Paper Citation Record · LEDGER

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

As of 7 August 2026, this Paper Citation Record lists 100 of 137 outbound references and 41 inbound Pith citation observations for arXiv:2403.09611.

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

pith.paper-citation-record.v1
2403.09611 v4

Coverage vector

measured 100 of 137 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T04:09:36.019146Z

measured 141 of 141 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 41 of 41 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:03:25.101268Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

100 of 137 outbound references displayed

verified exact7
verified fuzzy35
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch43

External citation measurements

11
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 52984cd2-2a08-4832-8309-08850565750d · outbound

This paper cites GPT-4 Technical Report.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training GPT-4 Technical Report

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.440929Z

Source-reported events for the cited work

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Observation ff5ae10a-e89a-4ee7-a990-5b5971cbec47 · outbound

This paper cites In: ICCV (2019).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICCV (2019)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.544311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3f98930c-b76d-4ffd-af2b-2078e34f6aab · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.548097Z

Source-reported events for the cited work

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Observation 31f07fd6-8f3e-49ba-9eed-7e8a91a09192 · outbound

This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.180189Z

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Observation e91d606a-c567-4ecb-9f5e-7ae270836808 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.214525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 52e6c210-4f2d-4713-84c1-1bcd47a01b8e · outbound

This paper cites In: EMNLP (2013).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: EMNLP (2013)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.551875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7f1acd2c-a893-421b-9128-92049224e440 · outbound

This paper cites AAAI (2020).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training AAAI (2020)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.555688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e079e4cb-7c98-495b-8c24-8982cc7f0483 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Training Diffusion Models with Reinforcement Learning

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.373850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 970824c6-f955-4db4-9983-7c6969419393 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training On the Opportunities and Risks of Foundation Models

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.132763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 37cee271-5c8f-466c-95a1-258b6d9700d2 · outbound

This paper cites NeurIPS (2020).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training NeurIPS (2020)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.559111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 671852e6-e722-4d51-bdf2-25cfe45285fd · outbound

This paper cites https://github.com/kakaobrain/coyo-dataset (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training https://github.com/kakaobrain/coyo-dataset (2022)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.562695Z

Source-reported events for the cited work

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Observation 7bdbda1d-41da-4d34-8bf9-82923ec64273 · outbound

This paper cites Honeybee: Locality-enhanced Projector for Multimodal LLM.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Honeybee: Locality-enhanced Projector for Multimodal LLM

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.228739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 42425d51-6414-454d-84a8-ec8c278ea8ee · outbound

This paper cites In: CVPR (2021).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2021)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.566166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a3fc9b4e-5f33-4700-8d05-4bb087fed4f7 · outbound

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

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.498427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8e2c4f3b-0dc4-4d48-9875-ca59ea3711f1 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.127582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e5e08aa1-5855-456e-9fed-a694872c8e5b · outbound

This paper cites In: ICCV (2023).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICCV (2023)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.569961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 28579ef0-fbde-4206-a8f7-2108b1517492 · outbound

This paper cites PaLI-X: On Scaling up a Multilingual Vision and Language Model.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training PaLI-X: On Scaling up a Multilingual Vision and Language Model

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T14:36:10.299419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 634ff84b-25a1-48e8-8fe9-f4856ffe6db7 · outbound

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

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.145523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5addcd36-ca0f-4d0c-913a-87b665f0e296 · outbound

This paper cites JMLR (2023).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training JMLR (2023)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.573122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6f2d595-4bbe-4f80-8f1a-d7393d254b97 · outbound

This paper cites MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T16:35:38.347525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08f49448-5684-42c0-b86b-f5d11a8854df · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Scaling Instruction-Finetuned Language Models

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.193132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7ee52c6a-7a32-48d4-8a35-5a7120a86125 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 22

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.199890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99ab4eca-51ac-4c8a-9a8f-62e3b3f9b773 · outbound

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

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.207078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ead157dd-857d-4ad3-a04f-660a503e8b3c · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.576986Z

