Meta Superintelligence Labs vs Facebook AI Research

🚀 Frontier AI Seminar Series

Jan 30, 2026

After delivering influential models like LLaMA and SAM, Meta’s AI research has been the subject of ongoing debate and speculation.

Instead of engaging with the headlines, in the next AI by Hand Frontier Seminar I’ll take a quieter approach: letting the papers speak for themselves—albeit only through what Meta is willing to openly publish.

I’ll walk through three of the most recent publications from FAIR and three from MSL, using them to understand what Meta is actually investing in and where its AI research direction appears to be heading.

Our guest industry expert will be Yichen Wang, who is a Research Scientist at Meta working on GenAI safety.

The six papers I picked are as follows:

Facebook AI Research (FAIR)

Text-Guided Semantic Image Encoder
1. https://arxiv.org/abs/2511.20770 (11.25.2025)
Pixel Seal: Adversarial-only training for invisible image and video watermarking
1. https://arxiv.org/abs/2512.16874 (12.18.2025)
Safety Alignment of LLMs via Non-cooperative Games
1. https://arxiv.org/abs/2512.20806 (12.23.2025)

Meta Superintelligence Labs (MSL)

REFRAG: Rethinking RAG based Decoding
1. https://arxiv.org/abs/2509.01092 (10.12.2025)
SAM 3: Segment Anything with Concepts
1. https://arxiv.org/abs/2511.16719 (11.20.2025)
Dr. Zero: Self-Evolving Search Agents without Training Data
1. https://arxiv.org/abs/2601.07055 (1.11.2026)