Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models | Paper Citation Record

Observation 014a6b4e-5543-4ca1-b076-21b0c270a20b · outbound

This paper cites Vqa: Visual question answering.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Vqa: Visual question answering

Reference 1

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Observation 10842e3c-6d3a-4439-b75b-b3045ac97e33 · outbound

This paper cites Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond

Reference 2

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Observation 165fadfc-068b-4381-9f8b-f0418c780c06 · outbound

This paper cites Hallucination of Multimodal Large Language Models: A Survey.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Hallucination of Multimodal Large Language Models: A Survey

Reference 3

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This paper cites Causal feature learning: an overview.Behav- iormetrika, 44:137–164, 2017.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Causal feature learning: an overview.Behav- iormetrika, 44:137–164, 2017

Reference 4

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This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 5

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This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 6

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Observation 08463434-275a-44f0-8a15-921f2f369b28 · outbound

This paper cites Neural Modular Control for Embodied Question Answering.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Neural Modular Control for Embodied Question Answering

Reference 7

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Observation b2fbccac-c66d-4628-be79-e878396c9193 · outbound

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

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 8

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Observation c9e7988c-42e5-43fa-b732-83a94c0e3604 · outbound

This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answering.International Journal of Computer Vision, 127:398 – 414, 2016.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Making the v in vqa matter: Elevating the role of image understanding in visual question answering.International Journal of Computer Vision, 127:398 – 414, 2016

Reference 9

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Observation 4c0e50e2-16d7-4d1d-abe8-98e1c48e207f · outbound

This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 10

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Observation 743e38ca-d838-4589-a5b6-fac6d159fec8 · outbound

This paper cites Unbiased classification through bias-contrastive and bias-balanced learning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unbiased classification through bias-contrastive and bias-balanced learning

Reference 11

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Observation 6f844add-5e84-4dbf-966b-b0ddcb69709e · outbound

This paper cites CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning

Reference 12

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Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 13

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Observation 371ec215-5d3f-4af2-9653-411bd6ef6134 · outbound

This paper cites Hudson and Christopher D.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Hudson and Christopher D

Reference 14

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Observation 6b824612-57b4-4b5d-97b2-6a50423c7b47 · outbound

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

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 15

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Observation 23edb86b-9426-4220-910f-9df8a7b8e2f2 · outbound

This paper cites Introducing idefics: An open reproduction of state-of-the-art visual language model.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Introducing idefics: An open reproduction of state-of-the-art visual language model

Reference 16

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Observation b199e25a-bed3-414e-b672-dba534049efa · outbound

This paper cites Vcoder: Versatile vision encoders for multimodal large language models.2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 27992–28002, 2023.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Vcoder: Versatile vision encoders for multimodal large language models.2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 27992–28002, 2023

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:16.062074Z

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Observation 08d6b5e4-04de-42e6-b611-c6b08f6e1937 · outbound

This paper cites Causal inference meets deep learning: A comprehensive survey.Research, 7, 2024.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Causal inference meets deep learning: A comprehensive survey.Research, 7, 2024

Reference 18

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Observation 7c7091d6-4d2d-46bd-a51a-954f60465837 · outbound

This paper cites Unbiased learning-to-rank with biased feedback.Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2016.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unbiased learning-to-rank with biased feedback.Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2016

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:15.592963Z

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Observation 6ec84d65-83d9-479c-a740-01987c29c820 · outbound

This paper cites Deep visual-semantic alignments for generating image descriptions.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Deep visual-semantic alignments for generating image descriptions

Reference 20

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Observation 374a87b5-da22-49ce-9e0c-32b9bc6c8c25 · outbound

This paper cites Learning not to learn: Training deep neural networks with biased data.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9004–9012, 2018.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Learning not to learn: Training deep neural networks with biased data.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9004–9012, 2018

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:15.414896Z

Source-reported events for the cited work

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Observation 15cc1d48-831d-4b2b-815f-8922bf6ca451 · outbound

This paper cites Sophia Koepke, Cordelia Schmid, and Zeynep Akata.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Sophia Koepke, Cordelia Schmid, and Zeynep Akata

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:15.204904Z

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Observation 8017d1f0-3ddf-4639-928e-61290230a9f3 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Adam: A Method for Stochastic Optimization

Reference 23

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Observation 057b404f-ab45-4d77-a9ce-4786f8262b62 · outbound

This paper cites Shamma, Michael S.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Shamma, Michael S

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:14.795871Z

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Observation 88185505-8ad4-4524-8633-415616b4eaba · outbound

This paper cites V olcano: Mitigating multimodal hal- lucination through self-feedback guided revision.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models V olcano: Mitigating multimodal hal- lucination through self-feedback guided revision

Reference 25

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Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 26

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This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 27

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This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 28

