diff --git a/README.md b/README.md
index 3ea3e9c9..f2447270 100644
--- a/README.md
+++ b/README.md
@@ -73,7 +73,7 @@ Some presses rely on a different logic:
 - `ThinKPress` ([source](kvpress/presses/think_press.py), [paper](https://arxiv.org/pdf/2407.21018)): compress the dimensions of the keys based on the channel attention score on the last queries 
 - `SimLayerKVPress` ([source](kvpress/presses/simlayerkv_press.py), [paper](https://arxiv.org/abs/2410.13846)): identify "lazy" layers, and apply the StreamingLLM approach to them 
 - `DuoAttentionPress` ([source](kvpress/presses/duo_attention_press.py), [paper](https://arxiv.org/abs/2410.10819)): split heads into retrieval heads (no compression) and streaming heads (StreamingLLM approach)
-- `FinchPress` (([source](kvpress/presses/finch_press.py)), [paper](https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00716/125280)): similar to SnapKV with a dynamic window size and key value re-rotation
+- `FinchPress` ([source](kvpress/presses/finch_press.py), [paper](https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00716/125280)): similar to SnapKV with a dynamic window size and key value re-rotation
 
 Finally we provide wrapper presses that can be combined with other presses:
 - `AdaKVPress` ([source](kvpress/presses/adakv_press.py), [paper](https://arxiv.org/abs/2407.11550)): prune bottom scores of any `ScorerPress` but across all heads, achieving head-wise compressions