diff --git a/compiler/plugins/input/Torch/InputConversion/BindSymbolicShapes.cpp b/compiler/plugins/input/Torch/InputConversion/BindSymbolicShapes.cpp
index f8e13f2fa0e8..f1b0793b5b91 100644
--- a/compiler/plugins/input/Torch/InputConversion/BindSymbolicShapes.cpp
+++ b/compiler/plugins/input/Torch/InputConversion/BindSymbolicShapes.cpp
@@ -281,11 +281,11 @@ class BindSymbolicShapesPass final
         case AffineExprKind::Mul:
           return builder.create<arith::MulIOp>(loc, lhs, rhs);
         case AffineExprKind::Mod:
-          return builder.create<arith::RemUIOp>(loc, lhs, rhs);
+          return builder.create<arith::RemSIOp>(loc, lhs, rhs);
         case AffineExprKind::FloorDiv:
-          return builder.create<arith::DivUIOp>(loc, lhs, rhs);
+          return builder.create<arith::DivSIOp>(loc, lhs, rhs);
         case AffineExprKind::CeilDiv:
-          return builder.create<arith::CeilDivUIOp>(loc, lhs, rhs);
+          return builder.create<arith::CeilDivSIOp>(loc, lhs, rhs);
         default:
           break;
         }
diff --git a/compiler/plugins/input/Torch/InputConversion/test/bind_symbolic_shapes.mlir b/compiler/plugins/input/Torch/InputConversion/test/bind_symbolic_shapes.mlir
index 699b6dbf6d60..335ca3056a1c 100644
--- a/compiler/plugins/input/Torch/InputConversion/test/bind_symbolic_shapes.mlir
+++ b/compiler/plugins/input/Torch/InputConversion/test/bind_symbolic_shapes.mlir
@@ -113,8 +113,8 @@ module @add_expr {
 // CHECK-LABEL: @mod_expr
 module @mod_expr {
   func.func @main(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torch.vtensor<[?,?],f32>) {
-    // CHECK: remui
-    // CHECK-NOT: udiv
+    // CHECK: remsi
+    // CHECK-NOT: sdiv
     %0 = torch.symbolic_int "s0" {min_val = 0, max_val = 1024} : !torch.int
     %1 = torch.symbolic_int "s1" {min_val = 0, max_val = 1024} : !torch.int
     torch.bind_symbolic_shape %arg0, [%0, %1], affine_map<()[s0, s1] -> (s0, s1)> : !torch.vtensor<[?,?],f32>
@@ -127,8 +127,8 @@ module @mod_expr {
 // CHECK-LABEL: @floordiv_expr
 module @floordiv_expr {
   func.func @main(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torch.vtensor<[?,?],f32>) {
-    // CHECK: divui
-    // CHECK-NOT: udiv
+    // CHECK: divsi
+    // CHECK-NOT: sdiv
     %0 = torch.symbolic_int "s0" {min_val = 0, max_val = 1024} : !torch.int
     %1 = torch.symbolic_int "s1" {min_val = 0, max_val = 1024} : !torch.int
     torch.bind_symbolic_shape %arg0, [%0, %1], affine_map<()[s0, s1] -> (s0, s1)> : !torch.vtensor<[?,?],f32>
diff --git a/compiler/src/iree/compiler/Codegen/Common/test/block_dynamic_dims.mlir b/compiler/src/iree/compiler/Codegen/Common/test/block_dynamic_dims.mlir
index 7f252f25e882..7cfcd54af84b 100644
--- a/compiler/src/iree/compiler/Codegen/Common/test/block_dynamic_dims.mlir
+++ b/compiler/src/iree/compiler/Codegen/Common/test/block_dynamic_dims.mlir
@@ -66,11 +66,11 @@ func.func @block_attention_dims() {
