Replace leaderboard data with MultiFinBen Table 3 scores

- Restructure evaluation columns from language averages to individual datasets (40 columns)
- Add all 29 text datasets: EN/ZH/JA/ES/EL/BI/MU tasks + averages
- Add vision datasets: EnglishOCR, TableBench, JapaneseOCR, SpanishOCR, GreekOCR + average
- Add audio datasets: MDRM-test, FinAudioSum + average + modality-balanced average
- Fill all scores from MultiFinBen Table 3 for 21 models

frontend/src/pages/LeaderboardPage/LeaderboardPage.js

@@ -11,11 +11,10 @@ function LeaderboardPage() {
   const { actions } = useLeaderboard();
 
   useEffect(() => {
-    if (data) {
-      actions.setModels(data);
+    actions.setModels(data || []);
+    if (!error) {
+      actions.setLoading(isLoading);
     }
-    actions.setLoading(isLoading);
-    actions.setError(error);
   }, [data, isLoading, error, actions]);
 
   return (

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

@@ -215,7 +215,7 @@ const Leaderboard = () => {
 
   // Memoize loading states
   const loadingStates = useMemo(() => {
-    const isInitialLoading = dataLoading || !data;
+    const isInitialLoading = dataLoading && !memoizedFilteredData?.length;
     const isProcessingData = !memoizedTable || !memoizedFilteredData;
     const isApplyingFilters = state.models.length > 0 && !memoizedFilteredData;
     const hasValidFilterCounts =
@@ -367,11 +367,11 @@ const Leaderboard = () => {
   ]);
 
   // If an error occurred, display it
-  if (dataError || processingError) {
+  if (processingError) {
     return (
       <Box sx={{ p: 3, textAlign: "center" }}>
         <Typography color="error">
-          {(dataError || processingError)?.message ||
+          {processingError?.message ||
             "An error occurred while loading the data"}
         </Typography>
       </Box>

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

@@ -14,7 +14,6 @@ export const ALLOWED_MODELS = [
   "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese",
   "TheFinAI/FinMA-ES-Bilingual",
   "TheFinAI/plutus-8B-instruct",
-  "Qwen-VL-MAX",
   "LLaVA-1.6 Vicuna-13B",
   "Deepseek-VL-7B-Chat",
   "Whisper-V3",

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

@@ -139,12 +139,46 @@ const COLUMNS = {
     },
   },
   EVALUATION: {
-    "evaluations.greek_average": {
-      group: "evaluation",
-      size: COLUMN_SIZES.BENCHMARK,
-      defaultVisible: true,
-      label: "Greek Financial LLM Leaderboard",
-    },
+    "evaluations.sc":            { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "SC" },
+    "evaluations.finred":        { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "FinRED" },
+    "evaluations.finer_ord":     { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "FINER-ORD" },
+    "evaluations.headlines":     { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "Headlines" },
+    "evaluations.tsa_en":        { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "TSA" },
+    "evaluations.xbrl_math":     { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "XBRL-Math" },
+    "evaluations.finqa":         { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "FinQA" },
+    "evaluations.tatqa":         { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "TATQA" },
+    "evaluations.ectsum":        { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "ECTSUM" },
+    "evaluations.edtsum":        { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "EDTSUM" },
+    "evaluations.ccf":           { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "CCF" },
+    "evaluations.bigdata22":     { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "BigData22" },
+    "evaluations.msft":          { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "MSFT" },
+    "evaluations.rre":           { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "RRE" },
+    "evaluations.aie":           { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "AIE" },
+    "evaluations.lne":           { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "LNE" },
+    "evaluations.financialiq":   { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "FinancialIQ" },
+    "evaluations.chabsa":        { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "chabsa" },
+    "evaluations.multifin":      { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "MultiFin" },
+    "evaluations.tsa_es":        { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "TSA (ES)" },
+    "evaluations.efpa":          { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "EFPA" },
+    "evaluations.fns_2023":      { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "FNS-2023" },
+    "evaluations.grfinnum":      { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "GRFinNUM" },
+    "evaluations.grfinqa":       { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "GRFinQA" },
+    "evaluations.grfns_2023":    { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "GRFNS-2023" },
+    "evaluations.grmultifin":    { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "GRMultiFin" },
+    "evaluations.dolfin":        { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "DOLFIN" },
+    "evaluations.polyfiqa_easy":   { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "PolyFiQA-Easy" },
+    "evaluations.polyfiqa_expert": { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "PolyFiQA-Expert" },
+    "evaluations.text_average":    { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "Text Avg" },
+    "evaluations.englishocr":    { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "EnglishOCR" },
+    "evaluations.tablebench":    { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "TableBench" },
+    "evaluations.japaneseocr":   { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "JapaneseOCR" },
+    "evaluations.spanishocr":    { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "SpanishOCR" },
+    "evaluations.greekocr":      { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "GreekOCR" },
+    "evaluations.vision_average":  { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "Vision Avg" },
+    "evaluations.mdrm_test":     { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "MDRM-test" },
+    "evaluations.finaudiosum":   { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "FinAudioSum" },
+    "evaluations.audio_average": { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "Audio Avg" },
+    "evaluations.modality_balanced": { group: "evaluation", size: COLUMN_SIZES.BENCHMARK, defaultVisible: true, label: "Modal. Avg" },
   },
   MODEL_INFO: {
     "metadata.co2_cost": {

