Disentanglement-Based Equivariant Learning for Compositional VQA | Paper Citation Record

Observation 9f695afd-c87c-47b1-9790-c4df90d71020 · outbound

This paper cites Vqa: Visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Vqa: Visual question answering,

Reference 1

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Observation 4457f8f5-fbf4-4ffa-9dba-0e57cc100178 · outbound

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

Disentanglement-Based Equivariant Learning for Compositional VQA Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 2

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Observation 3c1bc5aa-0459-450a-8f87-2c13003ec651 · outbound

This paper cites Image as a foreign language: Beit pretraining for vision and vision-language tasks,.

Disentanglement-Based Equivariant Learning for Compositional VQA Image as a foreign language: Beit pretraining for vision and vision-language tasks,

Reference 3

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Observation c1ee886b-4cb1-456b-a3a8-0f302ee759f9 · outbound

This paper cites Connectionism and cognitive archi- tecture: A critical analysis,.

Disentanglement-Based Equivariant Learning for Compositional VQA Connectionism and cognitive archi- tecture: A critical analysis,

Reference 4

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Observation 65222092-fd15-40b3-b9b4-9701a8da8b92 · outbound

This paper cites Systematic Generalization: What Is Required and Can It Be Learned?.

Disentanglement-Based Equivariant Learning for Compositional VQA Systematic Generalization: What Is Required and Can It Be Learned?

Reference 5

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Observation 0b607505-1732-4b83-8733-8c91f2a66987 · outbound

This paper cites CLOSURE: Assessing Systematic Generalization of CLEVR Models.

Disentanglement-Based Equivariant Learning for Compositional VQA CLOSURE: Assessing Systematic Generalization of CLEVR Models

Reference 6

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Observation b87c9b17-dd30-4251-9545-19d00601e586 · outbound

This paper cites A benchmark for systematic generalization in grounded language under- standing,.

Disentanglement-Based Equivariant Learning for Compositional VQA A benchmark for systematic generalization in grounded language under- standing,

Reference 7

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Observation fba93d66-587b-4ac7-8b74-f3c11a71e192 · outbound

This paper cites How modular should neural module networks be for systematic generalization?.

Disentanglement-Based Equivariant Learning for Compositional VQA How modular should neural module networks be for systematic generalization?

Reference 8

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Observation 1c7b0d6e-87c1-44d3-bb8d-6be96d409160 · outbound

This paper cites Meta module network for compositional visual reasoning,.

Disentanglement-Based Equivariant Learning for Compositional VQA Meta module network for compositional visual reasoning,

Reference 9

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Observation 6e449ac8-373b-4afc-9fa4-e73261789a87 · outbound

This paper cites Transformer module networks for systematic generalization in visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Transformer module networks for systematic generalization in visual question answering,

Reference 10

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Observation 1f084baa-277c-4598-b2a3-30da671d3a4c · outbound

This paper cites Detection-based intermediate supervision for visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Detection-based intermediate supervision for visual question answering,

Reference 11

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Observation 0c74a796-66f4-498b-ac7a-6f43f7c3d3ac · outbound

This paper cites Neural module networks,.

Disentanglement-Based Equivariant Learning for Compositional VQA Neural module networks,

Reference 12

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Observation f0bc193f-b735-4ab7-90fd-2ebbef8c892d · outbound

This paper cites Linguistically routing capsule network for out-of-distribution visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Linguistically routing capsule network for out-of-distribution visual question answering,

Reference 13

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Observation c5b9e607-d1ae-4257-a2bd-0af933afc54f · outbound

This paper cites Neural- symbolic vqa: Disentangling reasoning from vision and language under- standing,.

Disentanglement-Based Equivariant Learning for Compositional VQA Neural- symbolic vqa: Disentangling reasoning from vision and language under- standing,

Reference 14

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Observation 01199c1f-7d17-4ae4-b218-63bd8eb946f5 · outbound

This paper cites Multimodal graph networks for composi- tional generalization in visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Multimodal graph networks for composi- tional generalization in visual question answering,

Reference 15

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Observation c76e7700-179c-495c-8ed8-f954ff50c167 · outbound

This paper cites Compositional generalization in neuro- symbolic visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Compositional generalization in neuro- symbolic visual question answering,

Reference 16

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Observation e8765eb5-b42d-491a-9752-cb6f5dfccc1c · outbound

This paper cites Mdetr-modulated detection for end-to-end multi-modal understanding,.

Disentanglement-Based Equivariant Learning for Compositional VQA Mdetr-modulated detection for end-to-end multi-modal understanding,

Reference 17

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Observation e75fec6e-a4a2-425b-bcfe-8bf105aa7729 · outbound

This paper cites Exploring the effect of primitives for compositional generalization in vision-and-language,.

Disentanglement-Based Equivariant Learning for Compositional VQA Exploring the effect of primitives for compositional generalization in vision-and-language,

Reference 18

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Observation ebd91367-320c-487d-a84d-184ccc174617 · outbound

This paper cites Towards a Definition of Disentangled Representations.