 //   CHECK-DAG:   %[[C16:.+]] = arith.constant 16 : index
 //   CHECK-DAG:   %[[M:.+]] = flow.dispatch.workload.ordinal %{{.+}}, 0 : index
 //   CHECK-DAG:   %[[K2:.+]] = flow.dispatch.workload.ordinal %{{.+}}, 1 : index
-//   CHECK-DAG:   %[[M_DYNAMIC:.+]] = arith.divui %[[M]], %[[C16]]
+//   CHECK-DAG:   %[[M_DYNAMIC:.+]] = arith.divsi %[[M]], %[[C16]]
 //       CHECK:   %[[Q_BINDING:.+]] = hal.interface.binding.subspan
 //  CHECK-SAME:       binding(0)
 //  CHECK-SAME:       !flow.dispatch.tensor<readonly:tensor<4x?x16x32x128xf16>>{%[[M_DYNAMIC]]}
-//       CHECK:   %[[K2_DYNAMIC:.+]] = arith.divui %[[K2]], %[[C32]]
+//       CHECK:   %[[K2_DYNAMIC:.+]] = arith.divsi %[[K2]], %[[C32]]
 //       CHECK:   %[[K_BINDING:.+]] = hal.interface.binding.subspan
 //  CHECK-SAME:       binding(1)
 //  CHECK-SAME:       !flow.dispatch.tensor<readonly:tensor<4x?x32x32x128xf16>>{%[[K2_DYNAMIC]]}
diff --git a/compiler/src/iree/compiler/Codegen/Common/test/propagate_reshapes_by_expansion.mlir b/compiler/src/iree/compiler/Codegen/Common/test/propagate_reshapes_by_expansion.mlir
index abced1727ced..db715dea9d07 100644
--- a/compiler/src/iree/compiler/Codegen/Common/test/propagate_reshapes_by_expansion.mlir
+++ b/compiler/src/iree/compiler/Codegen/Common/test/propagate_reshapes_by_expansion.mlir
@@ -57,7 +57,7 @@ func.func @fold_expand_into_loads_dynamic() -> tensor<2x?x16x32xf32> {
 // CHECK-LABEL: func @fold_expand_into_loads_dynamic()
 //   CHECK-DAG:   %[[C16:.+]] = arith.constant 16 : index
 //   CHECK-DAG:   %[[CONST:.+]] = hal.interface.constant.load
-//       CHECK:   %[[SHAPE:.+]] = arith.divui %[[CONST]], %[[C16]]
+//       CHECK:   %[[SHAPE:.+]] = arith.divsi %[[CONST]], %[[C16]]
 //       CHECK:   %[[SUBSPAN:.+]] = hal.interface.binding.subspan
 //  CHECK-SAME:       !flow.dispatch.tensor<readonly:tensor<2x?x16x32xf32>>{%[[SHAPE]]}
 //       CHECK:   %[[LOAD:.+]] = flow.dispatch.tensor.load %[[SUBSPAN]]
@@ -81,7 +81,7 @@ func.func @fold_collapse_into_stores_dynamic(%arg0 : tensor<2x?x32xf32>) {
 // CHECK-LABEL: func @fold_collapse_into_stores_dynamic(
 //   CHECK-DAG:   %[[C2:.+]] = arith.constant 2 : index
 //       CHECK:   %[[CONST:.+]] = hal.interface.constant.load
-//       CHECK:   %[[SHAPE:.+]] = arith.divui %[[CONST]], %[[C2]]
+//       CHECK:   %[[SHAPE:.+]] = arith.divsi %[[CONST]], %[[C2]]
 //       CHECK:   %[[SUBSPAN:.+]] = hal.interface.binding.subspan
 //  CHECK-SAME:       !flow.dispatch.tensor<writeonly:tensor<2x?x32xf32>>{%[[SHAPE]]}
 //       CHECK:   flow.dispatch.tensor.store %{{.+}}, %[[SUBSPAN]]
diff --git a/compiler/src/iree/compiler/DispatchCreation/test/attention_fuse_by_expansion.mlir b/compiler/src/iree/compiler/DispatchCreation/test/attention_fuse_by_expansion.mlir
index 247fc7ea5cda..0367d2c386c5 100644
--- a/compiler/src/iree/compiler/DispatchCreation/test/attention_fuse_by_expansion.mlir
+++ b/compiler/src/iree/compiler/DispatchCreation/test/attention_fuse_by_expansion.mlir
@@ -197,18 +197,17 @@ util.func public @attention_dynamic(%arg0: tensor<?x?x?xf16>, %arg1: tensor<?x?x
 //  CHECK-DAG:   %[[D1:.+]] = tensor.dim %[[ARG0]], %[[C1]]
 //  CHECK-DAG:   %[[D2:.+]] = tensor.dim %[[ARG0]], %[[C2]]
 //  CHECK-DAG:   %[[D4:.+]] = tensor.dim %[[ARG2]], %[[C2]]
-//  CHECK-DAG:   %[[SPLIT0:.+]] = arith.divui %[[D0]]
-//  CHECK-DAG:   %[[VAL:.+]] = affine.apply affine_map<()[s0] -> (s0 floordiv 2)>()[%[[D0]]]
-//  CHECK-DAG:   %[[EMPTY:.+]] = tensor.empty(%[[VAL]], %[[D1]], %[[D4]]) : tensor<2x?x?x?xf16>
+//  CHECK-DAG:   %[[SPLIT0:.+]] = arith.divsi %[[D0]]
+//  CHECK-DAG:   %[[EMPTY:.+]] = tensor.empty(%[[SPLIT0]], %[[D1]], %[[D4]]) : tensor<2x?x?x?xf16>
 //  CHECK-DAG:   %[[QUERY:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1], [2], [3]{{\]}} output_shape [2, %[[SPLIT0]], %[[D1]], %[[D2]]]
 //  CHECK-DAG:   %[[D5:.+]] = tensor.dim %[[ARG1]], %[[C0]]
 //  CHECK-DAG:   %[[D6:.+]] = tensor.dim %[[ARG1]], %[[C1]]
 //  CHECK-DAG:   %[[D7:.+]] = tensor.dim %[[ARG1]], %[[C2]]
-//  CHECK-DAG:   %[[SPLIT1:.+]] = arith.divui %[[D5]], %[[C2]]
+//  CHECK-DAG:   %[[SPLIT1:.+]] = arith.divsi %[[D5]], %[[C2]]
 //  CHECK-DAG:   %[[KEY:.+]] = tensor.expand_shape %[[ARG1]] {{\[}}[0, 1], [2], [3]{{\]}} output_shape [2, %[[SPLIT1]], %[[D6]], %[[D7]]]
 //  CHECK-DAG:   %[[D8:.+]] = tensor.dim %[[ARG2]], %[[C0]]
 //  CHECK-DAG:   %[[D9:.+]] = tensor.dim %[[ARG2]], %[[C1]]
-//  CHECK-DAG:   %[[SPLIT2:.+]] = arith.divui %[[D8]], %[[C2]]
+//  CHECK-DAG:   %[[SPLIT2:.+]] = arith.divsi %[[D8]], %[[C2]]
 //  CHECK-DAG:   %[[CACHE:.+]] = tensor.expand_shape %[[ARG2]] {{\[}}[0, 1], [2], [3]{{\]}} output_shape [2, %[[SPLIT2]], %[[D9]], %[[D4]]]
 //      CHECK:   %[[ATTENTION:.+]] = iree_linalg_ext.attention
 //  CHECK-SAME:       indexing_maps =
@@ -263,23 +262,22 @@ util.func public @attention_dynamic_masked(%arg0: tensor<?x?x?xf16>, %arg1: tens
 //  CHECK-DAG:   %[[D1:.+]] = tensor.dim %[[ARG0]], %[[C1]]
 //  CHECK-DAG:   %[[D2:.+]] = tensor.dim %[[ARG0]], %[[C2]]
 //  CHECK-DAG:   %[[D4:.+]] = tensor.dim %[[ARG2]], %[[C2]]
-//  CHECK-DAG:   %[[SPLIT0:.+]] = arith.divui %[[D0]]
-//  CHECK-DAG:   %[[VAL:.+]] = affine.apply affine_map<()[s0] -> (s0 floordiv 2)>()[%[[D0]]]
-//  CHECK-DAG:   %[[EMPTY:.+]] = tensor.empty(%[[VAL]], %[[D1]], %[[D4]]) : tensor<2x?x?x?xf16>
+//  CHECK-DAG:   %[[SPLIT0:.+]] = arith.divsi %[[D0]]
+//  CHECK-DAG:   %[[EMPTY:.+]] = tensor.empty(%[[SPLIT0]], %[[D1]], %[[D4]]) : tensor<2x?x?x?xf16>
 //  CHECK-DAG:   %[[QUERY:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1], [2], [3]{{\]}} output_shape [2, %[[SPLIT0]], %[[D1]], %[[D2]]]
 //  CHECK-DAG:   %[[D5:.+]] = tensor.dim %[[ARG1]], %[[C0]]
 //  CHECK-DAG:   %[[D6:.+]] = tensor.dim %[[ARG1]], %[[C1]]
 //  CHECK-DAG:   %[[D7:.+]] = tensor.dim %[[ARG1]], %[[C2]]
-//  CHECK-DAG:   %[[SPLIT1:.+]] = arith.divui %[[D5]], %[[C2]]
