diff --git a/mlir/lib/Dialect/SparseTensor/Pipelines/SparseTensorPipelines.cpp b/mlir/lib/Dialect/SparseTensor/Pipelines/SparseTensorPipelines.cpp
--- a/mlir/lib/Dialect/SparseTensor/Pipelines/SparseTensorPipelines.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Pipelines/SparseTensorPipelines.cpp
@@ -9,6 +9,7 @@
 #include "mlir/Dialect/SparseTensor/Pipelines/Passes.h"
 
 #include "mlir/Conversion/Passes.h"
+#include "mlir/Dialect/Arithmetic/Transforms/Passes.h"
 #include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
 #include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
 #include "mlir/Dialect/Bufferization/Transforms/Passes.h"
@@ -73,6 +74,8 @@
   pm.addPass(createConvertVectorToLLVMPass(options.lowerVectorToLLVMOptions()));
   pm.addPass(createMemRefToLLVMPass());
   pm.addNestedPass<func::FuncOp>(createConvertComplexToStandardPass());
+  pm.addNestedPass<mlir::func::FuncOp>(
+      mlir::arith::createArithmeticExpandOpsPass());
   pm.addNestedPass<func::FuncOp>(createConvertMathToLLVMPass());
   pm.addPass(createConvertMathToLibmPass());
   pm.addPass(createConvertComplexToLibmPass());
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
@@ -43,27 +43,26 @@
 module {
   // Creates a new sparse vector using the minimum values from two input sparse vectors.
   // When there is no overlap, include the present value in the output.
-  func.func @vector_min(%arga: tensor<?xf64, #SparseVector>,
-                        %argb: tensor<?xf64, #SparseVector>) -> tensor<?xf64, #SparseVector> {
+  func.func @vector_min(%arga: tensor<?xi32, #SparseVector>,
+                        %argb: tensor<?xi32, #SparseVector>) -> tensor<?xi32, #SparseVector> {
     %c = arith.constant 0 : index
-    %d = tensor.dim %arga, %c : tensor<?xf64, #SparseVector>
-    %xv = bufferization.alloc_tensor(%d) : tensor<?xf64, #SparseVector>
+    %d = tensor.dim %arga, %c : tensor<?xi32, #SparseVector>
+    %xv = bufferization.alloc_tensor(%d) : tensor<?xi32, #SparseVector>
     %0 = linalg.generic #trait_vec_op
-       ins(%arga, %argb: tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>)
-        outs(%xv: tensor<?xf64, #SparseVector>) {
-        ^bb(%a: f64, %b: f64, %x: f64):
-          %1 = sparse_tensor.binary %a, %b : f64, f64 to f64
+       ins(%arga, %argb: tensor<?xi32, #SparseVector>, tensor<?xi32, #SparseVector>)
+        outs(%xv: tensor<?xi32, #SparseVector>) {
+        ^bb(%a: i32, %b: i32, %x: i32):
+          %1 = sparse_tensor.binary %a, %b : i32, i32 to i32
             overlap={
-              ^bb0(%a0: f64, %b0: f64):
-                %cmp = arith.cmpf "olt", %a0, %b0 : f64
-                %2 = arith.select %cmp, %a0, %b0: f64
-                sparse_tensor.yield %2 : f64
+              ^bb0(%a0: i32, %b0: i32):
+                %2 = arith.minsi %a0, %b0: i32
+                sparse_tensor.yield %2 : i32
             }
             left=identity
             right=identity
-          linalg.yield %1 : f64
-    } -> tensor<?xf64, #SparseVector>
-    return %0 : tensor<?xf64, #SparseVector>
+          linalg.yield %1 : i32
+    } -> tensor<?xi32, #SparseVector>
+    return %0 : tensor<?xi32, #SparseVector>
   }
 
