diff --git a/docs/docs/configuration/face_recognition.md b/docs/docs/configuration/face_recognition.md
index 3082e46d0..63c16c2a8 100644
--- a/docs/docs/configuration/face_recognition.md
+++ b/docs/docs/configuration/face_recognition.md
@@ -74,8 +74,10 @@ Fine-tune face recognition with these optional parameters at the global level of
 
 ## Usage
 
+Follow these steps to begin:
+
 1. **Enable face recognition** in your configuration file and restart Frigate.
-2. **Upload your face** using the **Add Face** button's wizard in the Face Library section of the Frigate UI.
+2. **Upload one face** using the **Add Face** button's wizard in the Face Library section of the Frigate UI. Read below for the best practices on expanding your training set.
 3. When Frigate detects and attempts to recognize a face, it will appear in the **Train** tab of the Face Library, along with its associated recognition confidence.
 4. From the **Train** tab, you can **assign the face** to a new or existing person to improve recognition accuracy for the future.
 
diff --git a/docs/docs/configuration/object_detectors.md b/docs/docs/configuration/object_detectors.md
index 32ca7bed4..90b12a88a 100644
--- a/docs/docs/configuration/object_detectors.md
+++ b/docs/docs/configuration/object_detectors.md
@@ -1053,13 +1053,14 @@ python3 yolo_to_onnx.py -m yolov7-320
 
 #### YOLOv9
 
-YOLOv9 models can be exported using the below code or they [can be downloaded from hugging face](https://huggingface.co/Xenova/yolov9-onnx/tree/main)
+YOLOv9 models can be exported using the below code
 
 ```sh
 git clone https://github.com/WongKinYiu/yolov9
 cd yolov9
 
 # setup the virtual environment so installation doesn't affect main system
+# NOTE: Virtual environment must be using Python 3.11 or older.
 python3 -m venv ./
 bin/pip install -r requirements.txt
 bin/pip install onnx onnxruntime onnx-simplifier>=0.4.1
diff --git a/frigate/data_processing/real_time/face.py b/frigate/data_processing/real_time/face.py
index 963a3e73a..2bd8546a6 100644
--- a/frigate/data_processing/real_time/face.py
+++ b/frigate/data_processing/real_time/face.py
@@ -471,17 +471,22 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
         if not results_list:
             return None, 0.0
 
-        weighted_scores = {}
-        total_weights = {}
+        counts: dict[str, int] = {}
+        weighted_scores: dict[str, int] = {}
+        total_weights: dict[str, int] = {}
 
         for name, score, face_area in results_list:
             if name == "unknown":
                 continue
 
             if name not in weighted_scores:
+                counts[name] = 0
                 weighted_scores[name] = 0.0
                 total_weights[name] = 0.0
 
+            # increase count
+            counts[name] += 1
+
             # Capped weight based on face area
             weight = min(face_area, max_weight)
 
@@ -494,6 +499,12 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             return None, 0.0
 
         best_name = max(weighted_scores, key=weighted_scores.get)
+
+        # If the best name has the same number of results as another name, we are not confident it is a correct result
+        for name, count in counts.items():
+            if name != best_name and counts[best_name] == count:
+                return None, 0.0
+
         weighted_average = weighted_scores[best_name] / total_weights[best_name]
 
         return best_name, weighted_average
diff --git a/frigate/detectors/plugins/hailo8l.py b/frigate/detectors/plugins/hailo8l.py
index 3f561c5f5..aa856dd80 100755
--- a/frigate/detectors/plugins/hailo8l.py
+++ b/frigate/detectors/plugins/hailo8l.py
@@ -345,11 +345,17 @@ class HailoDetector(DetectionApi):
         request_id = self.input_store.put(tensor_input)
 
         try:
-            _, infer_results = self.response_store.get(request_id, timeout=10.0)
+            _, infer_results = self.response_store.get(request_id, timeout=1.0)
         except TimeoutError:
             logger.error(
                 f"Timeout waiting for inference results for request {request_id}"
             )
+
+            if not self.inference_thread.is_alive():
+                raise RuntimeError(
+                    "HailoRT inference thread has stopped, restart required."
+                )
+
             return np.zeros((20, 6), dtype=np.float32)
 
         if isinstance(infer_results, list) and len(infer_results) == 1:
diff --git a/web/src/components/input/InputWithTags.tsx b/web/src/components/input/InputWithTags.tsx
index c2afd441c..ab31e1808 100644
--- a/web/src/components/input/InputWithTags.tsx
+++ b/web/src/components/input/InputWithTags.tsx
@@ -763,12 +763,18 @@ export default function InputWithTags({
 
             {inputFocused ? (
               <LuChevronUp
-                onClick={() => setInputFocused(false)}
+                onClick={() => {
+                  setInputFocused(false);
+                  inputRef.current?.blur();
+                }}
                 className="size-4 cursor-pointer text-secondary-foreground"
               />
             ) : (
               <LuChevronDown
-                onClick={() => setInputFocused(true)}
+                onClick={() => {
+                  setInputFocused(true);
+                  inputRef.current?.focus();
+                }}
                 className="size-4 cursor-pointer text-secondary-foreground"
               />
             )}
@@ -778,7 +784,9 @@ export default function InputWithTags({
         <CommandList
           className={cn(
             "scrollbar-container border-t duration-200 animate-in fade-in",
-            inputFocused ? "visible" : "hidden",
+            inputFocused && inputRef.current?.matches(":focus")
+              ? "visible"
+              : "hidden",
           )}
         >
           {!currentFilterType && inputValue && (