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Observation fec8f324-f7ed-4747-838f-b80befc809d8 · outbound

This paper cites Towards deconfounded image-text matching with causal inference.Proceedings of the 31st ACM International Conference on Multimedia, 2023.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Towards deconfounded image-text matching with causal inference.Proceedings of the 31st ACM International Conference on Multimedia, 2023

Reference 29

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

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Evaluating object hallucination in large vision-language models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:13.663560Z

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Observation 2e2e3bee-a71e-4ca4-af16-0469f0d9b3ca · outbound

This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 31

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This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C

Reference 32

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Observation eb905292-61e0-4dab-b002-2e2cddee5023 · outbound

This paper cites Show, deconfound and tell: Image captioning with causal inference.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 18020–18029, 2022.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Show, deconfound and tell: Image captioning with causal inference.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 18020–18029, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:13.146836Z

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Observation a1c74763-284a-4a2e-8092-48a08a69eeca · outbound

This paper cites Mitigating hallucination in large multi-modal models via robust instruction tuning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Mitigating hallucination in large multi-modal models via robust instruction tuning

Reference 34

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Observation 8983dbec-8768-4db9-ba5e-b0e487b5f1a6 · outbound

This paper cites A Survey on Hallucination in Large Vision-Language Models.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models A Survey on Hallucination in Large Vision-Language Models

Reference 35

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Observation 941f5dd5-4539-49b9-a280-cf10f8299786 · outbound

This paper cites Improved baselines with visual instruction tuning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Improved baselines with visual instruction tuning

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Observation 5e7a841c-fdb8-4c1f-a050-953bc72af9d7 · outbound

This paper cites Visual Instruction Tuning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Visual Instruction Tuning

Reference 37

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Observation 0d077064-b255-47b8-ac09-99c7c253a416 · outbound

This paper cites Mmbench: Is your multi-modal model an all-around player? InEuropean Conference on Computer Vision, 2023.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Mmbench: Is your multi-modal model an all-around player? InEuropean Conference on Computer Vision, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:12.302595Z

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Observation b7588ef9-9cb8-436b-a37c-800b87776e0a · outbound

This paper cites Discovering causal signals in images.2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 58–66, 2016.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Discovering causal signals in images.2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 58–66, 2016

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:12.118295Z

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Observation 523091e8-a24f-4750-ae8b-f8182bb2be3b · outbound

This paper cites Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

Reference 40

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This paper cites The deep regression bayesian network and its applications: Proba- bilistic deep learning for computer vision.IEEE Signal Processing Magazine, 35:101–111, 2018.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models The deep regression bayesian network and its applications: Proba- bilistic deep learning for computer vision.IEEE Signal Processing Magazine, 35:101–111, 2018

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:11.947909Z

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Observation 006add3d-a315-4f53-a516-c8a0a11441ad · outbound

This paper cites Counterfactual vqa: A cause-effect look at language bias.2021 IEEE/CVF Conference on Computer Vision and Pattern Recog- nition (CVPR), pages 12695–12705, 2020.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Counterfactual vqa: A cause-effect look at language bias.2021 IEEE/CVF Conference on Computer Vision and Pattern Recog- nition (CVPR), pages 12695–12705, 2020

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:11.777390Z

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Observation 5ecf661f-6ea1-435b-926d-75e954dee91a · outbound

This paper cites Basic books, 2018.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Basic books, 2018

Reference 43

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Source-reported events for the cited work

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Observation 8dfdcc2a-a1fe-4914-a4c7-dc3190657254 · outbound

This paper cites Two causal principles for improving visual dialog.2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10857–10866, 2019.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Two causal principles for improving visual dialog.2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10857–10866, 2019

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:11.617036Z

Source-reported events for the cited work

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Observation d55702c7-ff6b-4c49-a756-de8213488948 · outbound

This paper cites Object hallucination in image captioning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Object hallucination in image captioning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:11.469998Z

Source-reported events for the cited work

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Observation 3bbb0d25-af3a-423d-8185-218fc55a05ac · outbound

This paper cites Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:04.245081Z

Source-reported events for the cited work

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Observation 8bb3660c-308d-4a13-8354-25b943a7e2e1 · outbound

This paper cites Towards vqa models that can read.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 8309–8318, 2019.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Towards vqa models that can read.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 8309–8318, 2019

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:11.302421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 65608bd0-3c4c-4d26-8627-33705a2fcae3 · outbound

This paper cites Heikkila, and Li Liu.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Heikkila, and Li Liu

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:11.130832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation edac3404-1493-48f5-80d1-2653097f8606 · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:04.556684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1f9e1e8-9e64-434b-a8e2-fa11d12d3a42 · outbound

This paper cites Unbiased scene graph generation from biased training.2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 3713–3722, 2020.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unbiased scene graph generation from biased training.2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 3713–3722, 2020

