Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning | Paper Citation Record

Observation 88fcee8e-b536-4f23-83ed-61fc586f5465 · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Learning transferable visual models from natural language supervision

Reference 1

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Observation 1a2feed3-2c2a-48c5-aad5-5a56d1975b13 · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Scaling up visual and vision-language representation learning with noisy text supervision

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:28.050920Z

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Observation d31fb068-aa02-483f-8c6c-6df90c3e9834 · outbound

This paper cites BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation, 2022.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation, 2022

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:27.897788Z

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Observation 6cc936eb-e062-43a3-bdb6-1c687a1a83cb · outbound

This paper cites Visual instruction tuning.Advances in Neural Information Processing Systems (NeurIPS), 36:34892–34916, 2023.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Visual instruction tuning.Advances in Neural Information Processing Systems (NeurIPS), 36:34892–34916, 2023

Reference 4

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Observation c6f33397-522f-42cd-8094-c5cfab1360d3 · outbound

This paper cites Clap learning audio concepts from natural language supervision.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Clap learning audio concepts from natural language supervision

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:27.514038Z

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Observation 5c4c8073-19af-4a27-b687-cff42eba5f52 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 6

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Observation 9b56f72f-eea8-4795-abaf-b5d88fc79a24 · outbound

This paper cites Palm-e: An embodied multimodal language model.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Palm-e: An embodied multimodal language model

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:27.334741Z

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Observation 7dc6fdd1-c18e-4b37-8101-5201b6a14cb4 · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning OpenVLA: An Open-Source Vision-Language-Action Model

Reference 8

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Observation f98bee01-7044-4b51-9a05-ba13b9253fdc · outbound

This paper cites an unresolved cited work.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Unresolved cited work

Reference 9

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Observation bb525eaa-311a-4eef-aec7-f4475c1724a4 · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:06.169961Z

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Observation dff39a45-fe4b-4fa8-8198-90a08189ac11 · outbound

This paper cites Berg, and Li Fei-Fei.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Berg, and Li Fei-Fei

Reference 11

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Observation 142a3491-806f-4dc7-a033-8f7a8a3a199e · outbound

This paper cites Read, watch and scream! sound generation from text and video.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Read, watch and scream! sound generation from text and video

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:26.588612Z

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Observation b8ae5879-52e0-4302-b0dd-7353b7da03df · outbound

This paper cites Are we done with ImageNet?.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Are we done with ImageNet?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:06.500633Z

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Observation 2e4d0c3a-e70b-4d10-bbfc-6b85c3195bad · outbound

This paper cites Evaluating machine accuracy on imagenet.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Evaluating machine accuracy on imagenet

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:26.404136Z

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Observation 0fff740e-d227-4abd-9ad4-e4e989bed8cf · outbound

This paper cites Re- labeling imagenet: from single to multi-labels, from global to localized labels.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Re- labeling imagenet: from single to multi-labels, from global to localized labels

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:26.223810Z

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Observation 9652c807-8017-4912-8362-afd002cc5401 · outbound

This paper cites Models, reasoning and inference.Cambridge, UK: CambridgeUniversityPress, 19(2):3,.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Models, reasoning and inference.Cambridge, UK: CambridgeUniversityPress, 19(2):3,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:26.092597Z

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Observation b0d93ccc-3424-4853-ab96-60a1082ac02b · outbound

This paper cites Microsoft COCO: Common objects in context.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Microsoft COCO: Common objects in context

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:25.948923Z

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Observation 7139b64b-5da4-44b6-b221-4861050926a7 · outbound

This paper cites Probabilistic embeddings for cross-modal retrieval.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Probabilistic embeddings for cross-modal retrieval

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:25.776407Z

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Observation 4a85e4c9-76e1-4166-9392-0df686d5e03b · outbound

This paper cites Oxford university press, 1990.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Oxford university press, 1990

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:25.561562Z

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Observation cfe9893d-95d1-4852-964f-04aa0824699b · outbound

This paper cites Connecting vision and language with localized narratives.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Connecting vision and language with localized narratives

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:25.415556Z

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Observation 29c3743b-6a58-4133-be19-750a60e8020f · outbound

This paper cites Visualcomet: Reasoning about the dynamic context of a still image.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Visualcomet: Reasoning about the dynamic context of a still image

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:25.238817Z

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Observation fe3fb05f-9d79-4172-968a-ec84917c188e · outbound

This paper cites Vggsound: A large-scale audio-visual dataset.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Vggsound: A large-scale audio-visual dataset

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:24.983610Z

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Observation fe62f28c-1a6c-4369-a2c3-898356804cdd · outbound

