sampler: lower Momentum Guidance decay default 0.9 -> 0.5

Live testing found decay=0.9 produces garbage at any strength on our
8-step schedule: the EMA barely forgets, so it stays anchored to the
very first (near-pure-noise, wrong-scale) step's direction for nearly
the whole run. decay=0.5 forgets that stale step within 2-3 iterations
and tested clean even at strength=1.0. Paper's longer-schedule decay
assumptions don't transfer to a few-step distilled run.

conditioning.py

@@ -14631,7 +14631,7 @@ class FunPackStudio:
                     alg_sigma_threshold=float(dc.get("alg_sigma_threshold", 0.94)),
                     mg_enabled=bool(dc.get("mg_enabled", False)),
                     mg_strength=float(dc.get("mg_strength", 0.5)),
-                    mg_decay=float(dc.get("mg_decay", 0.9)),
+                    mg_decay=float(dc.get("mg_decay", 0.5)),
                     mg_sigma_threshold=float(dc.get("mg_sigma_threshold", 0.975)),
                     sigmas=sigmas_raw,
                 )

movie_editor/frontend/sampler_panel.js

@@ -31,7 +31,7 @@
       velocity_bias_source: "mean", velocity_refinement_key: "default",
       rescue_mode: false, rescue_threshold: 0.15, rescue_strength: 0.2,
       alg_enabled: false, alg_strength: 2.0, alg_sigma_threshold: 0.975,
-      mg_enabled: false, mg_strength: 0.5, mg_decay: 0.9, mg_sigma_threshold: 0.975,
+      mg_enabled: false, mg_strength: 0.5, mg_decay: 0.5, mg_sigma_threshold: 0.975,
     };
   }
 

samplers.py

@@ -1639,7 +1639,7 @@ def sample_funpack_distilled_flow(model, x, sigmas, extra_args=None, callback=No
                                    rescue_prompt_sig=None,
                                    alg_enabled=False, alg_strength=2.0, alg_sigma_threshold=0.975,
                                    alg_guide_tail_frames=0,
-                                   mg_enabled=False, mg_strength=0.5, mg_decay=0.9, mg_sigma_threshold=0.975):
+                                   mg_enabled=False, mg_strength=0.5, mg_decay=0.5, mg_sigma_threshold=0.975):
     """
     ODE sampler for distilled few-step video models (e.g. LTX2.3 distilled LoRA).
 
@@ -1950,8 +1950,8 @@ class FunPackDistilledFlowSampler:
                     "tooltip": "Blend weight toward the momentum average when active (0 = no effect, 1 = fully replace the step's direction with the average). Only used when mg_enabled.",
                 }),
                 "mg_decay": ("FLOAT", {
-                    "default": 0.9, "min": 0.0, "max": 0.99, "step": 0.05,
-                    "tooltip": "EMA decay for the momentum average (higher = longer memory of past steps' directions). Only used when mg_enabled.",
+                    "default": 0.5, "min": 0.0, "max": 0.99, "step": 0.05,
+                    "tooltip": "EMA decay for the momentum average (higher = longer memory of past steps' directions). On our 8-step schedule, high decay (e.g. 0.9) keeps the EMA anchored to the very first, near-pure-noise step's direction for nearly the whole run — wrong scale, produces garbage regardless of mg_strength. Tested safe (and good) at 0.5 even at mg_strength=1.0. Only used when mg_enabled.",
                 }),
                 "mg_sigma_threshold": ("FLOAT", {
                     "default": 0.975, "min": 0.5, "max": 0.999, "step": 0.005,
@@ -1980,7 +1980,7 @@ class FunPackDistilledFlowSampler:
                     rescue_prompt_sig=None, sigmas=None, ab2_ramp=False,
                     normalize_strength=0.0, normalize_start_sigma=0.9,
                     alg_enabled=False, alg_strength=2.0, alg_sigma_threshold=0.975,
-                    mg_enabled=False, mg_strength=0.5, mg_decay=0.9, mg_sigma_threshold=0.975):
+                    mg_enabled=False, mg_strength=0.5, mg_decay=0.5, mg_sigma_threshold=0.975):
         prepared_sigmas = sigmas.detach().clone() if isinstance(sigmas, torch.Tensor) else sigmas
         sampler = comfy.samplers.KSAMPLER(
             sample_funpack_distilled_flow,