Add braindecode logo side-by-side and remove adapter emojis

Display the braindecode logo next to the eegdash brain logo in the
header, linking to braindecode.org. Replace all adapter method emoji
icons with plain text labels across the leaderboard, about page,
submission form, and filters.

frontend/src/components/Logo/Logo.js

@@ -28,27 +28,53 @@ const Logo = ({ height = "40px" }) => {
 
   return (
     <Box
-      onClick={handleReset}
       sx={{
         height,
         display: "flex",
         alignItems: "center",
         justifyContent: "center",
-        cursor: "pointer",
-        transition: "opacity 0.2s ease",
-        "&:hover": {
-          opacity: 0.8,
-        },
+        gap: 2,
       }}
     >
       <Box
+        onClick={handleReset}
         sx={{
           height: "100%",
           aspectRatio: "200/150",
+          cursor: "pointer",
+          transition: "opacity 0.2s ease",
+          "&:hover": {
+            opacity: 0.8,
+          },
         }}
       >
         <HFLogo />
       </Box>
+      <Box
+        component="a"
+        href="https://braindecode.org"
+        target="_blank"
+        rel="noopener noreferrer"
+        sx={{
+          height: "100%",
+          display: "flex",
+          alignItems: "center",
+          cursor: "pointer",
+          transition: "opacity 0.2s ease",
+          "&:hover": {
+            opacity: 0.8,
+          },
+        }}
+      >
+        <Box
+          component="img"
+          src="https://braindecode.org/stable/_images/braindecode.svg"
+          alt="Braindecode"
+          sx={{
+            height: "100%",
+          }}
+        />
+      </Box>
     </Box>
   );
 };

frontend/src/pages/AboutPage/AboutPage.js

@@ -137,48 +137,48 @@ function AboutPage() {
         <Box component="ul" sx={{ pl: 3 }}>
           <li>
             <Typography variant="body1" color="text.secondary" paragraph>
-              <strong>{"\u{1F9E9}"} LoRA</strong> - Low-Rank Adaptation (r=16,
+              <strong>LoRA</strong> - Low-Rank Adaptation (r=16,
               alpha=32): injects trainable low-rank matrices, ~98% parameter
               reduction.
             </Typography>
           </li>
           <li>
             <Typography variant="body1" color="text.secondary" paragraph>
-              <strong>{"\u{1F4A1}"} IA3</strong> - Infused Adapter by Inhibiting
+              <strong>IA3</strong> - Infused Adapter by Inhibiting
               and Amplifying Inner Activations: only learns scaling vectors,
               ~99.5% parameter reduction.
             </Typography>
           </li>
           <li>
             <Typography variant="body1" color="text.secondary" paragraph>
-              <strong>{"\u{1F3AF}"} AdaLoRA</strong> - Adaptive Low-Rank
+              <strong>AdaLoRA</strong> - Adaptive Low-Rank
               Adaptation: dynamic rank allocation across layers for optimal
               budget distribution.
             </Typography>
           </li>
           <li>
             <Typography variant="body1" color="text.secondary" paragraph>
-              <strong>{"\u{1F52C}"} DoRA</strong> - Weight-Decomposed Low-Rank
+              <strong>DoRA</strong> - Weight-Decomposed Low-Rank
               Adaptation: decomposes weights into magnitude and direction
               components.
             </Typography>
           </li>
           <li>
             <Typography variant="body1" color="text.secondary" paragraph>
-              <strong>{"\u{1F504}"} OFT</strong> - Orthogonal Fine-Tuning:
+              <strong>OFT</strong> - Orthogonal Fine-Tuning:
               applies orthogonal transformations to preserve pre-trained
               features.
             </Typography>
           </li>
           <li>
             <Typography variant="body1" color="text.secondary" paragraph>
-              <strong>{"\u{1F50D}"} Probe</strong> - Linear probing baseline:
+              <strong>Probe</strong> - Linear probing baseline:
               freezes the encoder and trains only the classification head.
             </Typography>
           </li>
           <li>
             <Typography variant="body1" color="text.secondary" paragraph>
-              <strong>{"\u{1F527}"} Full Fine-tune</strong> - Updates all model
+              <strong>Full Fine-tune</strong> - Updates all model
               parameters (baseline for comparison).
             </Typography>
           </li>

frontend/src/pages/AddModelPage/components/ModelSubmissionForm/ModelSubmissionForm.js