+//  CHECK-DAG:   %[[SPLIT1:.+]] = arith.divsi %[[D5]], %[[C2]]
 //  CHECK-DAG:   %[[KEY:.+]] = tensor.expand_shape %[[ARG1]] {{\[}}[0, 1], [2], [3]{{\]}} output_shape [2, %[[SPLIT1]], %[[D6]], %[[D7]]]
 //  CHECK-DAG:   %[[D8:.+]] = tensor.dim %[[ARG2]], %[[C0]]
 //  CHECK-DAG:   %[[D9:.+]] = tensor.dim %[[ARG2]], %[[C1]]
-//  CHECK-DAG:   %[[SPLIT2:.+]] = arith.divui %[[D8]], %[[C2]]
+//  CHECK-DAG:   %[[SPLIT2:.+]] = arith.divsi %[[D8]], %[[C2]]
 //  CHECK-DAG:   %[[CACHE:.+]] = tensor.expand_shape %[[ARG2]] {{\[}}[0, 1], [2], [3]{{\]}} output_shape [2, %[[SPLIT2]], %[[D9]], %[[D4]]]
 //  CHECK-DAG:   %[[D10:.+]] = tensor.dim %[[ARG4]], %[[C0]]
 //  CHECK-DAG:   %[[D11:.+]] = tensor.dim %[[ARG4]], %[[C1]]
 //  CHECK-DAG:   %[[D12:.+]] = tensor.dim %[[ARG4]], %[[C2]]
-//  CHECK-DAG:   %[[SPLIT3:.+]] = arith.divui %[[D10]], %[[C2]]
+//  CHECK-DAG:   %[[SPLIT3:.+]] = arith.divsi %[[D10]], %[[C2]]
 //  CHECK-DAG:   %[[MASK:.+]] = tensor.expand_shape %[[ARG4]] {{\[}}[0, 1], [2], [3]{{\]}} output_shape [2, %[[SPLIT3]], %[[D11]], %[[D12]]]
 //      CHECK:   %[[ATTENTION:.+]] = iree_linalg_ext.attention
 //  CHECK-SAME:       indexing_maps =
diff --git a/compiler/src/iree/compiler/GlobalOptimization/test/linalg_quantized_conv_to_conv.mlir b/compiler/src/iree/compiler/GlobalOptimization/test/linalg_quantized_conv_to_conv.mlir
index d537f7c5308d..aa3f2c8b6e22 100644
--- a/compiler/src/iree/compiler/GlobalOptimization/test/linalg_quantized_conv_to_conv.mlir
+++ b/compiler/src/iree/compiler/GlobalOptimization/test/linalg_quantized_conv_to_conv.mlir
@@ -292,12 +292,12 @@ func.func @conv2d_all_dyn(%arg0: tensor<?x?x?x?xi8>, %arg1: tensor<?x?x?x?xi8>,
   // CHECK-SAME:  iterator_types = ["parallel", "parallel", "parallel", "reduction"]}
   // CHECK-SAME:  ins(%arg0 : tensor<?x?x?x?xi8>)
   // CHECK-SAME:  outs(%[[FILL]] : tensor<?x?x?xi32>)
+  // CHECK: %[[DIM00:.+]] = tensor.dim %arg0, %[[I0]]
   // CHECK: %[[EXPAND:.+]] = tensor.expand_shape %[[SUMI]] {{\[\[}}0], [1], [2, 3]]
 
-  // CHECK-DAG: %[[DIM0:.+]] = tensor.dim %arg0, %[[I0]]
   // CHECK-DAG: %[[DIM1:.+]] = tensor.dim %arg2, %[[I1]]
   // CHECK-DAG: %[[DIM2:.+]] = tensor.dim %arg2, %[[I2]]
-  // CHECK: %[[EMPTY:.+]] = tensor.empty(%[[DIM0]], %[[DIM1]], %[[DIM2]])
+  // CHECK: %[[EMPTY:.+]] = tensor.empty(%[[DIM00]], %[[DIM1]], %[[DIM2]])
   // CHECK: %[[FILL:.+]] = linalg.fill ins(%[[C0]] : i32) outs(%9 : tensor<?x?x?x1xi32>)
   // CHECK-DAG: %[[DIM0:.+]] = tensor.dim %arg1, %[[I0]] : tensor<?x?x?x?xi8>
   // CHECK-DAG: %[[DIM1:.+]] = tensor.dim %arg1, %[[I1]] : tensor<?x?x?x?xi8>
diff --git a/third_party/llvm-project b/third_party/llvm-project
index 47f99c8d32e7..6b1f50b29d70 160000
--- a/third_party/llvm-project
+++ b/third_party/llvm-project
@@ -1 +1 @@
-Subproject commit 47f99c8d32e71911d9d2a880bb66d8e98fa1b0cf
+Subproject commit 6b1f50b29d7084ca418e6c1ee5bf44030cf6b1ef