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Paper Citation Record · LEDGER

Scalable Visual Pretraining for Language Intelligence

As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.09657.

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

pith.paper-citation-record.v1
2607.09657 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:33:10.074420Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

41 of 41 outbound references displayed

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  • unresolved39
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Outbound references

Observation b8c47e2c-77be-4d64-b8dc-b0f48c0f6e77 · outbound

This paper cites Barsalou.

Scalable Visual Pretraining for Language Intelligence Barsalou

Reference 1

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Observation 3746aa4f-4b1a-474a-abf2-7f00e4336f24 · outbound

This paper cites Barsalou.

Scalable Visual Pretraining for Language Intelligence Barsalou

Reference 2

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Observation 9c2199ab-4db8-41f2-8e18-b8c88d96c95b · outbound

This paper cites Nougat: Neural optical understanding for academic documents.

Scalable Visual Pretraining for Language Intelligence Nougat: Neural optical understanding for academic documents

Reference 3

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Observation 04c59f22-7e65-4f8b-ae08-07301156695f · outbound

This paper cites Language models are few-shot learners.

Scalable Visual Pretraining for Language Intelligence Language models are few-shot learners

Reference 4

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Observation fa8e1007-5b7a-4170-9e61-754bd09c3719 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Scalable Visual Pretraining for Language Intelligence Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 5

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Observation d5966839-b7c8-46d8-a512-df69ed8f9a29 · outbound

This paper cites Xtuner: A toolkit for efficiently fine-tuning llm.

Scalable Visual Pretraining for Language Intelligence Xtuner: A toolkit for efficiently fine-tuning llm

Reference 6

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Observation d05adbf0-518e-42c0-81ae-2888d6666cde · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Scalable Visual Pretraining for Language Intelligence The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 7

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Observation fbbca701-a1c5-4493-905c-b37dbac3e40a · outbound

This paper cites The Llama 3 Herd of Models.

Scalable Visual Pretraining for Language Intelligence The Llama 3 Herd of Models

Reference 8

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Observation bb00c18b-c33b-433e-8f8d-c9c7974b8c75 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Scalable Visual Pretraining for Language Intelligence Training Compute-Optimal Large Language Models

Reference 9

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Observation ec3917de-ad44-4442-b341-57b7e1b0b96c · outbound

This paper cites The Platonic Representation Hypothesis.

Scalable Visual Pretraining for Language Intelligence The Platonic Representation Hypothesis

Reference 10

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Observation 0b2623e6-b67b-4d20-b6b4-44af10497db0 · outbound

This paper cites GPT-4o System Card.

Scalable Visual Pretraining for Language Intelligence GPT-4o System Card

Reference 11

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Observation 00c2fbd2-7cea-4e09-8dff-7d2e5eb89b4e · outbound

This paper cites Scaling Laws for Neural Language Models.

Scalable Visual Pretraining for Language Intelligence Scaling Laws for Neural Language Models

Reference 12

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Observation 751d240c-522c-4644-90d7-b6a264841737 · outbound

This paper cites OCR-free Document Understanding Transformer.

Scalable Visual Pretraining for Language Intelligence OCR-free Document Understanding Transformer

Reference 13

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Observation 1c9a8ba3-9ca8-4360-8ed4-6ceb840a36fe · outbound

This paper cites Similarity of neural network representations revisited.

Scalable Visual Pretraining for Language Intelligence Similarity of neural network representations revisited

Reference 14

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Observation 08469284-d937-4473-9dda-95329c39aa22 · outbound

This paper cites Larkin and Herbert A.

Scalable Visual Pretraining for Language Intelligence Larkin and Herbert A

Reference 15

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Observation 72ab5ab9-1b4b-4ff8-befb-867806a997c8 · outbound

This paper cites Pix2struct: Screenshot parsing as pretraining for visual language understanding.

Scalable Visual Pretraining for Language Intelligence Pix2struct: Screenshot parsing as pretraining for visual language understanding

Reference 16

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Observation 5b609578-0400-4419-8d6b-6562de2c61bd · outbound

This paper cites Tracing the representation geometry of language models from pretraining to post-training.

Scalable Visual Pretraining for Language Intelligence Tracing the representation geometry of language models from pretraining to post-training

Reference 17

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Observation 4bfb3a5c-b2ca-4374-b82c-bdd75fd2e77e · outbound

This paper cites Autoregressive image generation without vector quantization.Advances in Neural Information Processing Systems, 37:56424–56445, 2024.

Scalable Visual Pretraining for Language Intelligence Autoregressive image generation without vector quantization.Advances in Neural Information Processing Systems, 37:56424–56445, 2024

Reference 18

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Observation bbf0a4c9-2906-49ab-a274-d87212619035 · outbound

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

Scalable Visual Pretraining for Language Intelligence Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning.Advances in Neural Information Processing Systems, 35:17612–17625, 2022

Reference 19

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Observation d20ccc5c-43f6-487e-aaf1-5b1d8fa8e22a · outbound

This paper cites Revisiting the Role of Language Priors in Vision-Language Models.

Scalable Visual Pretraining for Language Intelligence Revisiting the Role of Language Priors in Vision-Language Models

Reference 20

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Observation 93e5c59c-1d2a-4363-b0e4-424e34ef33c2 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

Scalable Visual Pretraining for Language Intelligence Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 21

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Observation dd40361d-36a6-42ff-ba76-8ddf1d893acd · outbound

This paper cites Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts.