This paper cites VoxCeleb: a large-scale speaker identification dataset.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning VoxCeleb: a large-scale speaker identification dataset

Reference 23

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Observation 2f726f4f-0836-4d02-8c76-76efbc048ecf · outbound

This paper cites Visually indicated sounds.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Visually indicated sounds

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:24.667638Z

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Observation e8ede0a3-0f9a-4702-9f96-9313e1eefa83 · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:24.331459Z

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Observation ec61533e-39b9-41f8-ab92-dc5113647f6d · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Vilt: Vision-and-language transformer without convolution or region supervision

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:24.049480Z

Source-reported events for the cited work

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Observation 0b80c615-85be-452a-8e20-6740b123a55c · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Sigmoid loss for language image pre-training

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:23.801664Z

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Observation b3d608b0-59b5-4866-8b7f-7cddee563ae0 · outbound

This paper cites Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:23.496510Z

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Observation 2f78cc14-814a-4a25-b081-bc4cbb78fd77 · outbound

This paper cites RedCaps: Web-curated image-text data created by the people, for the people.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning RedCaps: Web-curated image-text data created by the people, for the people

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:23.210366Z

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Observation 937ad39b-8511-42b5-ac2d-ed3afa494e1a · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 30

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Observation 9111481b-70bb-45ee-9e46-a7fefb0adf85 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in Neural Information Processing Systems (NeurIPS), 35:25278–25294, 2022.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in Neural Information Processing Systems (NeurIPS), 35:25278–25294, 2022

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:22.890150Z

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Observation bf47952b-83a7-4ee4-b559-7f76b20181d5 · outbound

This paper cites Datacomp: In search of the next generation of multimodal datasets.Advances in Neural Information Processing Systems (NeurIPS), 36,.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Datacomp: In search of the next generation of multimodal datasets.Advances in Neural Information Processing Systems (NeurIPS), 36,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:22.628648Z

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Observation dd90efe1-357c-4267-a0ee-cc6d119c435f · outbound

This paper cites VSE++: Improving visual-semantic embeddings with hard negatives.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning VSE++: Improving visual-semantic embeddings with hard negatives

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:22.345250Z

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Observation 7e0c6622-3003-4019-92a1-741253ba847b · outbound

This paper cites Learning the best pooling strategy for visual semantic embedding.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Learning the best pooling strategy for visual semantic embedding

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:22.200546Z

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Observation 115bcd22-c773-4c82-99da-0461a4ef534e · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning.Advances in Neural Information Processing Systems (NeurIPS), 35:17612–17625, 2022

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:21.974675Z

Source-reported events for the cited work

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Observation d0a88a38-2277-43d7-a0a5-1935022173e7 · outbound

This paper cites Boosting contrastive self-supervised learning with false negative cancellation.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Boosting contrastive self-supervised learning with false negative cancellation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:21.751468Z

Source-reported events for the cited work

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Observation f5a38849-a44d-4dd0-ac94-a2ba19fdad94 · outbound

This paper cites Mafa: Managing false negatives for vision-language pre-training.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Mafa: Managing false negatives for vision-language pre-training

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:21.466329Z

Source-reported events for the cited work

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Observation 72991341-5e02-4cdf-a121-5a421aa04c61 · outbound

This paper cites Supervision exists everywhere: A data efficient contrastive language-image pre-training paradigm.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Supervision exists everywhere: A data efficient contrastive language-image pre-training paradigm

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:21.286635Z

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Observation a9ab1f8c-4fbc-41ec-9e19-8a5ad39b8410 · outbound

This paper cites Improved probabilistic image-text representations.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Improved probabilistic image-text representations

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:21.060033Z

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Observation 0a986dc8-3c61-44ad-982b-6e5fa6297429 · outbound

This paper cites mixup: Beyond empirical risk minimization.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning mixup: Beyond empirical risk minimization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:20.859342Z

Source-reported events for the cited work

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Observation fbf3a614-dc65-4cf2-a544-6ae6407c82ac · outbound

This paper cites CutMix: Regularization strategy to train strong classifiers with localizable features.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning CutMix: Regularization strategy to train strong classifiers with localizable features

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:20.664206Z

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Observation 79beb560-2e5e-4200-a7c6-de599eb6a595 · outbound

This paper cites Learning with noisy correspondence for cross-modal matching.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Learning with noisy correspondence for cross-modal matching

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:20.473658Z

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 2151e1d7-8984-4e74-8063-81f39327de5e · outbound

This paper cites Learning from noisy labels with deep neural networks: A survey.IEEE transactions on neural networks and learning systems, 34(11):8135–8153, 2022.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Learning from noisy labels with deep neural networks: A survey.IEEE transactions on neural networks and learning systems, 34(11):8135–8153, 2022

