8a9-5d8ea0d7a1bb · outbound

This paper cites Benign overfitting in linear regression.Proceedings 10 of the National Academy of Sciences, 117(48):30063–30070,.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Benign overfitting in linear regression.Proceedings 10 of the National Academy of Sciences, 117(48):30063–30070,

Reference 3

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Observation e71d02e3-1686-4a7a-82f4-ed1f2f40d05b · outbound

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

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Reproducible scal- ing laws for contrastive language-image learning

Reference 4

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Observation 9417d13d-61d2-4269-ab66-d0638c85f260 · outbound

This paper cites Does learning require memorization? a short tale about a long tail.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Does learning require memorization? a short tale about a long tail

Reference 5

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Observation be88dc48-8d5e-4b5b-abe3-c8af4700f32d · outbound

This paper cites What neural networks memorize and why: Discovering the long tail via influence estimation.Advances in Neural Information Processing Sys- tems, 33:2881–2891, 2020.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning What neural networks memorize and why: Discovering the long tail via influence estimation.Advances in Neural Information Processing Sys- tems, 33:2881–2891, 2020

Reference 6

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Observation 14e7b2ff-a5a2-4121-8b54-ac47d09ac97b · outbound

This paper cites Gemmeke, Daniel P.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Gemmeke, Daniel P

Reference 7

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Observation 09e16746-d3db-4076-a2dc-fb8ab86b7d26 · outbound

This paper cites Imagebind: One embedding space to bind them all.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Imagebind: One embedding space to bind them all

Reference 8

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Observation 635d6537-315e-46c5-9b1d-99fb4abb6aee · outbound

This paper cites Esresnet: Environmental sound classification based on visual domain models.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Esresnet: Environmental sound classification based on visual domain models

Reference 9

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Observation c6febc83-b741-46af-b8d5-040bcf6e6975 · outbound

This paper cites Audioclip: Extending clip to image, text and audio.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Audioclip: Extending clip to image, text and audio

Reference 10

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Observation 17a684f9-e4d6-43f9-a193-f3c7a8820521 · outbound

This paper cites Scaling up vision- language pre-training for image captioning.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Scaling up vision- language pre-training for image captioning

Reference 11

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Observation 7c4869c0-f274-483e-84da-d6c263366f29 · outbound

This paper cites D´ej`a vu memorization in vision-language models.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning D´ej`a vu memorization in vision-language models

Reference 12

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Observation d93bae27-ca79-4e28-aa55-b877af9098b0 · outbound

This paper cites Multimodal alignment and fusion: A survey.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Multimodal alignment and fusion: A survey

Reference 13

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Observation c926ab74-5025-4bac-a7a9-5e50a72d1538 · outbound

This paper cites Foundations & trends in multimodal machine learning: Prin- ciples, challenges, and open questions.ACM Computing Surveys, 56(10):1–42, 2024.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Foundations & trends in multimodal machine learning: Prin- ciples, challenges, and open questions.ACM Computing Surveys, 56(10):1–42, 2024

Reference 14

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Observation b4041d6b-1259-48ef-a0e9-43a1c1e819dd · outbound

This paper cites Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning.Advances in Neural Information Processing Systems, 35:17612–17625, 2022.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning.Advances in Neural Information Processing Systems, 35:17612–17625, 2022

Reference 15

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Observation 1e5f1510-ac2e-4fb9-b3df-1a4b11e8f402 · outbound

This paper cites Microsoft coco: Common objects in context.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Microsoft coco: Common objects in context

Reference 16

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Observation 2c6ade06-9ccd-4000-aaa6-b5c000e5c58b · outbound

This paper cites CPTR: Full Transformer Network for Image Captioning.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning CPTR: Full Transformer Network for Image Captioning

Reference 17

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Observation aa0114ae-3690-4c30-8d34-2f0bdd8759d9 · outbound

This paper cites Do ssl models have d ´ej`a vu? a case of unintended memorization in self-supervised learn- ing.Advances in Neural Information Processing Systems, 36: 42775–42798, 2023.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Do ssl models have d ´ej`a vu? a case of unintended memorization in self-supervised learn- ing.Advances in Neural Information Processing Systems, 36: 42775–42798, 2023

Reference 18

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Observation 790a0bf2-c87d-48e5-a726-fd77a2251081 · outbound

This paper cites Slip: Self-supervision meets language-image pre- training.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Slip: Self-supervision meets language-image pre- training

Reference 19

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Observation d51b3e88-52f9-465e-9fcb-a82cfe33cd3f · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Representation Learning with Contrastive Predictive Coding

Reference 20

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Observation 2cd21d26-2892-4ca0-8d7e-9e971fe62d0d · outbound

This paper cites Balanced multimodal learning via on-the-fly gradient modulation.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Balanced multimodal learning via on-the-fly gradient modulation

Reference 21

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Observation 78dadd8d-dec6-4f9c-92af-85369bfef5d9 · outbound

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

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Learning transferable visual models from natural language supervi- sion

Reference 22

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Observation 3c6131d2-2d78-4928-b28c-11ebaf47565e · outbound

This paper cites On the Memorization Properties of Contrastive Learning.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning On the Memorization Properties of Contrastive Learning

