Stanford and UC Berkeley introduce TokenGate for faster long-context prefill
Original title: Researchers from Stanford and UC Berkeley Introduce TokenGate: Token-Gated Attention Makes Long-Context Prefill Up to 11.3x Faster
The title claims token-gated attention speeds long-context prefill by up to 11.3 times; the article body was not available.
A MarkTechPost headline says researchers from Stanford and UC Berkeley introduced TokenGate, describing token-gated attention that makes long-context prefill up to 11.3x faster. The captured page contains only a cookie-consent notice, so no method, models, benchmarks or release details are available beyond that title.
Unconfirmed: Only the headline is available; the 11.3x figure is the outlet’s claim and is not supported by any visible results.
- The stated speedup is up to 11.3x for long-context prefill.
- No model names, code or evaluation details appear in the captured text.
- Products
- TokenGate
- Organizations
- StanfordUC Berkeley
From the original article
14 min read at marktechpost.comStanford and UC Berkeley researchers released TokenGate, a drop-in learned token pruning module for LLMs. It cuts long-context prefill time-to-first-token by 1. 4x to 11.
By Asif Razzaq · marktechpost.com
A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.