diff --git a/scripts/fabric.py b/scripts/fabric.py
index 1cd1117..d3c2b68 100644
--- a/scripts/fabric.py
+++ b/scripts/fabric.py
@@ -139,6 +139,7 @@ class FabricParams:
     tome_ratio: float = 0.5
     tome_max_tokens: int = 4*4096
     tome_seed: int = -1
+    burnout_protection: bool = False
 
 
 # TODO: replace global state with Gradio state
@@ -218,6 +219,7 @@ class FabricScript(modules.scripts.Script):
 
                 feedback_max_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, value=0.8, label="Feedback Strength", elem_id="fabric_max_weight")
                 tome_enabled = gr.Checkbox(label="Enable Token Merging (faster, less VRAM, less accurate)", value=False)
+                burnout_protection = gr.Checkbox(label="Burnout protection (enable if results contain artifacts or are especially dark)", value=False)
 
             with gr.Accordion("Advanced options", open=DEBUG):
                 with FormGroup():
@@ -302,6 +304,7 @@ class FabricScript(modules.scripts.Script):
             (tome_ratio, "fabric_tome_ratio"),
             (tome_max_tokens, "fabric_tome_max_tokens"),
             (tome_seed, "fabric_tome_seed"),
+            (burnout_protection, "fabric_burnout_protection"),
             (feedback_during_high_res_fix, "fabric_feedback_during_high_res_fix"),
             (liked_paths, lambda d: gr.update(value=_load_feedback_paths(d, "fabric_pos_images")) if "fabric_pos_images" in d else None),
             (disliked_paths, lambda d: gr.update(value=_load_feedback_paths(d, "fabric_neg_images")) if "fabric_neg_images" in d else None),
@@ -323,6 +326,7 @@ class FabricScript(modules.scripts.Script):
             tome_ratio,
             tome_max_tokens,
             tome_seed,
+            burnout_protection,
         ]
     
 
@@ -429,6 +433,7 @@ class FabricScript(modules.scripts.Script):
             tome_ratio,
             tome_max_tokens,
             tome_seed,
+            burnout_protection,
         ) = args
 
         # restore original U-Net forward pass in case previous batch errored out
@@ -454,6 +459,7 @@ class FabricScript(modules.scripts.Script):
             tome_ratio=(round(tome_ratio * 16) / 16),
             tome_max_tokens=tome_max_tokens,
             tome_seed=get_fixed_seed(int(tome_seed)),
+            burnout_protection=burnout_protection,
         )
 
 
diff --git a/scripts/patching.py b/scripts/patching.py
index e3ed907..a298a45 100644
--- a/scripts/patching.py
+++ b/scripts/patching.py
@@ -156,6 +156,10 @@ def patch_unet_forward_pass(p, unet, params):
         "seed": params.tome_seed,
     }
 
+    prev_vals = {
+        "weight_modifier": 1.0,
+    }
+
     def new_forward(self, x, timesteps=None, context=None, **kwargs):
         _, uncond_ids, cond_ids, context = unmark_prompt_context(context)
         has_cond = len(cond_ids) > 0
@@ -167,11 +171,22 @@ def patch_unet_forward_pass(p, unet, params):
             if not params.feedback_during_high_res_fix:
                 print("[FABRIC] Skipping feedback during high-res fix")
                 return self._fabric_old_forward(x, timesteps, context, **kwargs)
-            
+        
         pos_weight, neg_weight = get_curr_feedback_weight(p, params, timesteps[0].item(), num_timesteps=num_timesteps)
         if pos_weight <= 0 and neg_weight <= 0:
             return self._fabric_old_forward(x, timesteps, context, **kwargs)
 
+        if params.burnout_protection and "cond" in prev_vals and "uncond" in prev_vals:
+            # burnout protection: if the difference betwen cond/uncond was too high in the previous step (sign of instability), slash the weight modifier
+            diff_std = (prev_vals["cond"] - prev_vals["uncond"]).std(dim=(2, 3)).max().item()
+            diff_abs_mean = (prev_vals["cond"] - prev_vals["uncond"]).mean(dim=(2, 3)).abs().max().item()
+            if diff_std > 0.06 or diff_abs_mean > 0.02:
+                prev_vals["weight_modifier"] *= 0.5
+            else:
+                prev_vals["weight_modifier"] = min(1.0, 1.5 * prev_vals["weight_modifier"])
+        
+        pos_weight, neg_weight = pos_weight * prev_vals["weight_modifier"], neg_weight * prev_vals["weight_modifier"]
+
         pos_latents, neg_latents = get_latents_from_params(p, params, w, h)
         pos_latents = pos_latents if has_cond else []
         neg_latents = neg_latents if has_uncond else []
@@ -288,6 +303,18 @@ def patch_unet_forward_pass(p, unet, params):
             # run forward pass with cached hidden states
             out = self._fabric_old_forward(x, timesteps, context, **kwargs)
 
+            cond_outs = out[cond_ids]
+            uncond_outs = out[uncond_ids]
+            
+            if has_cond:
+                prev_vals["cond"] = cond_outs.detach().clone()
+            if has_uncond:
+                prev_vals["uncond"] = uncond_outs.detach().clone()
+
+            if params.burnout_protection:
+                # burnout protection: recenter the output to prevent instabilities caused by mean drift
+                mean = out.mean(dim=(2, 3), keepdim=True)
+                out = out - 0.5 * mean
         finally:
             # restore original pass
             for module in self.modules():