Paper Citation Record · LEDGER

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

As of 21 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 47 inbound Pith citation observations for arXiv:2412.03069.

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

pith.paper-citation-record.v1
2412.03069 v2

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:54:20.710373Z

measured 124 of 124 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 47 of 47 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:41:47.730706Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

77 of 77 outbound references displayed

verified exact0
verified fuzzy20
unresolved55
parse uncertain1
malformed identifier1
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 6d0b9588-1f0b-4fde-98c5-e1d5b1e072db · outbound

This paper cites GPT-4 Technical Report.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation 9a9c9a12-e813-42db-b699-35d41b04f9fe · outbound

This paper cites Qwen Technical Report.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Qwen Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.437208Z

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Observation a600daf4-fa30-4998-98c4-aaf2a5cf9cc6 · outbound

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

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.440971Z

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Observation 1e42f739-a626-4adb-9fdb-6eac2aac593f · outbound

This paper cites Improving image generation with better captions.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Improving image generation with better captions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.533353Z

Source-reported events for the cited work

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Observation 0126eda4-bacf-4cd4-8c8e-490363c9c0a4 · outbound

This paper cites Coyo-700m: Image-text pair dataset.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Coyo-700m: Image-text pair dataset

Reference 5

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Observation 83b9e60b-9a7b-4007-8f90-4783bc6ac15f · outbound

This paper cites Muse: Text-To-Image Generation via Masked Generative Transformers.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Muse: Text-To-Image Generation via Masked Generative Transformers

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.452018Z

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Observation bde1a2d9-d9a1-4920-9081-92afa09a5756 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.456159Z

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Observation ee66adad-dd0e-4eae-b10f-14d17ca91814 · outbound

This paper cites Vitamin: Designing scalable vision models in the vision-language era.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Vitamin: Designing scalable vision models in the vision-language era

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.515254Z

Source-reported events for the cited work

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Observation 3bcc1fd3-13ea-4a9a-ab99-7c06c4a9641e · outbound

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

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.463765Z

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Observation 62f6e974-6380-4f05-8464-83a3484c7266 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Reference 10

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Observation d0bcf96c-b243-4657-8491-d244bdf98ed7 · outbound

This paper cites Scaling vision transformers to 22 billion pa- rameters.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Scaling vision transformers to 22 billion pa- rameters

Reference 11

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Observation 277ced2b-40c5-4f62-8949-5edbf2e6179c · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Imagenet: A large-scale hierarchical image database

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.473283Z

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Observation 3b41a819-0890-419e-aa81-45f85d443dd6 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Taming transformers for high-resolution image synthesis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.483238Z

Source-reported events for the cited work

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Observation 8442a6c1-1f43-4240-a106-4becb8e2f815 · outbound

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

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.479149Z

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Observation 6b935a5e-e2e8-49b5-a594-cceb16895586 · outbound

This paper cites Geneval: An object-focused framework for evaluating text- to-image alignment.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Geneval: An object-focused framework for evaluating text- to-image alignment

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.471133Z

Source-reported events for the cited work

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Observation 34ba906f-63fd-43aa-9dc1-7255b69946b8 · outbound

This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing

Reference 16

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Observation 77e81f5a-c599-44c3-8940-1b40d1538d1a · outbound

This paper cites Classifier-Free Diffusion Guidance.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Classifier-Free Diffusion Guidance

Reference 17

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Observation 1eb8ae94-2fc6-4c62-8163-8cd34638aa07 · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.493411Z

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Observation 275b0fea-09db-4020-94dc-f24fb0517144 · outbound

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

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.452078Z

Source-reported events for the cited work

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Observation 9465b5a9-afb4-4bd5-9d1d-47c20d3b6441 · outbound

This paper cites A diagram is worth a dozen images.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation A diagram is worth a dozen images

Reference 20

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Source-reported events for the cited work

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Observation cc895db4-5e7e-4816-9e78-2b335767cbc0 · outbound

This paper cites Autoregressive image generation using residual quantization.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Autoregressive image generation using residual quantization

Reference 21

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Source-reported events for the cited work

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Observation 1b2f7917-e8a3-4552-8f38-da51b150f588 · outbound

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

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

Reference 22

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Observation 6c17fdfb-fa90-4736-8ba1-43dc7d9771e7 · outbound

This paper cites Seed-bench: Bench- marking multimodal large language models.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Seed-bench: Bench- marking multimodal large language models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.405613Z

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Observation baa69641-420a-4977-aaee-7f0f29323e22 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 24

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Observation cc9ee8dd-5b24-4b43-a77a-ddfbe1152e28 · outbound

This paper cites ImageFolder: Autoregressive Image Generation with Folded Tokens.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation ImageFolder: Autoregressive Image Generation with Folded Tokens