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:20.252868Z

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Observation 86c4ac82-01ab-4dbf-9a7d-6d8be4e8a92f · outbound

This paper cites Learning from positive and unlabeled data: A survey.Machine Learning, 109(4):719–760, 2020.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Learning from positive and unlabeled data: A survey.Machine Learning, 109(4):719–760, 2020

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:20.059181Z

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 9aea5a1a-eeb8-4aaa-9c98-68305bb7741e · outbound

This paper cites Polysemous visual-semantic embedding for cross-modal retrieval.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Polysemous visual-semantic embedding for cross-modal retrieval

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:19.844161Z

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 b1512ce2-d6b2-4d52-86e1-04247c610a34 · outbound

This paper cites Improving cross-modal retrieval with set of diverse embeddings.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Improving cross-modal retrieval with set of diverse embeddings

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:19.667256Z

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 d4ae136b-7ad8-48e5-a63b-d41067ff60a9 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:09.462903Z

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Observation cfc0da8c-fb56-46d1-9058-d3d0baaa0108 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:09.536726Z

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Observation 0160d01b-cc0a-48ef-80eb-cb5f4677f591 · outbound

This paper cites Probvlm: Proba- bilistic adapter for frozen vison-language models.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Probvlm: Proba- bilistic adapter for frozen vison-language models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:19.533611Z

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 930f59d4-a35e-4388-9a72-397b8a0b5b4f · outbound

This paper cites Prototype-based aleatoric uncertainty quantification for cross-modal retrieval.Advances in Neural Information Processing Systems (NeurIPS), 36:24564–24585, 2023.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Prototype-based aleatoric uncertainty quantification for cross-modal retrieval.Advances in Neural Information Processing Systems (NeurIPS), 36:24564–24585, 2023

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:19.301851Z

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

Observation 3e149e25-a357-4f1b-9df8-7c57d2adcdc5 · outbound

This paper cites Post-hoc probabilistic vision-language models.arXiv preprint arXiv:2412.06014, 2024.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Post-hoc probabilistic vision-language models.arXiv preprint arXiv:2412.06014, 2024

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:09.747225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b94099c9-1a2a-4588-93b1-d6f314d53663 · outbound

This paper cites Probabilistic language-image pre-training.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Probabilistic language-image pre-training

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:19.077995Z

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 3a7c1829-a0bd-4cd4-981c-b9f94ef1548c · outbound

This paper cites LongProLIP: A probabilistic vision-language model with long context text.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning LongProLIP: A probabilistic vision-language model with long context text

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:18.899901Z

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 f130cd30-0d9b-417e-a315-b0d5d9f36064 · outbound

This paper cites Seeing what you say: Expressive image generation from speech.Under review, 2025.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Seeing what you say: Expressive image generation from speech.Under review, 2025

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:18.723468Z

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 aab51bfb-cf2e-4660-bb27-e1e0b7e248f5 · outbound

This paper cites Flaws of imagenet, com- puter vision’s favorite dataset.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Flaws of imagenet, com- puter vision’s favorite dataset

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:18.549313Z

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 a1611fd9-3d99-4cf0-af30-bcecd8896d65 · outbound

This paper cites ECCV Caption: Correcting false negatives by collecting machine-and-human-verified image-caption associations for MS-COCO.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning ECCV Caption: Correcting false negatives by collecting machine-and-human-verified image-caption associations for MS-COCO

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:18.353786Z

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 21230f8e-0a9e-440c-ad8f-371df56e56e5 · outbound

This paper cites A metric learning reality check.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning A metric learning reality check

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:18.177846Z

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 aec1ba88-db07-472e-b3dc-2d2a662d2d8f · outbound

This paper cites Holistic evaluation of text-to-image models.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Holistic evaluation of text-to-image models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:17.972297Z

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 139dfd9e-ff68-4140-b77f-e3d614e57d84 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in Neural Information Processing Systems (NeurIPS), 30, 2017.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in Neural Information Processing Systems (NeurIPS), 30, 2017

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:17.717520Z

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 a6b36c31-f7bc-4be1-9e88-dcd69c13a0d8 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Bleu: a method for automatic evaluation of machine translation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:17.518665Z

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 6e859e9c-831e-4ccb-b2a7-0fb689c8239a · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Rouge: A package for automatic evaluation of summaries

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:10.445461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f19c540-9c5e-4908-857e-fd6e2f38542c · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with human judgments.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Meteor: An automatic metric for mt evaluation with improved correlation with human judgments

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:17.327520Z

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 084c31fe-2b0c-492d-b952-a66bc4e0f290 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning The unreasonable effectiveness of deep features as a perceptual metric

