dirtyharrylyl / llm-in-vision Goto Github PK

Can you help me update the name of my paper:

From

(arXiv 2023.6) Aligning Large Multi-Modal Model with Robust Instruction Tuning.

to

(arXiv 2023.6) Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning.

Thanks!

(arXiv 2024.3) MineDreamer: Learning to Follow Instructions via Chain-of-Imagination for Simulated-World Control, [Paper], [Project]

1. AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling
2. VITRON: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing
3. Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
4. GLaMM: Pixel Grounding Large Multimodal Model
5. Planting a SEED of Vision in Large Language Model

EVE: Efficient Vision-Language Pre-training with Masked Prediction and
Modality-Aware MoE

Such as https://github.com/zhimin-z/awesome-awesome-machine-learning

1. Efficient Multimodal Learning from Data-centric Perspective

1. MM1: Methods, Analysis & Insights from
   Multimodal LLM Pre-training (https://arxiv.org/pdf/2403.09611.pdf)
2. Mini-Gemini: Mining the Potential of Multi-modality
   Vision Language Models (https://arxiv.org/pdf/2403.18814.pdf)

Hi, thanks for your great efforts for establishing this list. Could you please add our recent paper about large vision-language model to the list? The name is: DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback. The arxiv link. Thanks!

1. AUTORT: EMBODIED FOUNDATION MODELS FOR LARGE SCALE ORCHESTRATION OF ROBOTIC AGENTS

1. Lumos : Empowering Multimodal LLMs with Scene Text Recognition
2. Dej´a Vu Memorization in Vision-Language Models
3. Red Teaming Visual Language Models
4. VideoOFA: Two-Stage Pre-Training for Video-to-Text Generation

1. DetGPT: Detect What You Need via Reasoning
2. Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld
3. INSTRUCTCV: INSTRUCTION-TUNED TEXT-TO-IMAGE DIFFUSION MODELS AS VISION GENERALISTS
4. GROUNDHOG : Grounding Large Language Models to Holistic Segmentation
5. LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model
6. OCTAVIUS: MITIGATING TASK INTERFERENCE IN MLLMS VIA LORA-MOE