HazyResearch shows how to write facts into Transformers without training
CSProfKGD · x · 2026-07-23
A HazyResearch team reports a new way to inject knowledge into Transformer blocks without gradient descent.
- The paper frames the problem as how facts are stored in language models’ MLPs, then asks whether they can be written into Transformers directly.
- The authors claim a closed-form recipe for fact-storing, Transformer-ready MLPs.
- The work has been accepted at COLM 2026 and is presented as a research/blogpost package for further reading.
Related event: HazyResearch Proposes Training-Free Method to Write Facts into MLPs(5 posts)→
More from Research
- Workshop talk on 3D editing and generation highlights new research directions — RanaHanocka · 2026-07-23
- ApertureData argues AI memory is a relevance engine, not just retrieval — dunkhippo33 · 2026-07-23
- NVIDIA says its open-source robotics simulator cut training from 5 hours to under 2 minutes — imjustnewatai · 2026-07-23
- A new CS2 replay benchmark would ask agents to spot cheaters in impossible cases — rufreakde1 · 2026-07-23
- Anshul Kundaje is hiring 1–2 scientists for agentic genomics work — anshulkundaje · 2026-07-23
- DecBench tracks how close LLMs are to near-perfect binary decompilation — moyix · 2026-07-23