This seems like a bug.
Could you create a Github issue and post this code to reproduce the issue:
output = torch.randn(5, 2, requires_grad=True)
target = torch.empty(5, dtype=torch.long).random_(2)
target[0] = -9223372036854775808

criterion = nn.CrossEntropyLoss()
loss = criterion(output, target)
print(loss)