diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
index 46ecc5b70..22fd82371 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
@@ -1501,4 +1501,28 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
                       binder.op, resultType, self, other);
                   return success();
                 });
+  patterns.onOp("Mish", 18,
+                [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+                  Torch::ValueTensorType resultType;
+                  Value input;
+                  if (binder.tensorOperand(input) ||
+                      binder.tensorResultType(resultType)) {
+                    return failure();
+                  }
+                  rewriter.replaceOpWithNewOp<Torch::AtenMishOp>(
+                      binder.op, resultType, input);
+                  return success();
+                });
+  patterns.onOp("HardSwish", 14,
+                [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+                  Torch::ValueTensorType resultType;
+                  Value input;
+                  if (binder.tensorOperand(input) ||
+                      binder.tensorResultType(resultType)) {
+                    return failure();
+                  }
+                  rewriter.replaceOpWithNewOp<Torch::AtenHardswishOp>(
+                      binder.op, resultType, input);
+                  return success();
+                });
 }
diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index b5e9162bc..9218f5376 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -2099,4 +2099,67 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
                       binder.op, resultType, operand);
                   return success();
                 });
+  patterns.onOp(
+      "Softplus", 1, [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+        Torch::ValueTensorType resultType;
+        Value input;
+        if (binder.tensorOperand(input) ||
+            binder.tensorResultType(resultType)) {
+          return failure();
+        }
+        // out = ln(exp(x) + 1)
+        Value exp = rewriter.create<Torch::AtenExpOp>(binder.getLoc(),
+                                                      resultType, input);
+        rewriter.replaceOpWithNewOp<Torch::AtenLog1pOp>(binder.op, resultType,
+                                                        exp);
+        return success();
+      });
+  patterns.onOp(
+      "Trilu", 14, [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+        Torch::ValueTensorType resultType;
+        Value input;
+        int64_t upper;
+        if (binder.tensorOperandAtIndex(input, 0) ||
+            binder.s64IntegerAttr(upper, "upper", 1) ||
+            binder.tensorResultType(resultType)) {
+          return failure();
+        }
+
+        Value diagonal;
+        if (binder.tensorOperandAtIndex(diagonal, 1)) {
+          diagonal = rewriter.create<Torch::ConstantIntOp>(
+              binder.getLoc(), rewriter.getI64IntegerAttr(0));
+        } else {
+          diagonal = rewriter.create<Torch::AtenItemOp>(
+              binder.getLoc(), rewriter.getType<Torch::IntType>(), diagonal);
+        }
+
+        if (upper) {
+          rewriter.replaceOpWithNewOp<Torch::AtenTriuOp>(binder.op, resultType,
+                                                         input, diagonal);
+          return success();
+        }
+        rewriter.replaceOpWithNewOp<Torch::AtenTrilOp>(binder.op, resultType,
+                                                       input, diagonal);
+        return success();
+      });
+  patterns.onOp("ThresholdedRelu", 10,
+                [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+                  Torch::ValueTensorType resultType;
+                  Value input;
+                  float alpha;
+                  if (binder.tensorOperand(input) ||
+                      binder.f32FloatAttr(alpha, "alpha", 1.0)) {
+                    return failure();
+                  }
+                  Value cstAlpha = rewriter.create<Torch::ConstantFloatOp>(
+                      binder.getLoc(), rewriter.getType<Torch::FloatType>(),
+                      rewriter.getFloatAttr(rewriter.getF64Type(), alpha));
+                  Value value = rewriter.create<Torch::ConstantFloatOp>(
+                      binder.getLoc(), rewriter.getType<Torch::FloatType>(),
+                      rewriter.getFloatAttr(rewriter.getF64Type(), 0.0));
+                  rewriter.replaceOpWithNewOp<Torch::AtenThresholdOp>(
+                      binder.op, resultType, input, cstAlpha, value);
+                  return success();
+                });
 }
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index 55b7d8883..9bbd115cd 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -1924,11 +1924,6 @@ ONNX_XFAIL_SET = {
     "EinsumStaticFourDimensionModule_basic",
     "EinsumStaticModule_basic",
 
-    # Failure - onnx_lowering: onnx.HardSwish
-    "HardswishModule_basic",
-    "HardswishRandomModule_basic",
-    "MobilenetV3Module_basic",
-
     # Failure - onnx_lowering: onnx.MaxPool
     "MaxPool2dWithIndicesAllNegativeValuesModule_basic",
     "MaxPool2dWithIndicesNonDefaultPaddingModule_basic",
@@ -2043,10 +2038,6 @@ ONNX_XFAIL_SET = {
     "CrossEntropyLossModule_basic",
     "CrossEntropyLossNoReductionModule_basic",
 
-    # Failure - onnx_lowering: onnx.Softplus
-    "ElementwiseMishModule_basic",
-    "SoftplusModule_basic",
-
     # Failure - onnx_lowering: onnx.Squeeze
     "SqueezeModule_allUnitDim",
     "SqueezeModule_broadcast",
@@ -2059,16 +2050,6 @@ ONNX_XFAIL_SET = {
     "SortTensorSpecificDimension_basic",
     "SortTensor_basic",
 
-    # Failure - onnx_lowering: onnx.Trilu
-    "AtenTrilModule_basic",
-    "AtenTrilWithNegDiagonalModule_basic",
-    "AtenTrilWithPosDiagonalModule_basic",
-    "AtenTriuModule_basic",
-    "AtenTriuWithNegDiagonalModule_basic",
-    "AtenTriuWithPosDiagonalModule_basic",
-    "TriuBroadcastModule_basic",
-    "TriuModule_basic",
-
     # Failure - incorrect dtype
     "ReduceMaxAlongDimUnsignedInt_basic",
 