Scalable Visual Pretraining for Language Intelligence Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts

Reference 22

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Observation 239b6565-1ea2-4913-a2c7-827c8bd51436 · outbound

This paper cites Chartqapro: A more diverse and challenging benchmark for chart question answering.

Scalable Visual Pretraining for Language Intelligence Chartqapro: A more diverse and challenging benchmark for chart question answering

Reference 23

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Observation 8837db91-f031-4cc2-9926-e590a0b4b903 · outbound

This paper cites American invitational mathematics ex- amination (AIME).

Scalable Visual Pretraining for Language Intelligence American invitational mathematics ex- amination (AIME)

Reference 24

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Observation 7472badf-d638-430c-bf9a-0602dd78126a · outbound

This paper cites Llama 3.2 vision model card.

Scalable Visual Pretraining for Language Intelligence Llama 3.2 vision model card

Reference 25

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Observation cb0efa8c-57e8-4dc6-9cf1-61721a724063 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Scalable Visual Pretraining for Language Intelligence Representation Learning with Contrastive Predictive Coding

Reference 26

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Observation acd58fce-6dc3-4b1a-8458-2ecbf37bc76a · outbound

This paper cites Openwebmath: An open dataset of high-quality mathematical web text.

Scalable Visual Pretraining for Language Intelligence Openwebmath: An open dataset of high-quality mathematical web text

Reference 27

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Observation da07e400-09b4-4cf0-9132-7ad6451806a8 · outbound

This paper cites Humanity's Last Exam.

Scalable Visual Pretraining for Language Intelligence Humanity's Last Exam

Reference 28

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Observation 5c16946c-be79-4299-b664-df7adfa67325 · outbound

This paper cites Qwen3.5: Towards native multimodal agents, February 2026.

Scalable Visual Pretraining for Language Intelligence Qwen3.5: Towards native multimodal agents, February 2026

Reference 29

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Observation 6f8b033b-b4a0-4d54-9a0a-e204f9bee17e · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Scalable Visual Pretraining for Language Intelligence GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 30

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Observation 6a7e673d-0243-4486-9c16-46960ab59d5f · outbound

This paper cites Visualizing data using t-sne.Journal of Machine Learning Research, 9(86):2579–2605, 2008.

Scalable Visual Pretraining for Language Intelligence Visualizing data using t-sne.Journal of Machine Learning Research, 9(86):2579–2605, 2008

Reference 31

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Observation 74266ce5-cc88-4c3b-9053-9d07f60f0c60 · outbound

This paper cites MinerU: An Open-Source Solution for Precise Document Content Extraction.

Scalable Visual Pretraining for Language Intelligence MinerU: An Open-Source Solution for Precise Document Content Extraction

Reference 32

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Observation 3b8ce6b2-4b6d-4290-ac23-c2a828bea112 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Scalable Visual Pretraining for Language Intelligence Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 33

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Observation df685192-34af-4b8d-93d7-0f36f1a83b8b · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

Scalable Visual Pretraining for Language Intelligence MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 34

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source=pdf_text observed=2026-08-02T07:33:09.384419Z digest=sha256:1132ede2e8ac75a21a46586e979bc75209e2d939ce968d89ec3cda3074354f42

Observation 974d4fbd-1a77-4fbc-a192-c2a0eb3e8b59 · outbound

This paper cites Emergent Abilities of Large Language Models.

Scalable Visual Pretraining for Language Intelligence Emergent Abilities of Large Language Models

Reference 35

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source=pdf_text observed=2026-08-02T07:33:09.504568Z digest=sha256:7f77786a1c439cdc480867b5d879d6d04c1b8f697189c1df4833b6737b55c8c7

Observation 0358d240-7186-4ea6-ba37-285247f7d261 · outbound

This paper cites Qwen3 Technical Report.

Scalable Visual Pretraining for Language Intelligence Qwen3 Technical Report

Reference 36

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Observation 7a2b2e41-0edb-4191-83bd-a03c47bdd84d · outbound

This paper cites Mmmu-pro: A more robust multi-discipline multimodal understanding benchmark.

Scalable Visual Pretraining for Language Intelligence Mmmu-pro: A more robust multi-discipline multimodal understanding benchmark

Reference 37

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source=pdf_text observed=2026-08-02T07:33:09.711862Z digest=sha256:2bcfdae12fabf176937742a91d886cff8934e8e527b382b7c33dc37b109a2d9c

Observation 53efcfad-baeb-412a-851a-d82299eafd8c · outbound

This paper cites The nature of external representations in problem solving.Cognitive Science, 21(2):179–217,.

Scalable Visual Pretraining for Language Intelligence The nature of external representations in problem solving.Cognitive Science, 21(2):179–217,

Reference 38

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Observation 52eacf1a-c44b-48c2-bf79-fb92ac28f055 · outbound

This paper cites Exploring visual pretraining for learning language intelligence.

Scalable Visual Pretraining for Language Intelligence Exploring visual pretraining for learning language intelligence

Reference 39

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Observation 4d07708f-6447-41c0-940f-99d947910f73 · outbound

This paper cites think step by step.

Scalable Visual Pretraining for Language Intelligence think step by step

Reference 40

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unresolved
no resolver link, observed 2026-08-02T07:33:10.074420Z

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Observation ab1a5b1b-8b8e-4671-b708-ee06ebd0958b · outbound

This paper cites an unresolved cited work.

Scalable Visual Pretraining for Language Intelligence Unresolved cited work

Reference 1997

Resolution
verified exact
doi, observed 2026-08-02T07:33:23.573861Z

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.

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Pith citing papers

No inbound Pith citation observations are available.