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:17.171214Z

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 e0ea2121-3621-4b41-9bb0-e9bdce7a2395 · outbound

This paper cites Rank analysis of incomplete block designs: I.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Rank analysis of incomplete block designs: I

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:16.945964Z

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 7f28daa8-e56b-4409-8b05-c120f18f9220 · outbound

This paper cites The Caltech-UCSD Birds-200-2011 Dataset.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning The Caltech-UCSD Birds-200-2011 Dataset

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:16.724783Z

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 1dfcf618-c394-44b3-9c31-dba4c45a9c59 · outbound

This paper cites On semantic similarity in video retrieval.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning On semantic similarity in video retrieval

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:16.447933Z

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 9d49a3ce-90dd-43b9-8e1c-bf4e6a153432 · outbound

This paper cites Crisscrossed captions: Extended intramodal and intermodal semantic similarity judgments for MS-COCO.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Crisscrossed captions: Extended intramodal and intermodal semantic similarity judgments for MS-COCO

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:16.109279Z

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 8dc0f6f4-9bac-471e-b39e-ba384511d26f · outbound

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

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Reproducible scaling laws for contrastive language-image learning

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:15.833602Z

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 73e8ebde-88fb-464c-9d2b-aef37f4a43a1 · outbound

This paper cites T-mars: Improving visual representations by circumventing text feature learning.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning T-mars: Improving visual representations by circumventing text feature learning

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:15.603277Z

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 9e67b893-2440-4618-9dd5-b1d381a2ab94 · outbound

This paper cites Data filtering networks.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Data filtering networks

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:15.312960Z

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 0fcd36cb-bf55-4e59-9dc4-9adbcde8eab7 · outbound

This paper cites Text-only training for image captioning using noise- injected clip.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Text-only training for image captioning using noise- injected clip

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:15.052907Z

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 28f0f437-fada-4eb0-a288-e6d5acb6a66e · outbound

This paper cites I can’t believe there’s no images! learning visual tasks using only language supervision.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning I can’t believe there’s no images! learning visual tasks using only language supervision

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:14.791979Z

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 0f01aa81-1d49-455d-ab01-900f8926ee97 · outbound

This paper cites Decap: Decoding clip latents for zero-shot captioning via text-only training.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Decap: Decoding clip latents for zero-shot captioning via text-only training

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:14.504866Z

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 b45afb86-ea2f-48b9-867d-829e06dd8dd2 · outbound

This paper cites Language-only efficient training of zero-shot composed image retrieval.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Language-only efficient training of zero-shot composed image retrieval

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:14.237872Z

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 312dc320-60fe-457b-8e96-7256b5cfb945 · outbound

This paper cites The Devil is in the Details: A Deep Dive into the Rabbit Hole of Data Filtering.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning The Devil is in the Details: A Deep Dive into the Rabbit Hole of Data Filtering

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:11.606628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ecaad2b-9a75-4fa0-9f55-103d82bdab4b · outbound

This paper cites Icons: Influence consensus for vision-language data selection.arXiv preprint arXiv:2501.00654, 2024.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Icons: Influence consensus for vision-language data selection.arXiv preprint arXiv:2501.00654, 2024

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:11.706817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 541a3817-2404-4547-a1fa-85460bdb1ed8 · outbound

This paper cites HYPE: Hyperbolic entailment filtering for underspecified images and texts.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning HYPE: Hyperbolic entailment filtering for underspecified images and texts

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:14.068636Z

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 90c3b615-9367-4153-990d-e42b3283cb62 · outbound

This paper cites CompoDiff: Versatile composed image retrieval with latent diffusion.Transactions on Machine Learning Research (TMLR), 2024.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning CompoDiff: Versatile composed image retrieval with latent diffusion.Transactions on Machine Learning Research (TMLR), 2024

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:13.920023Z

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 5b275adf-e4f9-41c6-9e98-b2c9742cd007 · outbound

This paper cites Toward interactive regional understanding in vision- large language models.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Toward interactive regional understanding in vision- large language models

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:13.737946Z

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 17b406e2-2a86-4fc4-9ac5-03dd33e32755 · outbound

This paper cites Crepe: Can vision-language foundation models reason compositionally? InIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10910–10921, 2023.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Crepe: Can vision-language foundation models reason compositionally? InIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10910–10921, 2023

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:13.572416Z

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 1a411e0c-72d0-41a3-b175-3ab5af0fc8ef · outbound

This paper cites Large-scale interactive object segmentation with human annotators.

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning Large-scale interactive object segmentation with human annotators

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:13.369741Z

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.

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