diff --git a/comfy_extras/nodes_lt.py b/comfy_extras/nodes_lt.py
index b51d1580453a..50da5f4eb606 100644
--- a/comfy_extras/nodes_lt.py
+++ b/comfy_extras/nodes_lt.py
@@ -34,6 +34,7 @@ def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
         latent = torch.zeros([batch_size, 128, ((length - 1) // 8) + 1, height // 32, width // 32], device=comfy.model_management.intermediate_device())
         return io.NodeOutput({"samples": latent})
 
+    generate = execute  # TODO: remove
 
 class LTXVImgToVideo(io.ComfyNode):
     @classmethod
@@ -77,6 +78,8 @@ def execute(cls, positive, negative, image, vae, width, height, length, batch_si
 
         return io.NodeOutput(positive, negative, {"samples": latent, "noise_mask": conditioning_latent_frames_mask})
 
+    generate = execute  # TODO: remove
+
 
 def conditioning_get_any_value(conditioning, key, default=None):
     for t in conditioning:
@@ -264,6 +267,8 @@ def execute(cls, positive, negative, vae, latent, image, frame_idx, strength) ->
 
         return io.NodeOutput(positive, negative, {"samples": latent_image, "noise_mask": noise_mask})
 
+    generate = execute  # TODO: remove
+
 
 class LTXVCropGuides(io.ComfyNode):
     @classmethod
@@ -300,6 +305,8 @@ def execute(cls, positive, negative, latent) -> io.NodeOutput:
 
         return io.NodeOutput(positive, negative, {"samples": latent_image, "noise_mask": noise_mask})
 
+    crop = execute  # TODO: remove
+
 
 class LTXVConditioning(io.ComfyNode):
     @classmethod
@@ -498,6 +505,7 @@ def execute(cls, image, img_compression) -> io.NodeOutput:
             output_images.append(preprocess(image[i], img_compression))
         return io.NodeOutput(torch.stack(output_images))
 
+    preprocess = execute  # TODO: remove
 
 class LtxvExtension(ComfyExtension):
     @override