   // Creates a new sparse vector by multiplying a sparse vector with a dense vector.
@@ -428,8 +427,13 @@
       [0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 0., 1., 2., 3., 4., 5., 6., 7., 8., 9.,
        0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 0., 1.]
     > : tensor<32xf64>
+    %v1_si = arith.fptosi %v1 : tensor<32xf64> to tensor<32xi32>
+    %v2_si = arith.fptosi %v2 : tensor<32xf64> to tensor<32xi32>
+
     %sv1 = sparse_tensor.convert %v1 : tensor<32xf64> to tensor<?xf64, #SparseVector>
     %sv2 = sparse_tensor.convert %v2 : tensor<32xf64> to tensor<?xf64, #SparseVector>
+    %sv1_si = sparse_tensor.convert %v1_si : tensor<32xi32> to tensor<?xi32, #SparseVector>
+    %sv2_si = sparse_tensor.convert %v2_si : tensor<32xi32> to tensor<?xi32, #SparseVector>
     %dv3 = tensor.cast %v3 : tensor<32xf64> to tensor<?xf64>
 
     // Setup sparse matrices.
@@ -459,9 +463,9 @@
     %sm4 = sparse_tensor.convert %m4 : tensor<4x4xf64> to tensor<4x4xf64, #DCSR>
 
     // Call sparse vector kernels.
-    %0 = call @vector_min(%sv1, %sv2)
-       : (tensor<?xf64, #SparseVector>,
-          tensor<?xf64, #SparseVector>) -> tensor<?xf64, #SparseVector>
+    %0 = call @vector_min(%sv1_si, %sv2_si)
+       : (tensor<?xi32, #SparseVector>,
+          tensor<?xi32, #SparseVector>) -> tensor<?xi32, #SparseVector>
     %1 = call @vector_mul(%sv1, %dv3)
       : (tensor<?xf64, #SparseVector>,
          tensor<?xf64>) -> tensor<?xf64, #SparseVector>
@@ -494,7 +498,7 @@
     // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9 )
     // CHECK-NEXT: ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, -1, -1, -1, -1, -1, -1 )
     // CHECK-NEXT: ( 0, 11, 0, 12, 13, 0, 0, 0, 0, 0, 14, 0, 0, 0, 0, 0, 15, 0, 16, 0, 0, 17, 0, 0, 0, 0, 0, 0, 18, 19, 0, 20 )
-    // CHECK-NEXT: ( 1, 11, 2, 13, 14, 3, 15, 4, 16, 5, 6, 7, 8, 9, -1, -1 )
+    // CHECK-NEXT: ( 1, 11, 2, 13, 14, 3, 15, 4, 16, 5, 6, 7, 8, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 )
     // CHECK-NEXT: ( 1, 11, 0, 2, 13, 0, 0, 0, 0, 0, 14, 3, 0, 0, 0, 0, 15, 4, 16, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9 )
     // CHECK-NEXT: ( 0, 6, 3, 28, 0, 6, 56, 72, 9, -1, -1, -1, -1, -1, -1, -1 )
     // CHECK-NEXT: ( 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 28, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 56, 72, 0, 9 )
@@ -518,7 +522,7 @@
     //
     call @dump_vec(%sv1) : (tensor<?xf64, #SparseVector>) -> ()
     call @dump_vec(%sv2) : (tensor<?xf64, #SparseVector>) -> ()
-    call @dump_vec(%0) : (tensor<?xf64, #SparseVector>) -> ()
+    call @dump_vec_i32(%0) : (tensor<?xi32, #SparseVector>) -> ()
     call @dump_vec(%1) : (tensor<?xf64, #SparseVector>) -> ()
     call @dump_vec(%2) : (tensor<?xf64, #SparseVector>) -> ()
     call @dump_vec_i32(%3) : (tensor<?xi32, #SparseVector>) -> ()
@@ -537,7 +541,7 @@
     bufferization.dealloc_tensor %sm2 : tensor<?x?xf64, #DCSR>
     bufferization.dealloc_tensor %sm3 : tensor<4x4xf64, #DCSR>
     bufferization.dealloc_tensor %sm4 : tensor<4x4xf64, #DCSR>
-    bufferization.dealloc_tensor %0 : tensor<?xf64, #SparseVector>
+    bufferization.dealloc_tensor %0 : tensor<?xi32, #SparseVector>
     bufferization.dealloc_tensor %1 : tensor<?xf64, #SparseVector>
     bufferization.dealloc_tensor %2 : tensor<?xf64, #SparseVector>
     bufferization.dealloc_tensor %3 : tensor<?xi32, #SparseVector>