Reference 23

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Observation dee7eae6-ee50-409a-863d-af484dc416e4 · outbound

This paper cites A dataset and taxonomy for urban sound research.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning A dataset and taxonomy for urban sound research

Reference 24

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Observation 1f488f27-cc71-4bcf-803e-29cd776ba466 · outbound

This paper cites Clip models are few-shot learners: Empirical studies on vqa and visual entailment.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Clip models are few-shot learners: Empirical studies on vqa and visual entailment

Reference 25

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Observation 58de9197-fdca-435a-9de3-08da3a9cdedb · outbound

This paper cites Localizing memorization in ssl vision encoders.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Localizing memorization in ssl vision encoders

Reference 26

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Observation e9577389-ceaa-40fa-9765-3b531c31e1c4 · outbound

This paper cites Memorization in self-supervised learning improves down- stream generalization.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Memorization in self-supervised learning improves down- stream generalization

Reference 27

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Observation c571462b-ce2d-45b0-ad6d-99356d36969a · outbound

This paper cites Captured by captions: On memorization and its mitigation in clip models.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Captured by captions: On memorization and its mitigation in clip models

Reference 28

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Observation c6238950-4091-4ea6-a5c1-0a94bedb95a5 · outbound

This paper cites an unresolved cited work.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Unresolved cited work

Reference 29

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Observation 8528b358-36c1-46c8-88f0-e1d067969f5c · outbound

This paper cites Vqa-gnn: Reasoning with multi- modal knowledge via graph neural networks for visual ques- tion answering.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Vqa-gnn: Reasoning with multi- modal knowledge via graph neural networks for visual ques- tion answering

Reference 30

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Observation 7d7b8307-b741-4b66-93ad-e44bc7176811 · outbound

This paper cites Cookie: Contrastive cross-modal knowledge sharing pre-training for vision-language representation.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Cookie: Contrastive cross-modal knowledge sharing pre-training for vision-language representation

Reference 31

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Observation 87d7da45-f321-4942-9622-12e4527aea8d · outbound

This paper cites Videoclip: Contrastive pre-training for zero-shot video-text understanding.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Videoclip: Contrastive pre-training for zero-shot video-text understanding

Reference 32

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Observation 502a4642-e33a-436d-bdd1-87b0606f130a · outbound

This paper cites Msr-vtt: A large video description dataset for bridging video and language.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Msr-vtt: A large video description dataset for bridging video and language

Reference 33

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Observation 8ede04b4-ed7d-4ba2-b8b8-8375487ba005 · outbound

This paper cites Zero-shot video question answering via frozen bidirectional language models.Advances in Neural Information Processing Systems, 35:124–141, 2022.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Zero-shot video question answering via frozen bidirectional language models.Advances in Neural Information Processing Systems, 35:124–141, 2022

Reference 34

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Observation 187e9b80-c9f7-40af-a1ab-ad8e13f09ad9 · outbound

This paper cites Leave-one-out distinguishability in machine learn- ing.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Leave-one-out distinguishability in machine learn- ing

Reference 35

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Observation 890bd88e-d0bc-4fa4-bf17-f292917e0409 · outbound

This paper cites Openvna: A framework for analyzing the behavior of multimodal language understanding system under noisy scenarios.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Openvna: A framework for analyzing the behavior of multimodal language understanding system under noisy scenarios

Reference 36

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source=pdf_text observed=2026-06-26T11:59:16.070464Z digest=sha256:23294a9eb000d38c55e2b54753530363ae0a62de256a121807856fdf7acec2de

Observation 5f35cc77-8066-469c-8007-eeada1a5deca · outbound

This paper cites Tip- adapter: Training-free adaption of clip for few-shot classifi- cation.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Tip- adapter: Training-free adaption of clip for few-shot classifi- cation

Reference 37

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source=pdf_text observed=2026-06-26T11:59:16.070464Z digest=sha256:9572f9f21491123799b5ba255396b324b50ffc1d8df3ce2e726f3b6a249a5f63

Observation 9762a055-aced-4980-93b3-76ada2130595 · outbound

This paper cites Style-aware contrastive learning for multi-style image captioning.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning Style-aware contrastive learning for multi-style image captioning

Reference 38

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Observation 9a693ef4-7fc0-4e9c-b68b-699fd3d57e35 · outbound

This paper cites The results are shown in Figure 7, which aligns with the results for AudioCLIP in the main paper.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning The results are shown in Figure 7, which aligns with the results for AudioCLIP in the main paper

Reference 39

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source=pdf_text observed=2026-06-26T11:59:16.070464Z digest=sha256:cc003c417658a4f892bdb39f1ec0dd053f42c5c867fcbbb1a8c153035860144d

Observation 72dd861f-4365-4776-825e-f8130e959989 · outbound

This paper cites a man talking about hydroponic fluid pres- sure.

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning a man talking about hydroponic fluid pres- sure

Reference 40

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source=pdf_text observed=2026-06-26T11:59:16.070464Z digest=sha256:4b8c790b30e01e5dd8a16087905722c6c5416dcb8a7629b5d4f1015af3035297

Pith citing papers

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