The MLLM Field Guide, Curated by the Benchmark Authors

What it does

This is a curated index of multimodal large language model research, maintained by the NJU-MiG group. It catalogs papers, datasets, and benchmarks across topics like instruction tuning, hallucination, and chain-of-thought. The repository also doubles as a portal for the group’s own work, including literature surveys, the VITA omni-modal model family, and the MME benchmark suite.

The interesting bit

Most awesome lists are passive signposts; this one is an active research outpost. The curators do not merely collect papers—they publish the surveys, ship the VITA models, and define the MME evaluation standards that the rest of the field cites.

Key highlights

• Extensive paper tables with direct links to venues, code, and live demos where available.
• First-party projects embedded throughout: VITA for real-time vision-speech interaction, Video-MME for video understanding evaluation, and multiple comprehensive surveys.
• Dataset taxonomies covering pre-training, instruction tuning, RLHF, and chain-of-thought.
• Active WeChat community groups tied to specific sub-projects like VITA and MME.
• The README is large enough that GitHub truncates the preview.

Caveats

• The list is vast and the README preview is truncated, so expect to use browser search or scroll endurance.
• This is fundamentally a curated documentation hub; you will find bibliographies and links, not a single unified codebase to run out of the box.

Verdict

Researchers and engineers drowning in MLLM literature should treat this as a weekly checkpoint. If you need a monolithic, installable framework rather than a reading list with associated research satellites, look elsewhere.