# pliang279/awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

Repository: https://github.com/pliang279/awesome-multimodal-ml
Canonical: https://ross.abutalabs.com/products/awesome-multimodal-ml
License: MIT
License Family: permissive
Topics: multimodal-learning, machine-learning, representation-learning, natural-language-processing, computer-vision, speech-processing, robotics, healthcare, reading-list, deep-learning, reinforcement-learning
Last push: 2024-08-20T19:46:33+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2655, "days_push": 743, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6926, forks 900 (observed 2026-08-28T04:09:51.446732+00:00)

## What it is
A curated reading list of research papers, surveys, tutorials, and datasets on multimodal machine learning, maintained by Paul Liang at CMU. It organizes resources across core areas like representation, fusion, alignment, and pretraining, plus applications spanning vision, language, speech, robotics, and healthcare.

## Use cases
- find papers on multimodal fusion and alignment
- get started learning multimodal machine learning
- find datasets for vision-language research
- prepare a course or tutorial on multimodal ML
- survey recent trends in multimodal pretraining
- find reading material for a research literature review

## When to choose
- you need a curated, organized entry point into multimodal ML research
- you are a student or researcher building a literature review
- you want links to tutorials, courses, and survey papers

## When to avoid
- you need runnable code or a software library
- you need an exhaustive, automatically updated paper index
- you are looking for non-research practical tooling

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, nlp, computer-vision, speech-recognition
- domain: machine-learning, artificial-intelligence, computer-vision, speech-processing, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, reading-list, multimodal-learning, research-papers, representation-learning, natural-language-processing

## Member repositories
- pliang279/awesome-multimodal-ml (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:51.446732+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 2026-08-29T17:41:25.245548+00:00, confidence not recorded.
  - readme: https://github.com/pliang279/awesome-multimodal-ml (fetched 2026-08-28T04:09:51.446732+00:00, sha a3e5469c5da6)
- Data as of 2026-08-30T08:39:29.467469+00:00.