Disentanglement-Based Equivariant Learning for Compositional VQA Towards a Definition of Disentangled Representations

Reference 19

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Observation b7b3ef2f-a364-4b1b-bfd4-67041aa338ff · outbound

This paper cites Causal inference in statistics: An overview,.

Disentanglement-Based Equivariant Learning for Compositional VQA Causal inference in statistics: An overview,

Reference 20

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Observation 258d9ccf-cc4c-44de-b1b1-18147eb74029 · outbound

This paper cites Group equivariant convolutional networks,.

Disentanglement-Based Equivariant Learning for Compositional VQA Group equivariant convolutional networks,

Reference 21

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Observation a41f3597-08c7-4efc-8e0a-7316e03724d7 · outbound

This paper cites Mutan: Multi- modal tucker fusion for visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Mutan: Multi- modal tucker fusion for visual question answering,

Reference 22

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Observation eb009872-6290-49f3-8e1a-e7ddef126de4 · outbound

This paper cites Joint embedding vqa model based on dynamic word vector,.

Disentanglement-Based Equivariant Learning for Compositional VQA Joint embedding vqa model based on dynamic word vector,

Reference 23

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Observation 01a0301e-1ca1-4e54-9a71-b08348506c9e · outbound

This paper cites Where to look: Focus regions for visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Where to look: Focus regions for visual question answering,

Reference 24

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Observation ca384247-0ec2-4078-9424-34498047a0bb · outbound

This paper cites The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision.

Disentanglement-Based Equivariant Learning for Compositional VQA The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Reference 25

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Observation d47d5ad8-33a3-4fe5-8afe-92d825fb68f7 · outbound

This paper cites Visual question answering with dense inter-and intra-modality interactions,.

Disentanglement-Based Equivariant Learning for Compositional VQA Visual question answering with dense inter-and intra-modality interactions,

Reference 26

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Observation 3cc4150e-e47b-4b05-99e9-0b3c88ffdd9c · outbound

This paper cites Attention is all you need,.

Disentanglement-Based Equivariant Learning for Compositional VQA Attention is all you need,

Reference 27

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Observation 6dd99fb5-5bb4-45b4-9e2a-353802844ec5 · outbound

This paper cites LXMERT: Learning Cross-Modality Encoder Representations from Transformers.

Disentanglement-Based Equivariant Learning for Compositional VQA LXMERT: Learning Cross-Modality Encoder Representations from Transformers

Reference 28

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Observation 80c0c08e-dfbc-43c6-b4ca-4ff972963b9f · outbound

This paper cites Boosting generic visual-linguistic representation with dynamic contexts,.

Disentanglement-Based Equivariant Learning for Compositional VQA Boosting generic visual-linguistic representation with dynamic contexts,

Reference 29

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Observation 335dc2dc-8591-4188-bb68-ed35c7241019 · outbound

This paper cites MM-LLMs: Recent Advances in MultiModal Large Language Models.

Disentanglement-Based Equivariant Learning for Compositional VQA MM-LLMs: Recent Advances in MultiModal Large Language Models

Reference 30

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Observation 6e5f3483-d568-407b-ba10-ce9cfc691609 · outbound

This paper cites Exploring compositional generalization of large language models,.

Disentanglement-Based Equivariant Learning for Compositional VQA Exploring compositional generalization of large language models,

Reference 31

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Observation a192a7dd-0f1a-4b78-b1b1-3f3de31dfc57 · outbound

This paper cites Learning, reasoning, and compositional gen- eralisation in multimodal language models,.

Disentanglement-Based Equivariant Learning for Compositional VQA Learning, reasoning, and compositional gen- eralisation in multimodal language models,

Reference 32

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This paper cites An empirical study of gpt-3 for few-shot knowledge-based vqa,.

Disentanglement-Based Equivariant Learning for Compositional VQA An empirical study of gpt-3 for few-shot knowledge-based vqa,

Reference 33

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This paper cites Learning to supervise knowledge retrieval over a tree structure for visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Learning to supervise knowledge retrieval over a tree structure for visual question answering,

Reference 34

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Observation 63888886-6f4c-493d-9d62-95357b596296 · outbound

This paper cites Towards causal vqa: Revealing and reducing spurious correlations by invariant and covariant semantic editing,.

Disentanglement-Based Equivariant Learning for Compositional VQA Towards causal vqa: Revealing and reducing spurious correlations by invariant and covariant semantic editing,

Reference 35

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This paper cites Film: Visual reasoning with a general conditioning layer,.

Disentanglement-Based Equivariant Learning for Compositional VQA Film: Visual reasoning with a general conditioning layer,

Reference 36

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This paper cites Transparency by design: Closing the gap between performance and interpretability in visual reasoning,.

Disentanglement-Based Equivariant Learning for Compositional VQA Transparency by design: Closing the gap between performance and interpretability in visual reasoning,

Reference 37

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This paper cites Lexsym: Compositionality as lexical symmetry,.

