Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training | Paper Citation Record

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This paper cites Pixtral 12B.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Pixtral 12B

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This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Flamingo: a Visual Language Model for Few-Shot Learning

Reference 2

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This paper cites MINT-1T: scaling open-source multimodal data by 10x: A multimodal dataset with one trillion tokens.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training MINT-1T: scaling open-source multimodal data by 10x: A multimodal dataset with one trillion tokens

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

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Language models are few-shot learners

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This paper cites Lundberg, Harsha Nori, Hamid Palangi, Marco T´ulio Ribeiro, and Yi Zhang.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Lundberg, Harsha Nori, Hamid Palangi, Marco T´ulio Ribeiro, and Yi Zhang

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This paper cites Sharegpt4v: Improving large multi-modal models with better captions.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Sharegpt4v: Improving large multi-modal models with better captions

Reference 8

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This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Are We on the Right Way for Evaluating Large Vision-Language Models?

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This paper cites Sharegpt4video: Improving video understanding and generation with better captions.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Sharegpt4video: Improving video understanding and generation with better captions

Reference 10

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This paper cites CompCap: Improving Multimodal Large Language Models with Composite Captions.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training CompCap: Improving Multimodal Large Language Models with Composite Captions

Reference 11

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This paper cites DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback

Reference 12

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided Code-Vision Representation

Reference 13

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This paper cites Scaling Laws for Predicting Downstream Performance in LLMs.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Scaling Laws for Predicting Downstream Performance in LLMs

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training SOLO: A Single Transformer for Scalable Vision-Language Modeling

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training VisionArena: 230K Real World User-VLM Conversations with Preference Labels

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Unresolved cited work

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training NVLM: Open Frontier-Class Multimodal LLMs

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This paper cites Unveiling encoder-free vision-language models.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Unveiling encoder-free vision-language models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training A survey of vision-language pre-trained models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training The Llama 3 Herd of Models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training On Pre-training of Multimodal Language Models Customized for Chart Understanding

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Mme: A comprehensive evaluation benchmark for multimodal large language models, 2024

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training On Pre-training of Multimodal Language Models Customized for Chart Understanding

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Making llama SEE and draw with SEED tokenizer

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training GneissWeb: Preparing High Quality Data for LLMs at Scale

Reference 29

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Exploring the frontier of vision-language models: A survey of current methodologies and future directions

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training MultiModal-GPT: A Vision and Language Model for Dialogue with Humans

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Scaling Laws for Neural Language Models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Compression Represents Intelligence Linearly

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training GPT-4o System Card

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training The Scalability of Simplicity: Empirical Analysis of Vision-Language Learning with a Single Transformer

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Grounding language models to images for multimodal inputs and outputs

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training RL with KL penalties is better viewed as Bayesian inference

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Datacomp-lm: In search of the next generation of training sets for language models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Otter: A Multi-Modal Model with In-Context Instruction Tuning

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Seed-bench: Benchmarking multimodal large language models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Silkie: Preference Distillation for Large Visual Language Models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Multimodal arxiv: A dataset for improving scientific comprehension of large vision-language models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Visualbert: A simple and performant baseline for vision and language

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Evaluating Object Hallucination in Large Vision-Language Models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Multimodal Mamba: Decoder-only Multimodal State Space Model via Quadratic to Linear Distillation

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Microsoft coco: Common objects in context

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Visual instruction tuning

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Examining LLMs' Uncertainty Expression Towards Questions Outside Parametric Knowledge

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Improved Baselines with Visual Instruction Tuning

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

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Mmbench: Is your multi-modal model an all-around player? In European conference on computer vision, pages 216–233

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Diving into Self-Evolving Training for Multimodal Reasoning

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training MMInstruct: A High-Quality Multi-Modal Instruction Tuning Dataset with Extensive Diversity

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training DeepSeek-VL: Towards Real-World Vision-Language Understanding

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training DeepSeek-VL: Towards Real-World Vision-Language Understanding

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Learning transferable visual models from natural language supervision

Reference 66

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Openomni: Large language models pivot zero-shot omnimodal alignment across language with real-time self-aware emotional speech synthesis

Reference 68

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Policy opti- mization via importance sampling

Reference 69

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Laion- 5b: An open large-scale dataset for training next generation image-text models

Reference 70

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Shaker, Salman H

Reference 71

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters

Reference 72

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 73

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Emu: Generative pretraining in multimodality

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning

Reference 75

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training PandaGPT: One Model To Instruction-Follow Them All

Reference 77

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training OFA: unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:49:29.277670Z

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Aligning Large Multimodal Models with Factually Augmented RLHF

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training HoVLE: Unleashing the Power of Monolithic Vision-Language Models with Holistic Vision-Language Embedding

Reference 80

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Reconstructive Visual Instruction Tuning

Reference 81

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 82

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This paper cites Scaling Pre-training to One Hundred Billion Data for Vision Language Models.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Scaling Pre-training to One Hundred Billion Data for Vision Language Models

Reference 83

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training SimVLM: Simple Visual Language Model Pretraining with Weak Supervision

Reference 84

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets

Reference 85

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Knowledge-augmented few-shot visual relation detection

Reference 86

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Qwen2.5 Technical Report

Reference 87

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Capsfusion: Rethinking image-text data at scale

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training OmniAlign-V: Towards Enhanced Alignment of MLLMs with Human Preference

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Xing, Xiaodan Liang, and Zhiqiang Shen

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Observation 3aea2af3-136b-4e7b-94b9-a7548592bc4a · outbound

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Vinvl: Revisiting visual representations in vision-language models

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Minigpt-5: Interleaved vision-and-language generation via generative vokens

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Minigpt-4: Enhanc- ing vision-language understanding with advanced large language models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:49:29.232823Z

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Observation 87d92ebd-c559-40de-af3c-bd1e0548a290 · outbound

This paper cites Generalized decoding for pixel, image, and language.

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Generalized decoding for pixel, image, and language

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training CompCap: Improving Multimodal Large Language Models with Composite Captions

Reference 2024

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