diff --git a/mlir/lib/Dialect/SCF/Transforms/TileUsingInterface.cpp b/mlir/lib/Dialect/SCF/Transforms/TileUsingInterface.cpp
index 926ebb1a2cea87..ba44e5674fb21f 100644
--- a/mlir/lib/Dialect/SCF/Transforms/TileUsingInterface.cpp
+++ b/mlir/lib/Dialect/SCF/Transforms/TileUsingInterface.cpp
@@ -1536,6 +1536,12 @@ mlir::scf::tileConsumerAndFuseProducersUsingSCF(
       tiledAndFusedOps.insert(tiledAndFusedOp);
     }
 
+    // Drop the extract_slice if it has been replaced by the tiled producer, and
+    // is no longer used.
+    if (worklistItem.candidateSlice->use_empty()) {
+      rewriter.eraseOp(worklistItem.candidateSlice);
+    }
+
     if (failed(sliceTracker.insertAndApplyPatterns(worklistCandidates))) {
       return rewriter.notifyMatchFailure(consumer, "cleanup patterns failed");
     }
diff --git a/mlir/test/Dialect/Linalg/transform-op-fuse-into-containing.mlir b/mlir/test/Dialect/Linalg/transform-op-fuse-into-containing.mlir
index 4115f2857a20c6..2cea815ac2b047 100644
--- a/mlir/test/Dialect/Linalg/transform-op-fuse-into-containing.mlir
+++ b/mlir/test/Dialect/Linalg/transform-op-fuse-into-containing.mlir
@@ -651,6 +651,46 @@ module {
   }
 }
 
+// -----
+
+// This test checks that upon tiling and fusion, Linalg ops that have been tiled
+// through fusion and are not used elsewhere are indeed dead code and get
+// dropped.
+
+// CHECK-LABEL: func @tile_fuse_drop_dead_producer(
+// CHECK-SAME:    %[[TA:[0-9a-z]+]]: tensor<10x10xf32>) -> tensor<10x10xf32> {
+func.func @tile_fuse_drop_dead_producer(%arg0: tensor<10x10xf32>) -> tensor<10x10xf32> {
+  %c2f = arith.constant 2.0 : f32
+
+  // CHECK-NOT: linalg.generic {{{[^\}]*}}} ins(%[[TA]] : tensor<10x10xf32>) outs(%{{.*}} : tensor<10x10xf32>) {
+  %empty = tensor.empty() : tensor<10x10xf32>
+  %0 = linalg.generic {indexing_maps = [affine_map<(i, j) -> (i, j)>, affine_map<(i, j) -> (i, j)>], iterator_types = ["parallel", "parallel"]}
+       ins(%arg0: tensor<10x10xf32>) outs(%empty: tensor<10x10xf32>) {
+  ^bb0(%a: f32, %b: f32):
+    %res = arith.addf %a, %c2f : f32
+    linalg.yield %res : f32
+  } -> tensor<10x10xf32>
+
+  %empty2 = tensor.empty() : tensor<10x10xf32>
+  // CHECK: scf.for {{.*}} {
+  // CHECK: scf.for {{.*}} {
+  // CHECK: linalg.generic
+  // CHECK: linalg.negf
+  // CHECK: }
+  // CHECK: }
+  %1 = linalg.negf ins(%0 : tensor<10x10xf32>) outs(%empty2 : tensor<10x10xf32>) -> tensor<10x10xf32>
+
+  return %1 : tensor<10x10xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.negf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %tiled_low, %loop1, %loop2 = transform.structured.fuse %0 [5, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
 
 ////////////////////////////////////////////////////////////////////////////////
 // Tests below are expected to fail.