diff --git a/lib/Conversion/TorchToStablehlo/Basic.cpp b/lib/Conversion/TorchToStablehlo/Basic.cpp
index bec3eb5d38cb..844ac2f17332 100644
--- a/lib/Conversion/TorchToStablehlo/Basic.cpp
+++ b/lib/Conversion/TorchToStablehlo/Basic.cpp
@@ -1759,6 +1759,65 @@ LogicalResult ConvertAtenOp<AtenConstantPadNdOp>::matchAndRewrite(
   return success();
 }
 
+template <>
+LogicalResult ConvertAtenOp<AtenReflectionPad1dOp>::matchAndRewrite(
+    AtenReflectionPad1dOp op, OpAdaptor adaptor,
+    ConversionPatternRewriter &rewriter) const {
+  Location loc = op.getLoc();
+  Value self = adaptor.getSelf();
+  auto selfTy = cast<RankedTensorType>(self.getType());
+  if (!selfTy.hasStaticShape()) {
+    return rewriter.notifyMatchFailure(op, "only support static shape");
+  }
+  int64_t rank = selfTy.getRank();
+  int64_t dim = rank - 1;
+
+  SmallVector<int64_t> padInts;
+  if (!matchPattern(op.getPadding(), m_TorchListOfConstantInts(padInts))) {
+    return rewriter.notifyMatchFailure(op,
+                                       "only support constant int pad ranges");
+  }
+  if (padInts.size() != 2) {
+    return rewriter.notifyMatchFailure(op, "pad size must be 2");
+  }
+  if (padInts[0] >= selfTy.getDimSize(dim) ||
+      padInts[1] >= selfTy.getDimSize(dim)) {
+    return rewriter.notifyMatchFailure(op,
+                                       "pad size must be less than dim size");
+  }
+
+  Value left;
+  {
+    SmallVector<int64_t> startIndices(rank, 0);
+    SmallVector<int64_t> limitIndices(selfTy.getShape().begin(),
+                                      selfTy.getShape().end());
+    SmallVector<int64_t> strides(rank, 1);
+    startIndices[dim] = 1;
+    limitIndices[dim] = padInts[0] + 1;
+    left = rewriter.create<stablehlo::SliceOp>(loc, self, startIndices,
+                                               limitIndices, strides);
+    left = rewriter.create<stablehlo::ReverseOp>(loc, left,
+                                                 ArrayRef<int64_t>({dim}));
+  }
+  Value right;
+  {
+    SmallVector<int64_t> startIndices(rank, 0);
+    SmallVector<int64_t> limitIndices(selfTy.getShape().begin(),
+                                      selfTy.getShape().end());
+    SmallVector<int64_t> strides(rank, 1);
+    startIndices[dim] = selfTy.getDimSize(dim) - 1 - padInts[1];
+    limitIndices[dim] = selfTy.getDimSize(dim) - 1;
+    right = rewriter.create<stablehlo::SliceOp>(loc, self, startIndices,
+                                                limitIndices, strides);
+    right = rewriter.create<stablehlo::ReverseOp>(loc, right,
+                                                  ArrayRef<int64_t>({dim}));
+  }
+  Value result = rewriter.create<stablehlo::ConcatenateOp>(
+      loc, ValueRange{left, self, right}, dim);
+  rewriter.replaceOp(op, result);
+  return success();
+}
+
 template <>
 LogicalResult ConvertAtenOp<AtenGeluBackwardOp>::matchAndRewrite(
     AtenGeluBackwardOp op, OpAdaptor adaptor,
@@ -2269,6 +2328,7 @@ void mlir::torch::torch_to_stablehlo::populateBasicOpPatternsAndLegality(
   INSERT_ATENOP_PATTERN(AtenScalarImplicitOp);
   INSERT_ATENOP_PATTERN(AtenContiguousOp);
   INSERT_ATENOP_PATTERN(AtenConstantPadNdOp);
+  INSERT_ATENOP_PATTERN(AtenReflectionPad1dOp);
 
   INSERT_ATENOP_PATTERN(AtenReluOp);
   INSERT_ATENOP_PATTERN(AtenGeluOp);
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index d6daf2c3637a..bee2c62d7202 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -829,10 +829,6 @@
     "RandnLikeDtypeModule_basic",
     "RandnLikeModule_basic",
     "RandnModule_basic",
-    "ReflectionPad1dModule2dInput_Right",
-    "ReflectionPad1dModule2dInput_basic",
-    "ReflectionPad1dModule3dInput_Left",
-    "ReflectionPad1dModule3dInput_basic",
     "ReflectionPad2dModule_Bottom",
     "ReflectionPad2dModule_Left",
     "ReflectionPad2dModule_Right",