Source-reported events for the cited work

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Observation 2a60623f-18ef-4d72-9ccb-63e5341c61d3 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.580427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 942439c7-c3f0-438d-a349-3cdbb21074e3 · outbound

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

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.247419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6e9e65cb-c432-462a-80a8-2739a352a78c · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 27

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.252729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 02ce5c85-46d4-4d83-ab83-ad289e7fc8c3 · outbound

This paper cites PaLM-E: An Embodied Multimodal Language Model.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training PaLM-E: An Embodied Multimodal Language Model

Reference 28

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.320359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2b6f2cf3-f31f-4742-aaab-f310aba4c423 · outbound

This paper cites In: ICML (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICML (2022)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.583602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cc51c86e-8447-4528-87ac-473afe76094a · outbound

This paper cites Scalable Pre-training of Large Autoregressive Image Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Scalable Pre-training of Large Autoregressive Image Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.398124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f77a8e15-076d-4275-ad1e-8aeae032a19a · outbound

This paper cites Data Filtering Networks.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Data Filtering Networks

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.465728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7623c334-3a45-4175-ac6c-ea1bce611f53 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.586798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 80c1ef7a-c135-48fa-9e2b-aa9d77b07421 · outbound

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

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.522638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 81b7d2a8-df2a-4a4d-838e-2ac8de554557 · outbound

This paper cites Guiding Instruction-based Image Editing via Multimodal Large Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Guiding Instruction-based Image Editing via Multimodal Large Language Models

Reference 34

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.527995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 13e48b14-591c-44f2-82bc-19a8764a8f82 · outbound

This paper cites https://doi.org/10.5281/zenodo.10256836,https://zenodo.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training https://doi.org/10.5281/zenodo.10256836,https://zenodo

Reference 35

Resolution: verified exact; doi, observed 2026-05-16T04:09:36.095815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation af8ae0c2-4493-4ead-8c91-db74540d08e0 · outbound

This paper cites SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.109213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5c10f305-4288-4827-a656-462842bf09e0 · outbound

This paper cites MultiModal-GPT: A Vision and Language Model for Dialogue with Humans.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training MultiModal-GPT: A Vision and Language Model for Dialogue with Humans

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.115905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 49dccf1b-219c-4baa-9507-872f9a74bfe4 · outbound

This paper cites In: CVPR (2017).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2017)

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.589896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 39177b3e-2dd3-453d-be19-866453919463 · outbound

This paper cites In: CVPR (2018).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2018)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.592975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 09e96b13-8f7b-4534-955e-ea6b92dfd300 · outbound

This paper cites In: CVPR (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2022)

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.596132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 948384f8-c340-4e11-819f-f329b793ebde · outbound

This paper cites In: CVPR (2016).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2016)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.599739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 10fc5fcb-2c2c-449c-bf9d-7a35a5b434e0 · outbound

This paper cites Efficient Multimodal Learning from Data-centric Perspective.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Efficient Multimodal Learning from Data-centric Perspective

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.158828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4a7dad1e-d0d9-456e-91c1-11bf8ec428f5 · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Scaling Laws for Autoregressive Generative Modeling

Reference 43

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.169325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e0854ebc-7f93-4679-b5ac-fb21eb035aac · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.603096Z

Source-reported events for the cited work

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Observation aaf443ae-937c-4c18-b6b5-7042acc417bc · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.606308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d8cb4cf0-c05b-4ebd-b965-5fd44d7a30fc · outbound

This paper cites In: CVPR (2019).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2019)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.609658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c3af3a71-f461-4258-b78c-40d68e878ec3 · outbound

This paper cites https://huggingface.co/blog/idefics (2023).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training https://huggingface.co/blog/idefics (2023)

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.612755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4187dedb-bbe1-475d-9bc6-3132a3ed0cbc · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.615957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6cd8749b-43f6-4a2f-9ad3-2b64a24af156 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.619196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb5610d7-05a4-4afe-91d7-69ad82224a29 · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 50

