# BradyFU/Awesome-Multimodal-Large-Language-Models

:sparkles::sparkles:Latest Advances on Multimodal Large Language Models

Repository: https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models
Canonical: https://ross.abutalabs.com/products/awesome-multimodal-large-language-models
License Family: other
Topics: instruction-tuning, instruction-following, large-vision-language-model, visual-instruction-tuning, multi-modality, in-context-learning, large-language-models, large-vision-language-models, multimodal-chain-of-thought, multimodal-in-context-learning, multimodal-instruction-tuning, multimodal-large-language-models, chain-of-thought
Last push: 2026-08-21T16:19:20+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 35, longevity 85
- inputs: {"age_days": 1202, "days_push": 12, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 17988, forks 1132 (observed 2026-08-28T04:11:20.720243+00:00)

## What it is
A curated awesome-list tracking the latest advances in multimodal large language models (MLLMs), including papers, surveys, benchmarks like MME and Video-MME, and related projects such as the VITA series. It serves as a research reference hub rather than runnable software.

## Use cases
- find recent papers on multimodal large language models
- track benchmarks for evaluating vision-language models
- locate surveys on multimodal instruction tuning
- research video understanding evaluation for MLLMs
- keep up with state-of-the-art multimodal chain-of-thought research
- find open-source omni MLLM projects

## When to choose
- you need a continuously updated index of MLLM research papers and benchmarks
- you are surveying the multimodal LLM landscape for a literature review
- you want links to evaluation benchmarks like MME and Video-MME

## When to avoid
- you need runnable code or a library to build applications
- you want a maintained software tool rather than a paper list
- you need a single model implementation instead of a research collection

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: large-language-models, artificial-intelligence, computer-vision, awesome-lists, tutorials
- platform: -
- tags: awesome-list, multimodal, vision-language-models, benchmarks, survey, papers, instruction-tuning, chain-of-thought, natural-language-processing, web-server

## Member repositories
- BradyFU/Awesome-Multimodal-Large-Language-Models (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:20.720243+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:02:11.672607+00:00, confidence not recorded.
  - readme: https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models (fetched 2026-08-28T04:11:20.720243+00:00, sha edd60e83bd35)
- Data as of 2026-08-30T08:39:29.467469+00:00.