Disentanglement-Based Equivariant Learning for Compositional VQA Lexsym: Compositionality as lexical symmetry,

Reference 38

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This paper cites an unresolved cited work.

Disentanglement-Based Equivariant Learning for Compositional VQA Unresolved cited work

Reference 39

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Observation 86af0957-9e41-46cb-a8e0-c02afd9b4751 · outbound

This paper cites Disentangled representation learning,.

Disentanglement-Based Equivariant Learning for Compositional VQA Disentangled representation learning,

Reference 40

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This paper cites Robustly disentangled causal mechanisms: Validating deep representations for interventional robustness,.

Disentanglement-Based Equivariant Learning for Compositional VQA Robustly disentangled causal mechanisms: Validating deep representations for interventional robustness,

Reference 41

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This paper cites On causally disentangled representations,.

Disentanglement-Based Equivariant Learning for Compositional VQA On causally disentangled representations,

Reference 42

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This paper cites Derf: Decomposed radiance fields.

Disentanglement-Based Equivariant Learning for Compositional VQA Derf: Decomposed radiance fields

Reference 43

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This paper cites A meta-transfer objective for learning to disentangle causal mechanisms,.

Disentanglement-Based Equivariant Learning for Compositional VQA A meta-transfer objective for learning to disentangle causal mechanisms,

Reference 44

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This paper cites Disen- tangled generative causal representation learning,.

Disentanglement-Based Equivariant Learning for Compositional VQA Disen- tangled generative causal representation learning,

Reference 45

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This paper cites Equivariant flows: Exact likeli- hood generative learning for symmetric densities,.

Disentanglement-Based Equivariant Learning for Compositional VQA Equivariant flows: Exact likeli- hood generative learning for symmetric densities,

Reference 46

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This paper cites Group equivariant capsule networks,.

Disentanglement-Based Equivariant Learning for Compositional VQA Group equivariant capsule networks,

Reference 47

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This paper cites Learning generalized transformation equivariant representations via autoencoding transforma- tions,.

Disentanglement-Based Equivariant Learning for Compositional VQA Learning generalized transformation equivariant representations via autoencoding transforma- tions,

Reference 48

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Observation 16cd8704-c1fd-4a72-8d9a-a44a1b2d5715 · outbound

This paper cites Equivariant and invariant grounding for video question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Equivariant and invariant grounding for video question answering,

Reference 49

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Observation fa544d7f-30fb-4361-b3f8-1fb9263dc572 · outbound

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

Disentanglement-Based Equivariant Learning for Compositional VQA Vilt: Vision-and-language transformer without convolution or region supervision,

Reference 50

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This paper cites Invariant Risk Minimization.

Disentanglement-Based Equivariant Learning for Compositional VQA Invariant Risk Minimization

Reference 51

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Observation 637be5b8-5187-4b19-8d72-d63f0f60b91d · outbound

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Disentanglement-Based Equivariant Learning for Compositional VQA Bottom-up and top-down attention for image captioning and visual question answering,

Reference 52

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This paper cites Auto-Encoding Variational Bayes.

Disentanglement-Based Equivariant Learning for Compositional VQA Auto-Encoding Variational Bayes

Reference 53

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Observation c2c2093a-fb46-4478-8693-e3d95e68f4d4 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization,.

Disentanglement-Based Equivariant Learning for Compositional VQA Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 54

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This paper cites Clevr: A diagnostic dataset for compositional language and elementary visual reasoning,.

Disentanglement-Based Equivariant Learning for Compositional VQA Clevr: A diagnostic dataset for compositional language and elementary visual reasoning,

Reference 55

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This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answering,.

Disentanglement-Based Equivariant Learning for Compositional VQA Making the v in vqa matter: Elevating the role of image understanding in visual question answering,

Reference 56

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Observation afa23648-02e5-42d1-b46c-f31b83374864 · outbound

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

Disentanglement-Based Equivariant Learning for Compositional VQA Gqa: A new dataset for real-world visual reasoning and compositional question answering,

Reference 57

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Observation 33fd2797-4764-4720-9ee9-d266fa796a1b · outbound

This paper cites In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T.

Disentanglement-Based Equivariant Learning for Compositional VQA In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T

Reference 58

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Observation 41daf745-af95-48c6-a5bd-5de2f9c9c2e8 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Disentanglement-Based Equivariant Learning for Compositional VQA BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-07-01T22:46:20.176301Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9c4e75a6-2522-421d-b4b1-ddddd8ee115b · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

Disentanglement-Based Equivariant Learning for Compositional VQA Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-06-28T15:00:24.297044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 241e80d4-6cf4-4e75-9b52-4583a6893089 · outbound

This paper cites an unresolved cited work.

Disentanglement-Based Equivariant Learning for Compositional VQA Unresolved cited work

Reference 61

Resolution: unresolved; no resolver link, observed 2026-06-28T15:00:24.297044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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