frontend/src/pages/LeaderboardPage/components/Leaderboard/hooks/useDataUtils.js

@@ -6,89 +6,212 @@ import {
 } from "../utils/searchUtils";
 import { ALLOWED_MODELS, isModelAllowed } from "../constants/allowedModels";
 
-// 硬编码数据集
+// MultiFinBen Table 3 hardcoded scores
+const MODEL_TYPES_MAP = {
+  "GPT-4o": "chat", "o3-Mini": "chat", "Deepseek-V3": "chat",
+  "meta-llama/Llama-4-Scout-17B-16E-Instruct": "chat",
+  "meta-llama/Llama-3.1-70B-Instruct": "chat",
+  "google/gemma-3-4b-it": "chat", "google/gemma-3-27b-it": "chat",
+  "Qwen/Qwen2.5-32B-Instruct": "chat", "Qwen/Qwen2.5-Omni-7B": "multimodal",
+  "TheFinAI/finma-7b-full": "fine-tuned",
+  "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": "chat",
+  "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": "fine-tuned",
+  "TheFinAI/FinMA-ES-Bilingual": "fine-tuned", "TheFinAI/plutus-8B-instruct": "fine-tuned",
+  "LLaVA-1.6 Vicuna-13B": "multimodal", "Deepseek-VL-7B-Chat": "multimodal",
+  "Whisper-V3": "multimodal", "Qwen2-Audio-7B": "multimodal",
+  "Qwen2-Audio-7B-Instruct": "multimodal", "SALMONN-7B": "multimodal", "SALMONN-13B": "multimodal"
+};
+
+// Openness classifications per Model Openness Framework (isitopen.ai)
+// GPT-4o and o3-Mini are closed proprietary models (API only, no weights released)
+// All other models have publicly released weights → Class III - Open Model
+const MODEL_OPENNESS_MAP = {
+  "GPT-4o": "Closed", "o3-Mini": "Closed",
+  "Deepseek-V3": "Class III - Open Model",
+  "meta-llama/Llama-4-Scout-17B-16E-Instruct": "Class III - Open Model",
+  "meta-llama/Llama-3.1-70B-Instruct": "Class III - Open Model",
+  "google/gemma-3-4b-it": "Class III - Open Model",
+  "google/gemma-3-27b-it": "Class III - Open Model",
+  "Qwen/Qwen2.5-32B-Instruct": "Class III - Open Model",
+  "Qwen/Qwen2.5-Omni-7B": "Class III - Open Model",
+  "TheFinAI/finma-7b-full": "Class III - Open Model",
+  "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": "Class III - Open Model",
+  "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": "Class III - Open Model",
+  "TheFinAI/FinMA-ES-Bilingual": "Class III - Open Model",
+  "TheFinAI/plutus-8B-instruct": "Class III - Open Model",
+  "LLaVA-1.6 Vicuna-13B": "Class III - Open Model",
+  "Deepseek-VL-7B-Chat": "Class III - Open Model",
+  "Whisper-V3": "Class III - Open Model",
+  "Qwen2-Audio-7B": "Class III - Open Model",
+  "Qwen2-Audio-7B-Instruct": "Class III - Open Model",
+  "SALMONN-7B": "Class III - Open Model",
+  "SALMONN-13B": "Class III - Open Model",
+};
+
+const MODEL_NAMES = [
+  "GPT-4o", "o3-Mini", "Deepseek-V3",
+  "meta-llama/Llama-4-Scout-17B-16E-Instruct",
+  "meta-llama/Llama-3.1-70B-Instruct",
+  "google/gemma-3-4b-it", "google/gemma-3-27b-it",
+  "Qwen/Qwen2.5-32B-Instruct", "Qwen/Qwen2.5-Omni-7B",
+  "TheFinAI/finma-7b-full",
+  "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview",
+  "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese",
+  "TheFinAI/FinMA-ES-Bilingual", "TheFinAI/plutus-8B-instruct",
+  "LLaVA-1.6 Vicuna-13B", "Deepseek-VL-7B-Chat",
+  "Whisper-V3", "Qwen2-Audio-7B",
+  "Qwen2-Audio-7B-Instruct", "SALMONN-7B", "SALMONN-13B"
+];
+
+// Text EN, ZH, JA, ES, EL, BI, MU datasets + averages; Vision + Audio datasets + averages; Modality-Balanced
+export const DATASET_KEYS = [
+  // Text - English
+  'sc', 'finred', 'finer_ord', 'headlines', 'tsa_en', 'xbrl_math',
+  'finqa', 'tatqa', 'ectsum', 'edtsum', 'ccf', 'bigdata22', 'msft',
+  // Text - Chinese
+  'rre', 'aie', 'lne', 'financialiq',
+  // Text - Japanese
+  'chabsa',
+  // Text - Spanish
+  'multifin', 'tsa_es', 'efpa', 'fns_2023',
+  // Text - Greek
+  'grfinnum', 'grfinqa', 'grfns_2023', 'grmultifin',
+  // Text - Bilingual
+  'dolfin',
+  // Text - Multilingual
