Of course, love me some confirmation bias!
DCLM was for text, DCVLM is the same for vision: analyzing VLM data mix across scales. Filtering is no bueno, but the "type" mixing matters, with unfortunately (but imo expectedly) the best small-scale mix != the best mid-scale mix.
DataComp-VLM aka DCVLM is finally out! It was such a pleasure working with this team of cracked ML data folks. Check out what changes in comparison to DCLM as we have surprising findings for our VLM data pool.
Models are what they eat, and it continues to show!
🚀New Paper
https://t.co/cHemp66IDM
Everyone obsesses over VLM architectures & training recipes. But what about the data?
Presenting the latest work in the DataComp-series: a testbed for VLM data curation with 1,000+ controlled experiments and some surprising lessons 👀
🧵👇
The misery around recent decision for EU Frontier AI Grand Challenge reveals again strong deficits in EU decision making and its lack of basic competence in ML/AI. Hard to explain otherwise how an entity without a track of record in NeurIPS/ICLR/ICML gets to do "Frontier AI".
wild to me that people vibe-generate slides for conference talks
they are ugly (for now). they are low info densiry (thanks rlhf)
but worse, they don't represent your thoughts, so your presentation of them will be terrible, unless you put in a ton of work (so just write them!)
Models are typically specialized to new domains by finetuning on small, high-quality datasets.
We find that repeating the same dataset 10–50× starting from pretraining leads to substantially better downstream performance, in some cases outperforming larger models. 🧵
1/ People often think better multilingual models must come at the cost of English performance. Not true. The constraint isn’t capacity, it’s data quality, and we can fix it.
Today @datologyAI shares ÜberWeb: a year of multilingual curation lessons, scaled to 20T+ tokens.
@xeophon@RicardoMonti9@datologyai > You even got one in your name, how fun
Until you start applying for a US visa/bank account/SSN, this is where the fun stops 😂
> ß/ẞ into the data as well
As part of my PhD contract at ETH Zurich I had to agree to not use those anymore :( Swiss rules and whatnot 🇨🇭
@StasBekman@datologyai@josh_wills I sent over a mail to your Snowflake address, probably easier than a tweet. In any case, glad the OVERLORD ref was already helpful!