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
index 46eda0496..3741e5c9f 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
@@ -912,3 +912,22 @@ func.func @test_not_2d(%arg0: !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],
     %0 = torch.operator "onnx.PRelu"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32>
     return %0 : !torch.vtensor<[3,4,5],f32>
   }
+
+// -----
+
+// CHECK-LABEL: func.func @test_mish
+func.func @test_mish(%arg0: !torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  %none = torch.constant.none
+  // CHECK: torch.aten.mish %arg0 : !torch.vtensor<[10000],f32> -> !torch.vtensor<[10000],f32>
+  %0 = torch.operator "onnx.Mish"(%arg0) : (!torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32>
+  return %0 : !torch.vtensor<[10000],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_hardswish
+func.func @test_hardswish(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: torch.aten.hardswish %arg0 : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
+  %0 = torch.operator "onnx.HardSwish"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32>
+  return %0 : !torch.vtensor<[3,4,5],f32>
+}
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 508ed55d3..dc652bff9 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -1664,3 +1664,102 @@ func.func @test_size(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],si
   return %0 : !torch.vtensor<[],si32>
 }
 
+// -----
+
+// CHECK-LABEL: func.func @test_softplus
+func.func @test_softplus(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[EXP:.*]] = torch.aten.exp %arg0 : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
+  // CHECK: torch.aten.log1p %[[EXP]] : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
+  %0 = torch.operator "onnx.Softplus"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32>
+  return %0 : !torch.vtensor<[3],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_tril
+func.func @test_tril(%arg0: !torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.constant.int 0
+  // CHECK: torch.aten.tril %arg0, %[[DIAGONAL]] : !torch.vtensor<[4,5],si64>, !torch.int -> !torch.vtensor<[4,5],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64>
+  return %0 : !torch.vtensor<[4,5],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_tril_neg
+func.func @test_tril_neg(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.aten.item %arg1 : !torch.vtensor<[],si64> -> !torch.int
+  // CHECK: torch.aten.tril %arg0, %[[DIAGONAL]] : !torch.vtensor<[4,5],si64>, !torch.int -> !torch.vtensor<[4,5],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64>
+  return %0 : !torch.vtensor<[4,5],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_tril_one_row_neg
+func.func @test_tril_one_row_neg(%arg0: !torch.vtensor<[3,1,5],si64>) -> !torch.vtensor<[3,1,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.constant.int 0
+  // CHECK: torch.aten.tril %arg0, %[[DIAGONAL]] : !torch.vtensor<[3,1,5],si64>, !torch.int -> !torch.vtensor<[3,1,5],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[3,1,5],si64>) -> !torch.vtensor<[3,1,5],si64>
+  return %0 : !torch.vtensor<[3,1,5],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_tril_square
+func.func @test_tril_square(%arg0: !torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.constant.int 0
+  // CHECK: torch.aten.tril %arg0, %[[DIAGONAL]] : !torch.vtensor<[2,3,3],si64>, !torch.int -> !torch.vtensor<[2,3,3],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64>
+  return %0 : !torch.vtensor<[2,3,3],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_tril_zero
+func.func @test_tril_zero(%arg0: !torch.vtensor<[3,0,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[3,0,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.aten.item %arg1 : !torch.vtensor<[],si64> -> !torch.int
+  // CHECK: torch.aten.tril %arg0, %[[DIAGONAL]] : !torch.vtensor<[3,0,5],si64>, !torch.int -> !torch.vtensor<[3,0,5],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[3,0,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[3,0,5],si64>
+  return %0 : !torch.vtensor<[3,0,5],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_triu
+func.func @test_triu(%arg0: !torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.constant.int 0
+  // CHECK: torch.aten.triu %arg0, %[[DIAGONAL]] : !torch.vtensor<[4,5],si64>, !torch.int -> !torch.vtensor<[4,5],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0) : (!torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64>
+  return %0 : !torch.vtensor<[4,5],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_triu_one_row
+func.func @test_triu_one_row(%arg0: !torch.vtensor<[3,1,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[3,1,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.aten.item %arg1 : !torch.vtensor<[],si64> -> !torch.int
+  // CHECK: torch.aten.triu %arg0, %[[DIAGONAL]] : !torch.vtensor<[3,1,5],si64>, !torch.int -> !torch.vtensor<[3,1,5],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[3,1,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[3,1,5],si64>
+  return %0 : !torch.vtensor<[3,1,5],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_triu_square
+func.func @test_triu_square(%arg0: !torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.constant.int 0
+  // CHECK: torch.aten.triu %arg0, %[[DIAGONAL]] : !torch.vtensor<[2,3,3],si64>, !torch.int -> !torch.vtensor<[2,3,3],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0) : (!torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64>
+  return %0 : !torch.vtensor<[2,3,3],si64>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_triu_zero
+func.func @test_triu_zero(%arg0: !torch.vtensor<[0,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[0,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[DIAGONAL:.*]] = torch.aten.item %arg1 : !torch.vtensor<[],si64> -> !torch.int
+  // CHECK: torch.aten.triu %arg0, %[[DIAGONAL]] : !torch.vtensor<[0,5],si64>, !torch.int -> !torch.vtensor<[0,5],si64>
+  %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[0,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[0,5],si64>
+  return %0 : !torch.vtensor<[0,5],si64>
+}