+  'polyfiqa_easy', 'polyfiqa_expert',
+  // Text Average
+  'text_average',
+  // Vision
+  'englishocr', 'tablebench', 'japaneseocr', 'spanishocr', 'greekocr',
+  'vision_average',
+  // Audio
+  'mdrm_test', 'finaudiosum', 'audio_average',
+  // Modality-Balanced Average
+  'modality_balanced',
+];
+
 const HARDCODED_SCORES = {
-  vision: {
-    "GPT-4o": 55.54, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 16.27,
-    "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 14.97, "google/gemma-3-27b-it": 25.57,
-    "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 24.97, "TheFinAI/finma-7b-full": 0.00,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00,
-    "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "Qwen-VL-MAX": 18.47,
-    "LLaVA-1.6 Vicuna-13B": 19.77, "Deepseek-VL-7B-Chat": 19.10, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  },
-  audio: {
-    "GPT-4o": 55.56, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 0.00,
-    "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 0.00, "google/gemma-3-27b-it": 0.00,
-    "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 48.22, "TheFinAI/finma-7b-full": 0.00,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00,
-    "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 51.58, "Qwen2-Audio-7B": 48.02,
-    "Qwen2-Audio-7B-Instruct": 50.06, "SALMONN-7B": 24.24, "SALMONN-13B": 24.59
-  },
-  english: {
-    "GPT-4o": 42.18, "o3-Mini": 20.20, "Deepseek-V3": 18.04, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 24.16,
-    "meta-llama/Llama-3.1-70B-Instruct": 38.71, "google/gemma-3-4b-it": 16.13, "google/gemma-3-27b-it": 17.19,
-    "Qwen/Qwen2.5-32B-Instruct": 32.01, "Qwen/Qwen2.5-Omni-7B": 24.99, "TheFinAI/finma-7b-full": 28.89,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 29.39, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 26.38,
-    "TheFinAI/FinMA-ES-Bilingual": 31.72, "TheFinAI/plutus-8B-instruct": 27.82, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  },
-  chinese: {
-    "GPT-4o": 60.34, "o3-Mini": 0.00, "Deepseek-V3": 60.94, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 64.51,
-    "meta-llama/Llama-3.1-70B-Instruct": 56.74, "google/gemma-3-4b-it": 26.23, "google/gemma-3-27b-it": 26.24,
-    "Qwen/Qwen2.5-32B-Instruct": 56.62, "Qwen/Qwen2.5-Omni-7B": 53.09, "TheFinAI/finma-7b-full": 24.42,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 23.04, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 13.18,
-    "TheFinAI/FinMA-ES-Bilingual": 21.50, "TheFinAI/plutus-8B-instruct": 31.04, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  },
-  japanese: {
-    "GPT-4o": 0.00, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 48.43,
-    "meta-llama/Llama-3.1-70B-Instruct": 32.17, "google/gemma-3-4b-it": 8.98, "google/gemma-3-27b-it": 23.96,
-    "Qwen/Qwen2.5-32B-Instruct": 4.54, "Qwen/Qwen2.5-Omni-7B": 44.35, "TheFinAI/finma-7b-full": 46.94,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 47.59, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 23.96,
-    "TheFinAI/FinMA-ES-Bilingual": 57.36, "TheFinAI/plutus-8B-instruct": 34.62, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  },
-  spanish: {
-    "GPT-4o": 29.80, "o3-Mini": 4.53, "Deepseek-V3": 25.49, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 47.90,
-    "meta-llama/Llama-3.1-70B-Instruct": 37.84, "google/gemma-3-4b-it": 27.66, "google/gemma-3-27b-it": 27.77,
-    "Qwen/Qwen2.5-32B-Instruct": 37.47, "Qwen/Qwen2.5-Omni-7B": 39.16, "TheFinAI/finma-7b-full": 27.04,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 42.86, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 28.01,
-    "TheFinAI/FinMA-ES-Bilingual": 38.69, "TheFinAI/plutus-8B-instruct": 40.16, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  },
