diff --git a/core/conversion/converters/impl/select.cpp b/core/conversion/converters/impl/select.cpp
index 3599ab9939..0bb6ad01ff 100644
--- a/core/conversion/converters/impl/select.cpp
+++ b/core/conversion/converters/impl/select.cpp
@@ -22,6 +22,8 @@ bool add_split(ConversionCtx* ctx, const torch::jit::Node* n, args& args, bool s
 
   if (unbind) {
     axis = args[1].unwrapToInt();
+    auto maxDim = static_cast<int64_t>(in->getDimensions().nbDims);
+    axis = axis < 0 ? axis + maxDim : axis;
     numOutputs = in->getDimensions().d[axis];
     sizes.insert(sizes.end(), numOutputs, 1);
   } else {
diff --git a/core/conversion/evaluators/aten.cpp b/core/conversion/evaluators/aten.cpp
index 4632744790..4d8795f378 100644
--- a/core/conversion/evaluators/aten.cpp
+++ b/core/conversion/evaluators/aten.cpp
@@ -181,7 +181,12 @@ auto aten_registrations TORCHTRT_UNUSED =
         .evaluator({c10::Symbol::fromQualString("aten::slice"),
                     [](const torch::jit::Node* n, kwargs& args) -> c10::optional<torch::jit::IValue> {
                       c10::List<c10::IValue> list = args.at(n->input(0)).IValue()->to<c10::List<c10::IValue>>();
-                      int64_t start = args.at(n->input(1)).unwrapToInt();
+
+                      int64_t start = 0;
+                      auto startIVal = args.at(n->input(1)).IValue();
+                      if(!startIVal->isNone()){
+                        start = args.at(n->input(1)).unwrapToInt();
+                      }
                       int64_t end = args.at(n->input(2)).unwrapToInt();
                       int64_t step = args.at(n->input(3)).unwrapToInt();
 
diff --git a/tests/core/conversion/converters/test_select.cpp b/tests/core/conversion/converters/test_select.cpp
index c4bb727d11..03b6bda36c 100644
--- a/tests/core/conversion/converters/test_select.cpp
+++ b/tests/core/conversion/converters/test_select.cpp
@@ -365,6 +365,38 @@ TEST(Converters, ATenSliceNegEndIndexConvertsCorrectly) {
   ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt, 2e-6));
 }
 
+TEST(Converters, ATenSliceListConvertsCorrectly) {
+  const auto graph = R"IR(
+        graph(%x : Tensor):
+          %1 : NoneType = prim::Constant()
+          %2 : int = prim::Constant[value=2]()
+          %3 : int = prim::Constant[value=1]()
+          %4 : int = prim::Constant[value=3]()
+          %list : Tensor[] = aten::unbind(%x, %4)
+          %slice : Tensor[] = aten::slice(%list, %1, %2, %3)
+          %out.1 : Tensor, %out.2 : Tensor = prim::ListUnpack(%slice)
+          return (%out.1, %out.2))IR";
+  
+  auto g = std::make_shared<torch::jit::Graph>();
+
+  torch::jit::parseIR(graph, g.get());
+
+  auto in_x = at::randint(1, 10, {6, 5, 3, 3}, {at::kCUDA});
+
+  auto jit_in_x = at::clone(in_x);
+
+  auto params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {});
+  auto jit_results = torch_tensorrt::tests::util::RunGraph(g, params, {jit_in_x});
+
+  auto trt_in_x = at::clone(in_x);
+  auto trt_results = torch_tensorrt::tests::util::RunGraphEngine(g, params, {trt_in_x});
+
+  for (size_t i = 0; i < jit_results.size(); i++) {
+    auto trt = trt_results[i].reshape(jit_results[i].sizes());
+    ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[i], trt, 2e-6));
+  }
+}
+
 TEST(Converters, ATenSliceDynamicBatchConvertsCorrectly) {
   const auto graph = R"IR(
         graph(%x.1 : Tensor):
@@ -796,3 +828,30 @@ TEST(Converters, ATenUnbindConvertsCorrectly) {
     ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[i], trt, 2e-6));
   }
 }
+
+TEST(Converters, ATenUnbindNegativeAxisConvertsCorrectly) {
+  const auto graph = R"IR(
+    graph(%x.1 : Tensor):
+        %2 : int = prim::Constant[value=-1]()
+        %3 : Tensor[] = aten::unbind(%x.1, %2)
+        %o1.1 : Tensor, %o2.1 : Tensor = prim::ListUnpack(%3)
+        return (%o1.1, %o2.1))IR";
+
+  auto g = std::make_shared<torch::jit::Graph>();
+
+  torch::jit::parseIR(graph, g.get());
+
+  auto in = at::randint(1, 10, {5, 2}, {at::kCUDA});
+
+  auto jit_in = at::clone(in);
+  auto params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {});
+  auto jit_results = torch_tensorrt::tests::util::RunGraph(g, params, {jit_in});
+
+  auto trt_in = at::clone(in);
+  auto trt_results = torch_tensorrt::tests::util::RunGraphEngine(g, params, {trt_in});
+
+  for (size_t i = 0; i < jit_results.size(); i++) {
+    auto trt = trt_results[i].reshape(jit_results[i].sizes());
+    ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[i], trt, 2e-6));
+  }
+}