diff --git a/implicit/evaluation.pyx b/implicit/evaluation.pyx
index f25d0da..830e9c4 100644
--- a/implicit/evaluation.pyx
+++ b/implicit/evaluation.pyx
@@ -76,7 +76,7 @@ cdef _choose(rng, int n, float frac):
     return arr
 
 
-cdef _take_tails(arr, int n, return_complement=False, shuffled=False):
+cdef _take_tails(arr, int n, rng, return_complement=False, shuffled=False):
     """
     Given an array of (optionally shuffled) integers in the range 0->n, take the indices
     of the last 'n' occurrences of each integer (tail) -- subject to shuffling.
@@ -127,7 +127,7 @@ cdef _take_tails(arr, int n, return_complement=False, shuffled=False):
     ranges = np.linspace(start, end, num=n + 1, dtype=int)[1:]
 
     if shuffled:
-        shuffled_idx = (sorted_arr + np.random.random(arr.shape)).argsort()
+        shuffled_idx = (sorted_arr + rng.random(arr.shape)).argsort()
         tails = shuffled_idx[np.ravel(ranges, order="f")]
     else:
         tails = np.ravel(ranges, order="f")
@@ -206,7 +206,7 @@ cpdef leave_k_out_split(
     candidate_data = data[full_candidate_mask]
 
     test_idx, train_idx = _take_tails(
-        candidate_users, K, shuffled=True, return_complement=True
+        candidate_users, K, random_state, shuffled=True, return_complement=True
     )
 
     # get all remaining remaining candidate user-item pairs, and prepare to append to