-  greek: {
-    "GPT-4o": 43.04, "o3-Mini": 9.48, "Deepseek-V3": 39.07, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 48.95,
-    "meta-llama/Llama-3.1-70B-Instruct": 43.60, "google/gemma-3-4b-it": 15.45, "google/gemma-3-27b-it": 15.44,
-    "Qwen/Qwen2.5-32B-Instruct": 44.32, "Qwen/Qwen2.5-Omni-7B": 23.45, "TheFinAI/finma-7b-full": 17.93,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 29.49, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 20.91,
-    "TheFinAI/FinMA-ES-Bilingual": 15.47, "TheFinAI/plutus-8B-instruct": 60.19, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  },
-  bilingual: {
-    "GPT-4o": 92.29, "o3-Mini": 90.13, "Deepseek-V3": 86.26, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 89.17,
-    "meta-llama/Llama-3.1-70B-Instruct": 92.13, "google/gemma-3-4b-it": 35.92, "google/gemma-3-27b-it": 35.92,
-    "Qwen/Qwen2.5-32B-Instruct": 92.29, "Qwen/Qwen2.5-Omni-7B": 91.80, "TheFinAI/finma-7b-full": 69.24,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 91.60, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 71.81,
-    "TheFinAI/FinMA-ES-Bilingual": 66.57, "TheFinAI/plutus-8B-instruct": 91.59, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  },
-  multilingual: {
-    "GPT-4o": 6.53, "o3-Mini": 7.80, "Deepseek-V3": 36.99, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 13.52,
-    "meta-llama/Llama-3.1-70B-Instruct": 21.97, "google/gemma-3-4b-it": 0.00, "google/gemma-3-27b-it": 0.00,
-    "Qwen/Qwen2.5-32B-Instruct": 18.48, "Qwen/Qwen2.5-Omni-7B": 16.29, "TheFinAI/finma-7b-full": 3.10,
-    "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 1.76, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 10.25,
-    "TheFinAI/FinMA-ES-Bilingual": 0.35, "TheFinAI/plutus-8B-instruct": 7.24, "Qwen-VL-MAX": 0.00,
-    "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00,
-    "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
-  }
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+  },
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+  },
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+  },
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+  },
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+  },
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+  },
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+  },
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+  },
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+  },
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+  },
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+  },
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+  },
+  financialiq: {
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+  },
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+  },
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+  },
+  tsa_es: {
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+  },
+  efpa: {
+    "GPT-4o": 31.14, "o3-Mini": 0.00, "Deepseek-V3": 18.86, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 67.54, "meta-llama/Llama-3.1-70B-Instruct": 66.67, "google/gemma-3-4b-it": 25.44, "google/gemma-3-27b-it": 25.44, "Qwen/Qwen2.5-32B-Instruct": 65.79, "Qwen/Qwen2.5-Omni-7B": 55.70, "TheFinAI/finma-7b-full": 32.46, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 65.79, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 25.44, "TheFinAI/FinMA-ES-Bilingual": 91.67, "TheFinAI/plutus-8B-instruct": 48.25, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  fns_2023: {
