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README.md

@@ -22,9 +22,9 @@ library_name: transformers
 
 - With **only 6.6B** activate parameters, GRIN MoE achieves **exceptionally good** performance across a diverse set of tasks, particularly in coding and mathematics tasks.
 
-- GRIN uses **SparseMixer-v2** to estimate the gradient related to expert routing, while the conventional MoE training treats expert gating as a proxy for the gradient estimation. 
+- GRIN uses [**SparseMixer-v2**](https://arxiv.org/html/2409.12136v1#Pt1) to estimate the gradient related to expert routing, while the conventional MoE training treats expert gating as a proxy for the gradient estimation. 
 
-- GRIN scales MoE training with **neither expert parallelism nor token dropping**, while the conventional MoE training employs expert parallelism and deploys token dropping.
+- GRIN scales MoE training with [**neither expert parallelism nor token dropping**](https://arxiv.org/pdf/2409.12136#page=5.42), while the conventional MoE training employs expert parallelism and deploys token dropping.
 
 ## Intended Uses