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.221334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e0595f8f-a6e0-475f-bc56-8139c0607170 · outbound

This paper cites In: CVPR (2018).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2018)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.622409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 51721e93-c87c-456e-9d5b-a5110834c7b1 · outbound

This paper cites In: ECCV (2016).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ECCV (2016)

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.625838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 55fcfc5b-c42b-4508-ab2d-47d917163cbf · outbound

This paper cites In: ECCV (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ECCV (2022)

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.629426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 574486fd-fdde-468e-b95a-9d2b89837cd2 · outbound

This paper cites Generating Images with Multimodal Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Generating Images with Multimodal Language Models

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.284826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d4ca5d2-cea4-450d-ae1e-0f88769819bf · outbound

This paper cites In: ICLR (2023) 20 B.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICLR (2023) 20 B

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.633169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3b836275-5181-4428-b431-2b6e90226b10 · outbound

This paper cites LISA: Reasoning Segmentation via Large Language Model.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training LISA: Reasoning Segmentation via Large Language Model

Reference 56

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.331924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7fd15e9-a78d-4c20-b9bd-1793625f42e7 · outbound

This paper cites VeCLIP: Improving CLIP Training via Visual-enriched Captions.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training VeCLIP: Improving CLIP Training via Visual-enriched Captions

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.342638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1c8ec99a-7469-475b-b139-f4cd71a4b265 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.636218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9e5fe84a-a7cc-4f80-a240-335a5e24ed15 · outbound

This paper cites In: ICLR (2021).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICLR (2021)

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.639720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 88cc9aa3-66f0-45ff-8787-07577844ec3b · outbound

This paper cites MIMIC-IT: Multi-Modal In-Context Instruction Tuning.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training MIMIC-IT: Multi-Modal In-Context Instruction Tuning

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.435534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 38f5fa54-ffdb-4752-abd5-3518a7d1718d · outbound

This paper cites Otter: A Multi-Modal Model with In-Context Instruction Tuning.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Otter: A Multi-Modal Model with In-Context Instruction Tuning

Reference 61

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.448062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9dbfeace-473f-4087-bcf4-30b28aa6b0bd · outbound

This paper cites SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

Reference 62

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.453862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 125869bc-ad0a-4f6c-ae49-1192b81d123b · outbound

This paper cites Multimodal Foundation Models: From Specialists to General-Purpose Assistants.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Multimodal Foundation Models: From Specialists to General-Purpose Assistants

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.459955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fa4f27df-5e83-4913-8cb8-e909bf4afdb8 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.643433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2246ba8-9403-43fa-9f09-e147d5e42781 · outbound

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

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 65

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.471641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d84ef2d-5fec-424d-922f-c386ee15a067 · outbound

This paper cites M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning

Reference 66

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.478013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71e9bf56-b60f-4038-b075-f2bbf19b93c0 · outbound

This paper cites VisualBERT: A Simple and Performant Baseline for Vision and Language.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training VisualBERT: A Simple and Performant Baseline for Vision and Language

Reference 67

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.483344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b678ba0d-8536-4d27-ba67-4011e718dfa2 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Evaluating Object Hallucination in Large Vision-Language Models

Reference 68

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.488296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6b69ddb0-f51d-49e8-ad2a-daef9811f7b1 · outbound

This paper cites Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models

Reference 69

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.493562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c684790d-403a-421b-b6b9-7a70d445709d · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.646929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e62c1d3d-15ac-4a15-ab2e-037fa7173fb2 · outbound

This paper cites VILA: On Pre-training for Visual Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training VILA: On Pre-training for Visual Language Models

Reference 71

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.503622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4667a88a-6cea-4f9a-9748-108961504995 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Microsoft COCO: Common Objects in Context

Reference 72

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.508432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e9750ee8-4067-4275-8a67-a83b2d563b43 · outbound

This paper cites SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-17T03:03:27.047113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a7572d3a-e83e-4516-be1e-e996279e2ed1 · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Improved Baselines with Visual Instruction Tuning

Reference 74

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.518232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 05ed3e91-c99a-4fec-a901-904bf5699223 · outbound

This paper cites io/blog/2024-01-30-llava-next/.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training io/blog/2024-01-30-llava-next/

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.650865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 003de143-d596-4f17-bc3f-430b4edce97b · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.654426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ffe80b4-f047-46b4-9bbf-997312599f30 · outbound

This paper cites LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents

Reference 77

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.536840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ccdcdf43-7d9a-4726-9c80-dda1bfa04da9 · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training MMBench: Is Your Multi-modal Model an All-around Player?