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:10.936087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 919477ab-3f62-44cc-977e-1c958d98f2c6 · outbound

This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:18:10.780403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 745b2ab8-e68d-4476-b6fd-ab9083935f9b · outbound

This paper cites Vigc: Visual instruction generation and correction.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Vigc: Visual instruction generation and correction

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:10.604240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 46414d78-f54d-4b3b-be4d-1f5f1f83e100 · outbound

This paper cites Visual commonsense r-cnn.2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10757–10767, 2020.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Visual commonsense r-cnn.2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10757–10767, 2020

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:10.410650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a8223c6f-90d4-4f43-8f1e-5880c854b88c · outbound

This paper cites Advancing Fine-Grained Visual Understanding with Multi-Scale Alignment in Multi-Modal Models.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Advancing Fine-Grained Visual Understanding with Multi-Scale Alignment in Multi-Modal Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:05.180098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1959433-08a9-49a0-93d0-1a067cdbb920 · outbound

This paper cites Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:05.285816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa113eba-7ed1-415b-8f0d-49af9320eeb5 · outbound

This paper cites NoiseBoost: Alleviating Hallucination with Noise Perturbation for Multimodal Large Language Models.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models NoiseBoost: Alleviating Hallucination with Noise Perturbation for Multimodal Large Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:05.380471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 253f180e-74c8-4f1e-ad21-5d10357f2318 · outbound

This paper cites Courville, Ruslan Salakhutdinov, Richard S.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Courville, Ruslan Salakhutdinov, Richard S

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:10.277841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 20d51a02-14c0-45ff-8692-a18202018126 · outbound

This paper cites Deconfounded image captioning: A causal retrospect.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Deconfounded image captioning: A causal retrospect

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:10.087615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71dbf5a5-7195-4ddb-bfb1-09dabccc5f90 · outbound

This paper cites Causal attention for vision-language tasks.2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9842–9852, 2021.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Causal attention for vision-language tasks.2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9842–9852, 2021

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:09.901506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7575dd97-3d66-4c89-bb73-6b0f483b71fe · outbound

This paper cites A survey on causal inference.ACM Transactions on Knowledge Discovery from Data (TKDD), 15:1 – 46, 2020.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models A survey on causal inference.ACM Transactions on Knowledge Discovery from Data (TKDD), 15:1 – 46, 2020

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:09.718877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41f45e62-096e-4bac-b892-b359a868553e · outbound

This paper cites Woodpecker: Hallucination correction for multimodal large language models.Sci.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Woodpecker: Hallucination correction for multimodal large language models.Sci

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:09.490957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 224f1f59-cb6d-497f-bdf7-87ef6f198797 · outbound

This paper cites Ferret: Refer and Ground Anything Anywhere at Any Granularity.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Ferret: Refer and Ground Anything Anywhere at Any Granularity

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:06.180366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80659cfb-199e-4c0f-9523-42f07edff6c6 · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:06.339518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c82cd4c3-1388-4a71-b80b-5dcc43ae2439 · outbound

This paper cites Interventional Few-Shot Learning.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Interventional Few-Shot Learning

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:18:07.619481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5e3c6167-066a-43bc-ab62-1856b4a4871d · outbound

This paper cites Halle-control: Controlling object hallucination in large multimodal models.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Halle-control: Controlling object hallucination in large multimodal models

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:08.887598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f5f9ddb8-4be1-4c37-b9d3-3b73313b8254 · outbound

This paper cites Analyzing and Mitigating Object Hallucination in Large Vision-Language Models.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Analyzing and Mitigating Object Hallucination in Large Vision-Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:06.855970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79e8e05a-e626-4d00-9df2-dd4a61db20ba · outbound

This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:18:09.114842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f0f35041-5b4b-4063-bf88-62415a9fb8ee · outbound

This paper cites dining table.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models dining table

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:08.731952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bde4ca91-50f9-43c9-a11c-74f6db19fcf9 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:06.946545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ff641f8-205a-4537-af09-3406dcfcdb44 · outbound

This paper cites 7 and 8).

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models 7 and 8)

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:08.514660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8e766066-1fec-4c4a-80cb-c71c96755af1 · outbound

This paper cites 9 and 10).

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models 9 and 10)

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:08.321787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9a6cbe8e-50bc-4de3-aff2-ea4f16e4dafa · outbound

This paper cites dining table.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models dining table

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:18:08.137272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1ddd20d-6f33-40ec-93c3-69b60b169d17 · outbound

This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 2014

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:18:14.972036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 04c88184-dc78-4217-8d50-78eaaf56251e · outbound

This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:18:12.451967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5b8ed909-166b-43ac-949f-6d80c4f720eb · outbound

This paper cites an unresolved cited work.

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:18:12.861978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers