diff --git a/externals/llvm-project b/externals/llvm-project
index 70e227a40..1e5f29af8 160000
--- a/externals/llvm-project
+++ b/externals/llvm-project
@@ -1 +1 @@
-Subproject commit 70e227a404e51f9248c7ad5d79953805b2afacb4
+Subproject commit 1e5f29af81a5f6fda308074f6345b9fba4faa71c
diff --git a/externals/stablehlo b/externals/stablehlo
index ab92adeda..c44d9af8d 160000
--- a/externals/stablehlo
+++ b/externals/stablehlo
@@ -1 +1 @@
-Subproject commit ab92adeda9119a6c3914cd42367b0a2b70765e91
+Subproject commit c44d9af8d4879adccf1054cb61a53377ae5898cb
diff --git a/lib/Conversion/TorchToStablehlo/GatherScatter.cpp b/lib/Conversion/TorchToStablehlo/GatherScatter.cpp
index 5854b1b7d..feae36f4f 100644
--- a/lib/Conversion/TorchToStablehlo/GatherScatter.cpp
+++ b/lib/Conversion/TorchToStablehlo/GatherScatter.cpp
@@ -101,6 +101,8 @@ Value gatherTensorAlongSingleAxis(PatternRewriter &rewriter, Operation *op,
       rewriter.getContext(),
       /*offsetDims=*/offsetDims,
       /*collapsedSliceDims=*/collapsedSliceDims,
+      /*operandBatchingDims=*/{},
+      /*startIndicesBatchingDims=*/{},
       /*startIndexMap=*/startIndexMap,
       /*indexVecDim=*/indexVecDim);
 
@@ -584,6 +586,8 @@ LogicalResult ConvertAtenOp<AtenGatherOp>::matchAndRewrite(
       rewriter.getContext(),
       /*offsetDims=*/{},
       /*collapsedSliceDims=*/collapsedDims,
+      /*operandBatchingDims=*/{},
+      /*startIndicesBatchingDims=*/{},
       /*startIndexMap=*/startIndexMap,
       /*indexVecDim=*/indexVecDim);
 
@@ -744,6 +748,8 @@ public:
         rewriter.getContext(),
         /*updateWindowDims=*/{},
         /*insertedWindowDims=*/insertedWindowDims,
+        /*inputBatchingDims=*/{},
+        /*scatterIndicesBatchingDims=*/{},
         /*scatterDimsToOperandDim=*/scatterDimOperandDimMap,
         /*indexVectorDim=*/indexVecDim);
 
@@ -826,6 +832,8 @@ LogicalResult ConvertAtenOp<AtenIndexTensorHackedTwinOp>::matchAndRewrite(
       rewriter.getContext(),
       /*offsetDims=*/offsetDims,
       /*collapsedSliceDims=*/collapsedDims,
+      /*operandBatchingDims=*/{},
+      /*startIndicesBatchingDims=*/{},
       /*startIndexMap=*/startIndexMap,
       /*indexVecDim=*/indexVecDim);
 
@@ -900,6 +908,8 @@ LogicalResult ConvertAtenOp<AtenIndexPutHackedTwinOp>::matchAndRewrite(
       rewriter.getContext(),
       /*updateWindowDims=*/updateWindowDims,
       /*insertedWindowDims=*/insertedWindowDims,
+      /*inputBatchingDims=*/{},
+      /*scatterIndicesBatchingDims=*/{},
       /*scatterDimsToOperandDim=*/scatterDimOperandDimMap,
       /*indexVectorDim=*/indexVecDim);
 
diff --git a/lib/Conversion/TorchToStablehlo/ViewLike.cpp b/lib/Conversion/TorchToStablehlo/ViewLike.cpp
index 04952d843..5bb83d098 100644
--- a/lib/Conversion/TorchToStablehlo/ViewLike.cpp
+++ b/lib/Conversion/TorchToStablehlo/ViewLike.cpp
@@ -172,6 +172,7 @@ public:
     if (!rankType)
       return op.emitError("Only ranked tensor types are currently supported");
 
+    // collect Value of dims
     SmallVector<Value, 4> dimSizes;
     if (!getAtenViewOpSizes(op, adaptor, rewriter, dimSizes)) {
       return op.emitError("Dims size must be a list of Scalar");
@@ -187,6 +188,20 @@ public:
       return success();
     }
 
+    // collect constant dim size which == -1
+    SmallVector<size_t> negOneIndex;
+    for (size_t i = 0; i < dimSizes.size(); i++) {
+      int64_t dim;
+      if (matchPattern(dimSizes[i], m_TorchConstantInt(&dim))) {
+        if (dim == -1) {
+          negOneIndex.push_back(i);
+        }
+      }
+    }
+    if (negOneIndex.size() > 1) {
+      return op.emitError("Only support at most one -1 in view target dims");
+    }
+
     std::for_each(dimSizes.begin(), dimSizes.end(), [&](Value &dSize) {
       dSize = rewriter.create<ToI64Op>(loc, dSize).getResult();
       return dSize;
@@ -194,16 +209,29 @@ public:
 
     Value numel = rewriter.create<shape::NumElementsOp>(
         loc, rewriter.create<shape::ShapeOfOp>(loc, adaptor.getSelf()));
+    numel =
+        rewriter.create<arith::IndexCastOp>(loc, rewriter.getI64Type(), numel);
+
+    // note: assuming that -1 doesn't arise from dynamic value
+    if (negOneIndex.size() == 1) {
+      size_t index = negOneIndex[0];
+      Value realDim = numel;
+      for (size_t i = 0; i < dimSizes.size(); i++) {
+        if (i != index) {
+          realDim = rewriter.create<arith::DivUIOp>(loc, realDim, dimSizes[i]);
+        }
+      }
+      // update -1 to realDim
+      dimSizes[index] = realDim;
+    }
 
     Value stablehloShape =
         rewriter.create<tensor::FromElementsOp>(loc, dimSizes);
-    Value computedShape = rewriter.create<stablehlo::ComputeReshapeShapeOp>(
-        loc, stablehloShape.getType(), numel, stablehloShape);
     rewriter.replaceOpWithNewOp<stablehlo::DynamicReshapeOp>(
         op,
         OpConversionPattern<AtenOpT>::getTypeConverter()->convertType(
             op.getType()),
-        adaptor.getSelf(), computedShape);
+        adaptor.getSelf(), stablehloShape);
     return success();
   }
 
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index ab162ab94..c1a9bc26a 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -1449,6 +1449,13 @@ STABLEHLO_CRASHING_SET = {
 # Write the TOSA set as a "passing" set as it is very early in development
 # and very few tests work yet.
 TOSA_PASS_SET = {
+    "ElementwiseAddScalar_NumToTensorFloat_Module_basic",
+    "ElementwiseDivTensorFloatModule_basic",
+    "ElementwiseMulTensorFloatModule_basic",
+    "ElementwiseWhereScalarSelfStaticModule_basic",
+    "GroupNormModule_basic",
+    "GroupNormNoWeightAndBiasModule_basic",
+    "NativeGroupNormModule_basic",
     "AtenDotModule_basic",
     "ElementwiseFloatTensorGtIntScalarModule_basic",
     "ElementwiseLogSigmoidModule_basic",
@@ -1946,7 +1953,6 @@ MAKE_FX_TOSA_PASS_SET = (
     "Conv2dNoPaddingModule_basic",
     "Conv2dWithPaddingDilationStrideModule_basic",
     "Conv2dWithPaddingModule_basic",
-    "AtenInstanceNormModule_basic",
     # failed to legalize operation 'torch.operator'
     "ElementwisePreluModule_basic",
     "ElementwisePreluStaticModule_basic",
diff --git a/test/Conversion/TorchToStablehlo/view_like.mlir b/test/Conversion/TorchToStablehlo/view_like.mlir
index ab54d2764..3b0169036 100644
--- a/test/Conversion/TorchToStablehlo/view_like.mlir
+++ b/test/Conversion/TorchToStablehlo/view_like.mlir
@@ -310,11 +310,12 @@ func.func @torch.aten.slice.none.static$slice_like(%arg0: !torch.vtensor<[4,65,2
 // CHECK:         %[[T3:.*]] = torch_c.to_i64 %[[INT224]]
 // CHECK:         %[[T4:.*]] = shape.shape_of %[[T0]] : tensor<?x?x?x?xf32> -> tensor<4xindex>
 // CHECK:         %[[T5:.*]] = shape.num_elements %[[T4]] : tensor<4xindex> -> index
-// CHECK:         %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T2]], %[[T3]] : tensor<2xi64>
-// CHECK:         %[[T6:.*]] = stablehlo.compute_reshape_shape %[[T5]], %[[FROM_ELEMENTS]] : (index, tensor<2xi64>) -> tensor<2xi64>
-// CHECK:         %[[T7:.*]] = stablehlo.dynamic_reshape %[[T0]], %[[T6]] : (tensor<?x?x?x?xf32>, tensor<2xi64>) -> tensor<?x224xf32>
-// CHECK:         %[[T8:.*]] = torch_c.from_builtin_tensor %[[T7]] : tensor<?x224xf32> -> !torch.vtensor<[?,224],f32>
-// CHECK:         return %[[T8]] : !torch.vtensor<[?,224],f32>
+// CHECK:         %[[T6:.*]] = arith.index_cast %[[T5]] : index to i64
+// CHECK:         %[[T7:.*]] = arith.divui %[[T6]], %[[T3]] : i64
+// CHECK:         %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T7]], %[[T3]] : tensor<2xi64>
+// CHECK:         %[[T8:.*]] = stablehlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<?x?x?x?xf32>, tensor<2xi64>) -> tensor<?x224xf32>
+// CHECK:         %[[T9:.*]] = torch_c.from_builtin_tensor %[[T8]] : tensor<?x224xf32> -> !torch.vtensor<[?,224],f32>
+// CHECK:         return %[[T9]] : !torch.vtensor<[?,224],f32>
 func.func @torch.aten.view$basic(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?,224],f32> {
   %int-1 = torch.constant.int -1
   %int224 = torch.constant.int 224
@@ -339,11 +340,14 @@ func.func @torch.aten.view$basic(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch
 // CHECK:         %[[T5:.*]] = torch_c.to_i64 %[[INT64]]
 // CHECK:         %[[T6:.*]] = shape.shape_of %[[T0]] : tensor<?x?x?x?x?xf32> -> tensor<5xindex>
 // CHECK:         %[[T7:.*]] = shape.num_elements %[[T6]] : tensor<5xindex> -> index
-// CHECK:         %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T2]], %[[T3]], %[[T4]], %[[T5]] : tensor<4xi64>
-// CHECK:         %[[T8:.*]] = stablehlo.compute_reshape_shape %[[T7]], %[[FROM_ELEMENTS]] : (index, tensor<4xi64>) -> tensor<4xi64>
-// CHECK:         %[[T9:.*]] = stablehlo.dynamic_reshape %[[T0]], %[[T8]] : (tensor<?x?x?x?x?xf32>, tensor<4xi64>) -> tensor<?x120x4x64xf32>
-// CHECK:         %[[T10:.*]] = torch_c.from_builtin_tensor %[[T9]] : tensor<?x120x4x64xf32> -> !torch.vtensor<[?,120,4,64],f32>
-// CHECK:         return %[[T10]] : !torch.vtensor<[?,120,4,64],f32>
+// CHECK:         %[[T8:.*]] = arith.index_cast %[[T7]] : index to i64
+// CHECK:         %[[T9:.*]] = arith.divui %[[T8]], %[[T3]] : i64
+// CHECK:         %[[T10:.*]] = arith.divui %[[T9]], %[[T4]] : i64
+// CHECK:         %[[T11:.*]] = arith.divui %[[T10]], %[[T5]] : i64
+// CHECK:         %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T11]], %[[T3]], %[[T4]], %[[T5]] : tensor<4xi64>
+// CHECK:         %[[T12:.*]] = stablehlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<?x?x?x?x?xf32>, tensor<4xi64>) -> tensor<?x120x4x64xf32>
+// CHECK:         %[[T13:.*]] = torch_c.from_builtin_tensor %[[T12]] : tensor<?x120x4x64xf32> -> !torch.vtensor<[?,120,4,64],f32>
+// CHECK:         return %[[T13]] : !torch.vtensor<[?,120,4,64],f32>
 func.func @torch.aten.reshape$basic(%arg0: !torch.vtensor<[?,?,?,?,?],f32>) -> !torch.vtensor<[?,120,4,64],f32> {
   %int-1 = torch.constant.int -1
   %int120 = torch.constant.int 120