Gen-Verse/HermesFlow

[NeurIPS 2025] HermesFlow: Seamlessly Closing the Gap in Multimodal Understanding and Generation

27
/ 100
Experimental

This project helps AI researchers and developers improve the ability of multimodal large language models (MLLMs) to understand and generate content. It takes in image-caption pairs and uses an iterative self-optimization process to refine the model's performance. The outcome is a more accurate and coherent MLLM that better aligns image and text information.

No commits in the last 6 months.

Use this if you are an AI researcher or developer working on advanced MLLM architectures and want to enhance their multimodal understanding and generation capabilities.

Not ideal if you are looking for an out-of-the-box solution for end-user applications or do not have experience with model training and optimization.

AI Research Multimodal AI Large Language Models Machine Learning Engineering Generative AI
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 8 / 25

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77

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Language

Python

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Last pushed

Sep 19, 2025

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