Research Claims Docs

Loading page…

AI is dramatically lowering the cost of reading papers, writing code, and running experiments. But as research output explodes, telling which results can be trusted keeps getting harder. CiteArk connects the claims in scientific papers with their experimental conditions, execution process, result evidence, and verification records, so researchers and agents can verify claims, reuse experimental results, and build follow-up research on them instead of repeating work. We hope these trustworthy research records will grow into a scientific foundation that researchers, labs, and agents can all build on together.

Website

Explore
Claims
Runs
Import a paper

Docs

API docs
Badges & embeds
Roadmap
License Gate

About

About CiteArk
News
Contact & takedown

Legal

Privacy policy
Terms of service

© 2026 CiteArk · Ligu Corp. The traceable evidence layer for research.

Search papers, claims, runs, and users/

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning · CiteArk

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

PublicScope: Standard

Authors:Tri Dao

arXiv 2023 Machine Learning (cs.LG)

More

Copy repository link

1,206 files · 51.1 MB

CCiteArk CAP 1.0 Verified RunnerVerification runnerImport verified CAP 1.0 research Artifact—Current version

NameContentSize

README.md114 KB

Loading preview…