diff --git a/tests/models/language/pooling/test_bge_m3.py b/tests/models/language/pooling/test_bge_m3.py
index 5ad1fee03..2c0c0de34 100644
--- a/tests/models/language/pooling/test_bge_m3.py
+++ b/tests/models/language/pooling/test_bge_m3.py
@@ -136,6 +136,16 @@ async def test_bge_m3_api_server_sparse_embedding(client: openai.AsyncOpenAI):
     )
 
 
+@pytest.mark.asyncio
+async def test_bge_m3_api_server_sparse_embedding_corner_case(
+    client: openai.AsyncOpenAI,
+):
+    embeddings = await sparse_embeddings(client, ["Hi"])
+    assert len(embeddings) == 1
+    assert 2673 in embeddings[0]
+    assert embeddings[0][2673] == pytest.approx(0.26710861921310425, rel=0.01)
+
+
 # https://github.com/FlagOpen/FlagEmbedding/blob/6fd176266f2382878bcc69cd656cff425d52f49b/FlagEmbedding/inference/embedder/encoder_only/m3.py#L163
 def colbert_score(q_reps: torch.Tensor, p_reps: torch.Tensor) -> torch.Tensor:
     token_scores = torch.einsum("in,jn->ij", q_reps, p_reps)
diff --git a/vllm/model_executor/layers/pooler/special.py b/vllm/model_executor/layers/pooler/special.py
index 707e7c907..bafa191db 100644
--- a/vllm/model_executor/layers/pooler/special.py
+++ b/vllm/model_executor/layers/pooler/special.py
@@ -165,7 +165,7 @@ class BOSEOSFilter(Pooler):
                 pooled_data = pooled_data[1:]
             if token_ids[-1] == self.eos_token_id:
                 pooled_data = pooled_data[:-1]
-            pooled_outputs[i] = pooled_data.squeeze()
+            pooled_outputs[i] = pooled_data.squeeze(-1)
 
         return pooled_outputs