Reference 78

Resolution: verified exact; local_arxiv, observed 2026-05-16T04:09:36.532290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5cabe2d8-13c7-4438-96c3-ace57effbacc · outbound

This paper cites NeurIPS (2019).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training NeurIPS (2019)

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.658025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 73c880c6-bb6b-4a68-a0fa-272319facf30 · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 80

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.102982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 871a3cd4-4e37-40f2-b055-fdc1f36fbf30 · outbound

This paper cites NeurIPS (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training NeurIPS (2022)

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.661678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e76a5442-ac1e-4876-8b39-6e7a7df635bf · outbound

This paper cites In: CVPR (2019).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2019)

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.665293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bd20772e-827e-4fe0-8507-3e43805db485 · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 83

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.121556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f35af081-a5c1-449f-9c66-9bf0da08ae3b · outbound

This paper cites In: WACV (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: WACV (2022)

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.669063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 30305ea0-6963-4d35-b7a0-f847132a4b3e · outbound

This paper cites In: WACV (2021).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: WACV (2021)

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.672927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8bf52fcc-1aa3-462a-a583-941e5644c6be · outbound

This paper cites In: ICDAR (2019).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICDAR (2019)

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.676624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 01d8b1b6-8edb-492f-bc97-5338971b6e4d · outbound

This paper cites In: NeurIPS (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: NeurIPS (2022)

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.680572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6827c88e-c9f4-4974-9d28-a097dea10b28 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training DINOv2: Learning Robust Visual Features without Supervision

Reference 88

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.151501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bbabfbed-a48e-485b-ad9c-e1e65b7a0f60 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.684792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 931fbc62-baa8-44de-b477-0f568596d534 · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 90

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.163953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8109ac73-0b16-4720-80b7-f2af40eab767 · outbound

This paper cites In: ICML (2021).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICML (2021)

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.688939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1bedb279-c508-4f94-b660-122cce42945d · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 92

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T04:09:36.174953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5123a8ea-01d0-42e5-b3bf-7100642977ba · outbound

This paper cites JMLR (2020).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training JMLR (2020)

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.692817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 00ea4575-ceb4-4f8a-9798-008834fa56ae · outbound

This paper cites In: ICCV (2023).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ICCV (2023)

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.696773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1f945584-c92f-4092-a28f-6cda591bcfd7 · outbound

This paper cites In: CVPR (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: CVPR (2022)

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.700458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 22655654-3f06-49e7-ab3d-77bc325d3960 · outbound

This paper cites In: Beygelzimer, A., Dauphin, Y., Liang, P., Vaughan, J.W.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: Beygelzimer, A., Dauphin, Y., Liang, P., Vaughan, J.W

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.704444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f75281d8-deb7-4374-a1fc-6da4e35dfaa4 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 97

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.708663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 50896e14-6c60-41c3-9b5f-547277fcfeaf · outbound

This paper cites In: ECCV (2022).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ECCV (2022)

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.712686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c87d41e1-e7dd-4f46-99e5-8ae662f85539 · outbound

This paper cites an unresolved cited work.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Unresolved cited work

Reference 99

Resolution: unresolved; raw_fallback, observed 2026-05-16T04:09:36.716261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d33cb590-3fef-4e27-b114-29e0d2f12b11 · outbound

This paper cites In: ACL (2018).

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training In: ACL (2018)

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T04:09:36.719797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 14b8c1fe-c569-4462-9952-7a6f42276d1b · inbound

A Survey on Multimodal Large Language Models cites this paper.