@@ -59,13 +59,13 @@ const HELP_TEXTS = {
         Adapter / Fine-tuning Method
       </Typography>
       <Typography variant="body2" sx={{ opacity: 0.9, lineHeight: 1.4 }}>
-        {"\u{1F9E9}"} LoRA: Low-Rank Adaptation (~98% param reduction){" "}
-        {"\u{1F4A1}"} IA3: Scaling vectors only (~99.5% reduction){" "}
-        {"\u{1F3AF}"} AdaLoRA: Adaptive rank allocation{" "}
-        {"\u{1F52C}"} DoRA: Weight-decomposed adaptation{" "}
-        {"\u{1F504}"} OFT: Orthogonal fine-tuning{" "}
-        {"\u{1F50D}"} Probe: Linear probing (head only){" "}
-        {"\u{1F527}"} Full Fine-tune: All parameters updated
+        LoRA: Low-Rank Adaptation (~98% param reduction){" "}
+        IA3: Scaling vectors only (~99.5% reduction){" "}
+        AdaLoRA: Adaptive rank allocation{" "}
+        DoRA: Weight-decomposed adaptation{" "}
+        OFT: Orthogonal fine-tuning{" "}
+        Probe: Linear probing (head only){" "}
+        Full Fine-tune: All parameters updated
       </Typography>
     </Box>
   ),
@@ -110,9 +110,9 @@ const HELP_TEXTS = {
 
 // Convert MODEL_TYPES to format expected by Select component
 const modelTypeOptions = Object.entries(MODEL_TYPES).map(
-  ([value, { icon, label }]) => ({
+  ([value, { label }]) => ({
     value,
-    label: `${icon} ${label}`,
+    label,
   })
 );
 

frontend/src/pages/LeaderboardPage/components/Leaderboard/components/Filters/Filters.js

@@ -609,9 +609,7 @@ const LeaderboardFilters = ({
                         ).map((type) => (
                           <FilterTag
                             key={type}
-                            label={`${MODEL_TYPES[type]?.icon} ${
-                              MODEL_TYPES[type]?.label || type
-                            }`}
+                            label={MODEL_TYPES[type]?.label || type}
                             checked={selectedTypes.includes(type)}
                             onChange={() => {
                               const newTypes = selectedTypes.includes(type)

frontend/src/pages/LeaderboardPage/components/Leaderboard/constants/modelTypes.js

@@ -14,43 +14,43 @@ export const MODEL_TYPE_ORDER = [
 
 export const MODEL_TYPES = {
   'lora': {
-    icon: '\u{1F9E9}',
+    icon: '',
     label: 'LoRA',
     description: 'Low-Rank Adaptation: injects trainable low-rank matrices into transformer layers (~98% parameter reduction)',
     order: 0
   },
   'ia3': {
-    icon: '\u{1F4A1}',
+    icon: '',
     label: 'IA3',
     description: 'Infused Adapter by Inhibiting and Amplifying Inner Activations (~99.5% parameter reduction)',
     order: 1
   },
   'adalora': {
-    icon: '\u{1F3AF}',
+    icon: '',
     label: 'AdaLoRA',
     description: 'Adaptive Low-Rank Adaptation with dynamic rank allocation across layers',
     order: 2
   },
   'dora': {
-    icon: '\u{1F52C}',
+    icon: '',
     label: 'DoRA',
     description: 'Weight-Decomposed Low-Rank Adaptation: decomposes weights into magnitude and direction',
     order: 3
   },
   'oft': {
-    icon: '\u{1F504}',
+    icon: '',
     label: 'OFT',
     description: 'Orthogonal Fine-Tuning: applies orthogonal transformations to preserve pre-trained features',
     order: 4
   },
   'probe': {
-    icon: '\u{1F50D}',
+    icon: '',
     label: 'Probe',
     description: 'Linear probing: freezes the encoder and trains only the classification head',
     order: 5
   },
   'full_finetune': {
-    icon: '\u{1F527}',
+    icon: '',
     label: 'Full Fine-tune',
     description: 'Full fine-tuning baseline: all model parameters are updated during training',
     order: 6
@@ -62,7 +62,7 @@ export const getModelTypeIcon = (type) => {
   const matchedType = Object.entries(MODEL_TYPES).find(([key]) =>
     cleanType.includes(key)
   );
-  return matchedType ? matchedType[1].icon : '\u{2753}';
+  return matchedType ? matchedType[1].icon : '';
 };
 
 export const getModelTypeLabel = (type) => {

frontend/src/pages/LeaderboardPage/components/Leaderboard/utils/columnUtils.js

@@ -1,6 +1,6 @@
 import React from "react";
 import { Box, Typography, Link, Tooltip, IconButton } from "@mui/material";
-import { getModelTypeIcon } from "../constants/modelTypes";
+import { getModelTypeLabel } from "../constants/modelTypes";
 import TrendingUpIcon from "@mui/icons-material/TrendingUp";
 import TrendingDownIcon from "@mui/icons-material/TrendingDown";
 import RemoveIcon from "@mui/icons-material/Remove";
@@ -530,14 +530,13 @@ export const createColumns = (
           <Tooltip title={row.original.model.type}>
             <Typography
               sx={{
-                fontSize: "1.2rem",
+                fontSize: "0.75rem",
                 cursor: "help",
                 lineHeight: 1,
-                fontFamily:
-                  '"Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji", sans-serif',
+                fontWeight: 500,
               }}
             >
-              {getModelTypeIcon(row.original.model.type)}
+              {getModelTypeLabel(row.original.model.type)}
             </Typography>
           </Tooltip>
         </Box>