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T22:54:20.522317Z

Source-reported events for the cited work

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Observation 882d1ad6-b025-4264-988f-d5b5ab787d8d · outbound

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

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Evaluating Object Hallucination in Large Vision-Language Models

Reference 26

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Observation 8190837a-a921-4522-8ec4-960382bb187b · outbound

This paper cites Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Reference 27

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Observation cd2555aa-4a88-491b-aa82-b381cddce663 · outbound

This paper cites Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

Reference 28

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Observation bd19d9d4-709d-4af7-885b-579623b7efa9 · outbound

This paper cites Improved baselines with visual instruction tuning.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Improved baselines with visual instruction tuning

Reference 29

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Observation 81e0e3a7-ba44-455b-9d72-1a14cfebe7db · outbound

This paper cites Visual instruction tuning.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Visual instruction tuning

Reference 30

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Observation 0ecdae2f-e6b6-43b7-b059-12bb71766442 · outbound

This paper cites World Model on Million-Length Video And Language With Blockwise RingAttention.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation World Model on Million-Length Video And Language With Blockwise RingAttention

Reference 31

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Observation 91137bbb-6da4-4879-b7ed-4efac947e0ca · outbound

This paper cites Mmbench: Is your multi-modal model an all-around player? In European Conference on Computer Vision, pages 216–233.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Mmbench: Is your multi-modal model an all-around player? In European Conference on Computer Vision, pages 216–233

Reference 32

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Observation 25bbee17-e5d8-4dfa-a61d-269935bd978d · outbound

This paper cites Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation

Reference 33

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Observation 24522319-7885-4295-8579-54bddb232fc1 · outbound

This paper cites STAR: Scale-wise Text-conditioned AutoRegressive image generation.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation STAR: Scale-wise Text-conditioned AutoRegressive image generation

Reference 34

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Observation d8332b65-6797-4a6c-b077-13e575320895 · outbound

This paper cites BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers

Reference 35

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Observation 2a49e759-944f-4cc3-be32-39fcc5dc92f6 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 36

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Observation 236c09c7-6794-46f9-b308-3c4730825e3f · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Learning transferable visual models from natural language supervi- sion

Reference 37

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Observation d8f784aa-ffff-4faa-a70f-414a7e0a1104 · outbound

This paper cites Zero-shot text-to-image generation.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Zero-shot text-to-image generation

Reference 38

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Observation 8d85a53c-c0cc-4ca7-a145-53fe4e229c54 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 39

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Observation e145cf4c-c565-448b-9a35-40ca5035c484 · outbound

This paper cites Gener- ating diverse high-fidelity images with vq-vae-2.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Gener- ating diverse high-fidelity images with vq-vae-2

Reference 40

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Observation 38b9f5a3-b13a-49ec-97d3-3cc4ef2844cd · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models, 2021.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation High-resolution image syn- thesis with latent diffusion models, 2021

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.324026Z

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Observation adf34022-b3d7-42cc-8bec-9feb71bf7ddf · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 42

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Observation a54e9c2c-08d4-49d7-a53f-49f48bad442b · outbound

This paper cites Towards vqa models that can read.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Towards vqa models that can read

Reference 43

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Observation 32dc96f1-7c70-44c4-ad5d-7dedb75769a3 · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 44

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation EVA-CLIP: Improved Training Techniques for CLIP at Scale

Reference 45

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This paper cites Emu: Generative Pretraining in Multimodality.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Emu: Generative Pretraining in Multimodality

Reference 46

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Observation c578ad44-d825-4931-a306-606d9cd9bbdc · outbound

This paper cites HART: Efficient Visual Generation with Hybrid Autoregressive Transformer.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Reference 47

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This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 48

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Gemini: A Family of Highly Capable Multimodal Models

Reference 49

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This paper cites Qwen2.5: A party of foundation models, 2024.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Qwen2.5: A party of foundation models, 2024

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:54:21.291175Z

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Observation 830a81bd-5396-4b1b-a97e-418a0757aa38 · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 51

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

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Reference 52

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Observation efa95757-7033-4ac6-bdf8-8aad11a1e1bd · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 53

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Observation bbc79bd2-d88d-4710-b43e-82da69f3eec0 · outbound

This paper cites Neural discrete representation learning.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Neural discrete representation learning

Reference 54

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This paper cites Emu3: Next-Token Prediction is All You Need.

TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Emu3: Next-Token Prediction is All You Need

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Small-scale proxies for large-scale Transformer training instabilities

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation NExT-GPT: Any-to-Any Multimodal LLM

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation GPT-4o: Visual perception performance of multimodal large language models in piglet activity understanding

Reference 59

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Realworldqa, 2024

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Imagere- ward: Learning and evaluating human preferences for text- to-image generation

Reference 63

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Vector-quantized Image Modeling with Improved VQGAN

Reference 64

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for ex- pert agi

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Sigmoid loss for language image pre-training

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Regularized vector quantization for tokenized im- age synthesis

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Lmms- eval: Reality check on the evaluation of large multimodal models, 2024

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Tinyllama: An open-source small language model, 2024

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Movq: Modulating quantized vectors for high- fidelity image generation

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

Reference 74

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Scaling the Codebook Size of VQGAN to 100,000 with a Utilization Rate of 99%

Reference 76

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Reference 251

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Pith citing papers

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MUSE-VL: Modeling Unified VLM through Semantic Discrete Encoding TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 52

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Reference 29

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Reference 49

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Reference 68

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Reference 45

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Reference 60

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Reference 34

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Reference 55

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Reference 63

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Reference 60

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Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 62

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Reference 89

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UniGen: Enhanced Training & Test-Time Strategies for Unified Multimodal Understanding and Generation TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 51

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Reference 59

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Reference 70

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Reference 75

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Reference 47

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Show-o2: Improved Native Unified Multimodal Models TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 89

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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 44

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Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 25

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Observation e77a85cc-3c45-4774-b6cd-e6648a3feeb8 · inbound

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer cites this paper.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T19:41:23.743296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07056f24-8547-4f77-acc2-e499b83f6a3f · inbound

A Unified Low-level Foundation Model for Enhancing Pathology Image Quality cites this paper.

A Unified Low-level Foundation Model for Enhancing Pathology Image Quality TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T13:00:48.183504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6a80fd0-984a-4d3a-b633-fccfc4c216a0 · inbound

Interleaving Reasoning for Better Text-to-Image Generation cites this paper.

Interleaving Reasoning for Better Text-to-Image Generation TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T22:55:44.942757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8d924e2-91f0-486d-85fd-6eaf58b666e0 · inbound

Reconstruction Alignment Improves Unified Multimodal Models cites this paper.

Reconstruction Alignment Improves Unified Multimodal Models TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-04T22:36:08.122658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b88afb4d-7579-4fad-ae74-0661592f29e0 · inbound

A Unified and Controllable Framework for Layered Image Generation with Visual Effects cites this paper.

A Unified and Controllable Framework for Layered Image Generation with Visual Effects TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-16T11:57:50.252224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 609a9b36-99f1-4287-a95c-8be0c11ae5cb · inbound

FeynmanBench: Benchmarking Multimodal LLMs on Diagrammatic Physics Reasoning cites this paper.

FeynmanBench: Benchmarking Multimodal LLMs on Diagrammatic Physics Reasoning TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T16:52:59.470222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f7bec7b5-3764-4502-9b7e-e1511547bb45 · inbound

FeynmanBench: Benchmarking Multimodal LLMs on Diagrammatic Physics Reasoning cites this paper.

FeynmanBench: Benchmarking Multimodal LLMs on Diagrammatic Physics Reasoning TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-13T12:10:53.720348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 211c994b-f3f4-45f2-a9ff-72e6f011aac3 · inbound

Think in Strokes, Not Pixels: Process-Driven Image Generation via Interleaved Reasoning cites this paper.

Think in Strokes, Not Pixels: Process-Driven Image Generation via Interleaved Reasoning TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:10:53.714152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 85b178fd-4ad0-47f0-974e-080507de5924 · inbound

Free Lunch for Unified Multimodal Models: Enhancing Generation via Reflective Rectification with Inherent Understanding cites this paper.

Free Lunch for Unified Multimodal Models: Enhancing Generation via Reflective Rectification with Inherent Understanding TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T14:15:28.979944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fec4d6af-7265-4a0e-a833-957939712b01 · inbound

Meta-CoT: Enhancing Granularity and Generalization in Image Editing cites this paper.

Meta-CoT: Enhancing Granularity and Generalization in Image Editing TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:41:19.367534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 226722f2-0983-4fef-883d-c2374909187d · inbound

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling cites this paper.

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 63

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T10:16:29.041921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b7e1ded3-b160-45dd-bb73-6d9cfdeb56cc · inbound

What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion cites this paper.

What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 62

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T04:05:57.477353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ab1bc623-546d-41bc-9581-ddde19cc7ab6 · inbound

Vision Foundation Models as Generalist Tokenizers for Image Generation cites this paper.

Vision Foundation Models as Generalist Tokenizers for Image Generation TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:03:13.455436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 179e42ab-e52d-411d-96ca-81da6fff4ca9 · inbound

Histogram-constrained Image Generation cites this paper.

Histogram-constrained Image Generation TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 48

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:05:41.186922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c07c4d84-88bb-4bb0-bf4c-91baa3e94539 · inbound

OSVE: One Step Video Editing with One Step Diffusion Models cites this paper.

OSVE: One Step Video Editing with One Step Diffusion Models TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T11:29:16.883675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.