diff --git a/tests/eval/test_token_positions.py b/tests/eval/test_token_positions.py
index 826e7c04..c584b931 100644
--- a/tests/eval/test_token_positions.py
+++ b/tests/eval/test_token_positions.py
@@ -13,7 +13,7 @@ def mock_data():
         {"tokens": [[1, 2, 3], [4, 5, 6], [7, 8, 9]]}
     ).with_format("torch")
     selected_tokens = [2, 4, 6, 8]
-    metrics = torch.tensor([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]])
+    metrics = torch.tensor([[-1, 0.45, -0.33], [-1.31, 2.3, 0.6], [0.2, 0.8, 0.1]])
     return token_ids, selected_tokens, metrics
 
 
@@ -26,19 +26,29 @@ def test_get_all_tok_metrics_in_label(mock_data):
     )
     # key: (prompt_pos, tok_pos), value: logprob
     expected = {
-        (0, 1): 0.2,
-        (1, 0): 0.4,
+        (0, 1): 0.45,
+        (1, 0): -1.31,
         (1, 2): 0.6,
         (2, 1): 0.8,
     }
-    # use isclose to compare floating point numbers
+
+    # compare keys
+    assert result.keys() == expected.keys()
+    # compare values
     for k in result:
         assert isclose(cast(float, result[k]), expected[k], rel_tol=1e-6)  # type: ignore
 
     # test with quantile filtering
     result_q = get_all_tok_metrics_in_label(
-        token_ids["tokens"], selected_tokens, metrics, q_start=0.3, q_end=1.0
+        token_ids["tokens"], selected_tokens, metrics, q_start=0.6, q_end=1.0
     )
-    expected_q = {(1, 2): 0.6, (2, 1): 0.8, (1, 0): 0.4}
+    expected_q = {
+        (1, 2): 0.6,
+        (2, 1): 0.8,
+    }
+
+    # compare keys
+    assert result_q.keys() == expected_q.keys()
+    # compare values
     for k in result_q:
         assert isclose(cast(float, result_q[k]), expected_q[k], rel_tol=1e-6)  # type: ignore
diff --git a/tests/eval/test_utils.py b/tests/eval/test_utils.py
index ad0f54b8..a259d16b 100644
--- a/tests/eval/test_utils.py
+++ b/tests/eval/test_utils.py
@@ -61,7 +61,22 @@ def test_load_validation_dataset():
 def test_dict_filter_quantile():
     d = {1: 0.1, 2: 0.2, 3: 0.3, 4: 0.4, 5: 0.5}
     result = dict_filter_quantile(d, 0.2, 0.6)
-    expected = {2: 0.2, 3: 0.3, 4: 0.4}
+    expected = {2: 0.2, 3: 0.3}
+
+    # compare keys
+    assert result.keys() == expected.keys()
+    # compare values
+    for k in result:
+        assert isclose(result[k], expected[k], rel_tol=1e-6)
+
+    # test with negative values
+    d = {1: -0.1, 2: -0.2, 3: -0.3, 4: -0.4, 5: -0.5}
+    result = dict_filter_quantile(d, 0.2, 0.6)
+    expected = {3: -0.3, 4: -0.4}
+
+    # compare keys
+    assert result.keys() == expected.keys()
+    # compare values
     for k in result:
         assert isclose(result[k], expected[k], rel_tol=1e-6)