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Collections including paper arxiv:2406.11839

DocLLM: A layout-aware generative language model for multimodal document understanding

Paper • 2401.00908 • Published Dec 31, 2023 • 182
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training

Paper • 2401.00849 • Published Jan 1, 2024 • 17
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents

Paper • 2311.05437 • Published Nov 9, 2023 • 49
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing

Paper • 2311.00571 • Published Nov 1, 2023 • 41

Multi-modality LVM

VoCo-LLaMA: Towards Vision Compression with Large Language Models

Paper • 2406.12275 • Published Jun 18, 2024 • 30
TroL: Traversal of Layers for Large Language and Vision Models

Paper • 2406.12246 • Published Jun 18, 2024 • 35
Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning

Paper • 2406.15334 • Published Jun 21, 2024 • 9
Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning

Paper • 2406.12742 • Published Jun 18, 2024 • 15

mDPO: Conditional Preference Optimization for Multimodal Large Language Models

Paper • 2406.11839 • Published Jun 17, 2024 • 38

mDPO: Conditional Preference Optimization for Multimodal Large Language Models

Paper • 2406.11839 • Published Jun 17, 2024 • 38
Pandora: Towards General World Model with Natural Language Actions and Video States

Paper • 2406.09455 • Published Jun 12, 2024 • 15
WPO: Enhancing RLHF with Weighted Preference Optimization

Paper • 2406.11827 • Published Jun 17, 2024 • 14
In-Context Editing: Learning Knowledge from Self-Induced Distributions

Paper • 2406.11194 • Published Jun 17, 2024 • 15

iVideoGPT: Interactive VideoGPTs are Scalable World Models

Paper • 2405.15223 • Published May 24, 2024 • 13
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24, 2024 • 53
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27, 2024 • 87
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27, 2024 • 31

image llm works

Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation

Paper • 2404.19752 • Published Apr 30, 2024 • 24
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Paper • 2404.16821 • Published Apr 25, 2024 • 56
MoAI: Mixture of All Intelligence for Large Language and Vision Models

Paper • 2403.07508 • Published Mar 12, 2024 • 75
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Paper • 2403.09611 • Published Mar 14, 2024 • 126

Alignment-DPO-line

sDPO: Don't Use Your Data All at Once

Paper • 2403.19270 • Published Mar 28, 2024 • 41
Advancing LLM Reasoning Generalists with Preference Trees

Paper • 2404.02078 • Published Apr 2, 2024 • 44
Learn Your Reference Model for Real Good Alignment

Paper • 2404.09656 • Published Apr 15, 2024 • 83
mDPO: Conditional Preference Optimization for Multimodal Large Language Models

Paper • 2406.11839 • Published Jun 17, 2024 • 38

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 26
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 13
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 41
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 22

about 13 hours ago

PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models

Paper • 2402.08714 • Published Feb 13, 2024 • 12
Data Engineering for Scaling Language Models to 128K Context

Paper • 2402.10171 • Published Feb 15, 2024 • 24
RLVF: Learning from Verbal Feedback without Overgeneralization

Paper • 2402.10893 • Published Feb 16, 2024 • 11
Coercing LLMs to do and reveal (almost) anything

Paper • 2402.14020 • Published Feb 21, 2024 • 13

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