A Survey on Multimodal Large Language Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 61c632e2-a024-4ecd-969a-440c2fc20f46 · inbound

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone cites this paper.

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 74b488da-e850-4f47-a3e4-a542f4999c6a · inbound

How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites cites this paper.

How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f1e3ac38-2099-4fc0-a54e-1fd79265e8e8 · inbound

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

OpenVLA: An Open-Source Vision-Language-Action Model MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0cc19cb7-f707-4a8b-abe7-bba47e7b01d8 · inbound

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs cites this paper.

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 100

Resolution: verified exact; local_arxiv, observed 2026-05-17T00:05:03.829164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0cbfdc07-8249-45ed-9f01-533a10a4fe7a · inbound

PaliGemma: A versatile 3B VLM for transfer cites this paper.

PaliGemma: A versatile 3B VLM for transfer MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 96

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1fda17c4-bc48-4651-9e3e-e1407b6fa0ae · inbound

LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models cites this paper.

LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5e3cba1e-776f-47fa-bcee-c681ddb079c6 · inbound

MiniCPM-V: A GPT-4V Level MLLM on Your Phone cites this paper.

MiniCPM-V: A GPT-4V Level MLLM on Your Phone MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4bc1dab-bd26-4776-9b60-1e105abdc0bb · inbound

LLaVA-OneVision: Easy Visual Task Transfer cites this paper.

LLaVA-OneVision: Easy Visual Task Transfer MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2b45c23d-f818-4743-b9c3-15974fff83ba · inbound

mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models cites this paper.

mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 178

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T06:20:36.457574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c3d25bb7-cf7d-4f64-83e8-2634643781dc · inbound

Show-o: One Single Transformer to Unify Multimodal Understanding and Generation cites this paper.

Show-o: One Single Transformer to Unify Multimodal Understanding and Generation MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9614d6f-21ae-4f82-95a6-fcf0f851adaa · inbound

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? cites this paper.

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-05-16T07:59:32.843836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation db67f8a3-8083-40ea-b8f4-c41282c2bd7a · inbound

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models cites this paper.

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 40b0d271-7a01-4da9-a3ec-325d39165583 · inbound

PaliGemma 2: A Family of Versatile VLMs for Transfer cites this paper.

PaliGemma 2: A Family of Versatile VLMs for Transfer MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 43f2bb38-b30a-4eb6-b9ae-0c82ada3946c · inbound

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling cites this paper.

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 185

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0ee7314c-6c4c-4dfd-99ef-63d973fe5a0a · inbound

MetaMorph: Multimodal Understanding and Generation via Instruction Tuning cites this paper.

MetaMorph: Multimodal Understanding and Generation via Instruction Tuning MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 172

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T07:51:13.267056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 010c6de0-5704-47ef-87d1-90b6876a9286 · inbound

Semantics Disentanglement and Composition for Universal Image Coding with Efficiently LLM Reasoning and Generative Diffusion cites this paper.

Semantics Disentanglement and Composition for Universal Image Coding with Efficiently LLM Reasoning and Generative Diffusion MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-05-23T06:42:39.555305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2c3e8b0-a2cb-48c5-8adb-620909f0f6ec · inbound

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features cites this paper.

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ead99e0d-d6a2-4900-aaea-d29ea3561f95 · inbound

FLARE: Fully Integration of Vision-Language Representations for Deep Cross-Modal Understanding cites this paper.

FLARE: Fully Integration of Vision-Language Representations for Deep Cross-Modal Understanding MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-05-22T19:52:01.883820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0c45f6b8-6c9c-4d34-beed-57b63926474f · inbound

MMaDA: Multimodal Large Diffusion Language Models cites this paper.

MMaDA: Multimodal Large Diffusion Language Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b3d02633-9be4-4692-80de-134a95a7d6fe · inbound

Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding cites this paper.

Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T15:03:25.101268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 301aff66-ce55-45c8-91de-c03f5c645ec0 · inbound

Multimodal LLM-Guided Semantic Correction in Text-to-Image Diffusion cites this paper.

Multimodal LLM-Guided Semantic Correction in Text-to-Image Diffusion MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:49.131004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d246c863-0a36-4ae5-a52f-ff926dd5d1d1 · inbound

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought cites this paper.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T12:42:23.938819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e39d9be-e59f-403f-976d-c0213474736c · inbound

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation cites this paper.

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T12:38:43.703061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e4003eb-1b66-4a0d-bfdf-f24097734015 · inbound

ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding cites this paper.

ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T11:51:28.012308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b72702d1-76c2-49ca-ae00-13d7e5d4cdd0 · inbound

Rex-Thinker: Grounded Object Referring via Chain-of-Thought Reasoning cites this paper.

Rex-Thinker: Grounded Object Referring via Chain-of-Thought Reasoning MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T10:55:14.759449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b38f56ce-fee3-45bf-a545-1ee82014b56b · inbound

Synthetic Visual Genome cites this paper.

Synthetic Visual Genome MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T05:34:56.348041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd027e17-7925-479b-97f7-7d39f0994751 · inbound

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models cites this paper.

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:24.755181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2280f4f3-b2b0-4be1-838b-7c667339728c · inbound

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets cites this paper.

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:52.956170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26b9cebe-850f-4bff-b75f-82e4460c81a5 · inbound

Towards Multimodal Understanding via Stable Diffusion as a Task-Aware Feature Extractor cites this paper.

Towards Multimodal Understanding via Stable Diffusion as a Task-Aware Feature Extractor MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T18:52:35.255074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5b53bb2-96bb-493c-b041-ddd1971f8bb5 · inbound

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model cites this paper.

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T17:22:11.164532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7d879fd-ff47-4680-a577-3c7659f9c642 · inbound

Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models cites this paper.

Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 135

Resolution: unresolved; no resolver link, observed 2026-08-06T16:50:09.056933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 340c3a01-ac8a-4fda-9dd5-eb288decbba2 · inbound

MagicVL-2B: Empowering Vision-Language Models on Mobile Devices with Lightweight Visual Encoders via Curriculum Learning cites this paper.

MagicVL-2B: Empowering Vision-Language Models on Mobile Devices with Lightweight Visual Encoders via Curriculum Learning MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T05:36:20.191131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb22c86a-fb1b-4d97-8a4e-4a83edbcdedb · inbound

R3G: A Reasoning-Retrieval-Reranking Framework for Vision-Centric Answer Generation cites this paper.

R3G: A Reasoning-Retrieval-Reranking Framework for Vision-Centric Answer Generation MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-16T10:47:45.490874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 17f2b8d2-d76c-4729-a0dd-2ed2f6483cb5 · inbound

R3G: A Reasoning-Retrieval-Reranking Framework for Vision-Centric Answer Generation cites this paper.

R3G: A Reasoning-Retrieval-Reranking Framework for Vision-Centric Answer Generation MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T08:13:51.875404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e47458c-e6e4-484f-bcf0-2aff0da3f539 · inbound

Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models cites this paper.

Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5f442a76-4533-45d8-b2b6-6159d6599e5b · inbound

MixAtlas: Uncertainty-aware Data Mixture Optimization for Multimodal LLM Midtraining cites this paper.

MixAtlas: Uncertainty-aware Data Mixture Optimization for Multimodal LLM Midtraining MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df5b6639-7c56-4154-ab02-f94b25de8d52 · inbound

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

Compared to What? Baselines and Metrics for Counterfactual Prompting MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 89

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e6c0c0b3-0151-4b69-b23d-4747d0d5f1bd · inbound

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone cites this paper.

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2546657a-2e04-4ad7-84ff-2aa0687b3abb · inbound

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone cites this paper.

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:09:36.761640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3c4cf4c1-bc82-485c-a58d-18c69e8190a3 · inbound

An Exam for Active Observers cites this paper.

An Exam for Active Observers MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T21:12:05.997836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.