Paper Citation Record · LEDGER

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

As of 12 August 2026, this Paper Citation Record lists 100 of 113 outbound references and 9 inbound Pith citation observations for arXiv:2412.09604.

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

pith.paper-citation-record.v1
2412.09604 v1

Coverage vector

measured 100 of 113 reference resolution

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measured 109 of 109 standing notices

One-hop event checks from named stored sources.

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measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:35:40.295495Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:50:24.280970Z

Reference resolution

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External citation measurements

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Outbound references

Observation 64717b3e-5766-41ef-bc33-24fb9ff5f58d · outbound

This paper cites Qwen Technical Report.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Qwen Technical Report

Reference 1

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Observation 52df0d8e-5e4b-4c91-ad81-67c963194a47 · outbound

This paper cites Introducing our multimodal models, 2023.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Introducing our multimodal models, 2023

Reference 2

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Observation c06b6b5b-7756-4c95-8d47-81284370bb54 · outbound

This paper cites Improving image generation with better captions.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Improving image generation with better captions

Reference 3

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

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding PaliGemma: A versatile 3B VLM for transfer

Reference 4

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This paper cites Scene text visual question answering.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Scene text visual question answering

Reference 5

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

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Coyo-700m: Image-text pair dataset

Reference 6

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This paper cites InternLM2 Technical Report.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding InternLM2 Technical Report

Reference 7

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

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 8

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

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 9

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This paper cites SOLO: A Single Transformer for Scalable Vision-Language Modeling.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding SOLO: A Single Transformer for Scalable Vision-Language Modeling

Reference 10

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Observation 6eaa2e8e-9a92-4ffc-a583-6cfb99c13621 · outbound

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

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 11

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Observation ff0bc6a6-0d81-449a-b057-7d09068f27b0 · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Gonzalez, Ion Stoica, and Eric P

Reference 12

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This paper cites Icdar2019 robust read- ing challenge on arbitrary-shaped text-rrc-art.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Icdar2019 robust read- ing challenge on arbitrary-shaped text-rrc-art

Reference 13

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This paper cites MobileVLM V2: Faster and Stronger Baseline for Vision Language Model.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MobileVLM V2: Faster and Stronger Baseline for Vision Language Model

Reference 14

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This paper cites Simple and effec- tive multi-paragraph reading comprehension.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Simple and effec- tive multi-paragraph reading comprehension

Reference 15

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This paper cites Opencompass: A universal evaluation plat- form for foundation models.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Opencompass: A universal evaluation plat- form for foundation models

Reference 16

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This paper cites Funnel-transformer: Filtering out sequential redundancy for efficient language processing.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Funnel-transformer: Filtering out sequential redundancy for efficient language processing

Reference 17

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Observation c2dc95c6-0a66-4cec-90c5-5d0ba44fe7e3 · outbound

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

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Imagenet: A large-scale hierarchical im- age database

Reference 18

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This paper cites Unveiling Encoder-Free Vision-Language Models.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Unveiling Encoder-Free Vision-Language Models

Reference 19

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This paper cites Dreamllm: Synergistic multimodal com- prehension and creation.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Dreamllm: Synergistic multimodal com- prehension and creation

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This paper cites Vlmevalkit: An open-source toolkit for evaluating large multi-modality models, 2024.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Vlmevalkit: An open-source toolkit for evaluating large multi-modality models, 2024

Reference 21

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Taming transformers for high-resolution image synthesis

Reference 22

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

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Geneval: An object-focused framework for evaluating text- to-image alignment

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Wukong: A 100 million large-scale chinese cross-modal pre-training benchmark

Reference 26

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This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Gans trained by a two time-scale update rule converge to a local nash equilib- rium

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Block Transformer: Global-to-Local Language Modeling for Fast Inference

Reference 28

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Hudson and Christopher D

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Unified language-vision pre- training in llm with dynamic discrete visual tokenization

Reference 30

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding A diagram is worth a dozen images

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Ocr- free document understanding transformer

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Segment Anything

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Evaluating object hallucination in large vision-language models

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll ´ar, and C

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Improved Baselines with Visual Instruction Tuning

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Visual instruction tuning

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding World Model on Million-Length Video And Language With Blockwise RingAttention

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MMBench: Is Your Multi-modal Model an All-around Player?

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models

Reference 47

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding DeepSeek-VL: Towards Real-World Vision-Language Understanding

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Learn to explain: Multimodal reason- ing via thought chains for science question answering

Reference 49

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Megalith-huggingface

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Chartqa: A benchmark for question answering about charts with visual and logical reasoning

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Infographicvqa

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Plotqa: Reasoning over scientific plots

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Hierarchical Attention Encoder Decoder

Reference 56

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Datamux: Data multiplexing for neu- ral networks

Reference 57

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 58

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding GPT-4 Technical Report

Reference 59

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 60

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 61

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Learning transferable visual models from natural language supervision

Reference 62

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Zero-shot text-to-image generation

Reference 63

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Hierarchical Text-Conditional Image Generation with CLIP Latents

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding High-resolution image synthesis with latent diffusion models

Reference 65

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Photorealistic text-to-image diffusion models with deep language understanding

Reference 66

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 67

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Laion coco: 600m synthetic captions from laion2b-en

Reference 68

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Objects365: A large-scale, high-quality dataset for object detection

Reference 69

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Icdar2017 competition on reading chinese text in the wild (rctw-17)

Reference 70

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Textcaps: A dataset for image caption- ing with reading comprehension

Reference 71

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Towards VQA models that can read

Reference 72

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Textocr: Towards large- scale end-to-end reasoning for arbitrary-shaped scene text

Reference 73

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Journeydb: A benchmark for genera- tive image understanding

Reference 74

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 75

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Generative Multimodal Models are In-Context Learners

Reference 76

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Emu: Generative Pretraining in Multimodality

Reference 77

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Generative pretraining in mul- timodality

Reference 78

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Icdar 2019 competition on large-scale street view text with partial labeling-rrc-lsvt

Reference 79

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Gemini: A Family of Highly Capable Multimodal Models

Reference 80

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer

Reference 82

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 83

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding LLaMA: Open and Efficient Foundation Language Models

Reference 84

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Unsplash Dataset

Reference 85

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 86

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images

Reference 87

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 88

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding CogVLM: Visual Expert for Pretrained Language Models

Reference 89

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding The all-seeing project: Towards panoptic visual recognition and understanding of the open world

Reference 90

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Emu3: Next-Token Prediction is All You Need

Reference 91

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation

Reference 92

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding NExT-GPT: Any-to-Any Multimodal LLM

Reference 93

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

Reference 94

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding OmniGen: Unified Image Generation

Reference 95

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 96

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Raphael: Text-to- image generation via large mixture of diffusion paths

Reference 97

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Qwen2 Technical Report

Reference 98

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 99

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 100

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning

Reference 101

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding Megabyte: Predict- ing million-byte sequences with multiscale transformers

Reference 102

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SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

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Pith citing papers

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Liquid: Language Models are Scalable and Unified Multi-modal Generators SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 27

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Parameter-Inverted Image Pyramid Networks for Visual Perception and Multimodal Understanding SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 54

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UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

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WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 24

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UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 19

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OpenUni: A Simple Baseline for Unified Multimodal Understanding and Generation SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 24

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Show-o2: Improved Native Unified Multimodal Models SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 58

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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 SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 23

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Discrimination Is Generation: Unifying Ranking and Retrieval from a Tokenizer Perspective cites this paper.

Discrimination Is Generation: Unifying Ranking and Retrieval from a Tokenizer Perspective SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

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