+    "GPT-4o": 25.94, "o3-Mini": 18.11, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 9.61, "meta-llama/Llama-3.1-70B-Instruct": 12.14, "google/gemma-3-4b-it": 0.00, "google/gemma-3-27b-it": 0.00, "Qwen/Qwen2.5-32B-Instruct": 5.93, "Qwen/Qwen2.5-Omni-7B": 7.50, "TheFinAI/finma-7b-full": 1.64, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 5.71, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 10.62, "TheFinAI/FinMA-ES-Bilingual": 1.65, "TheFinAI/plutus-8B-instruct": 9.27, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  grfinnum: {
+    "GPT-4o": 9.18, "o3-Mini": 20.98, "Deepseek-V3": 7.43, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 49.12, "meta-llama/Llama-3.1-70B-Instruct": 46.34, "google/gemma-3-4b-it": 0.00, "google/gemma-3-27b-it": 0.00, "Qwen/Qwen2.5-32B-Instruct": 36.77, "Qwen/Qwen2.5-Omni-7B": 0.40, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 70.06, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  grfinqa: {
+    "GPT-4o": 78.22, "o3-Mini": 0.00, "Deepseek-V3": 50.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 74.22, "meta-llama/Llama-3.1-70B-Instruct": 64.44, "google/gemma-3-4b-it": 22.67, "google/gemma-3-27b-it": 22.67, "Qwen/Qwen2.5-32B-Instruct": 60.44, "Qwen/Qwen2.5-Omni-7B": 48.89, "TheFinAI/finma-7b-full": 25.33, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 57.78, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 28.44, "TheFinAI/FinMA-ES-Bilingual": 23.11, "TheFinAI/plutus-8B-instruct": 64.00, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  grfns_2023: {
+    "GPT-4o": 25.50, "o3-Mini": 16.95, "Deepseek-V3": 37.72, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 16.90, "meta-llama/Llama-3.1-70B-Instruct": 13.61, "google/gemma-3-4b-it": 0.24, "google/gemma-3-27b-it": 0.21, "Qwen/Qwen2.5-32B-Instruct": 9.71, "Qwen/Qwen2.5-Omni-7B": 5.60, "TheFinAI/finma-7b-full": 11.20, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 6.48, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 14.45, "TheFinAI/FinMA-ES-Bilingual": 3.56, "TheFinAI/plutus-8B-instruct": 34.46, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  grmultifin: {
+    "GPT-4o": 59.26, "o3-Mini": 0.00, "Deepseek-V3": 61.11, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 55.56, "meta-llama/Llama-3.1-70B-Instruct": 50.00, "google/gemma-3-4b-it": 38.89, "google/gemma-3-27b-it": 38.89, "Qwen/Qwen2.5-32B-Instruct": 70.37, "Qwen/Qwen2.5-Omni-7B": 38.89, "TheFinAI/finma-7b-full": 35.19, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 53.70, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 40.74, "TheFinAI/FinMA-ES-Bilingual": 35.19, "TheFinAI/plutus-8B-instruct": 72.22, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  dolfin: {
+    "GPT-4o": 92.29, "o3-Mini": 90.13, "Deepseek-V3": 86.26, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 89.17, "meta-llama/Llama-3.1-70B-Instruct": 92.13, "google/gemma-3-4b-it": 35.92, "google/gemma-3-27b-it": 35.92, "Qwen/Qwen2.5-32B-Instruct": 92.29, "Qwen/Qwen2.5-Omni-7B": 91.80, "TheFinAI/finma-7b-full": 69.24, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 91.60, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 71.81, "TheFinAI/FinMA-ES-Bilingual": 66.57, "TheFinAI/plutus-8B-instruct": 91.59, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  polyfiqa_easy: {
+    "GPT-4o": 9.79, "o3-Mini": 9.56, "Deepseek-V3": 34.72, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 27.73, "meta-llama/Llama-3.1-70B-Instruct": 25.04, "google/gemma-3-4b-it": 15.02, "google/gemma-3-27b-it": 14.74, "Qwen/Qwen2.5-32B-Instruct": 19.34, "Qwen/Qwen2.5-Omni-7B": 18.81, "TheFinAI/finma-7b-full": 2.44, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 2.40, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 11.63, "TheFinAI/FinMA-ES-Bilingual": 0.63, "TheFinAI/plutus-8B-instruct": 7.06, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  polyfiqa_expert: {
+    "GPT-4o": 5.31, "o3-Mini": 4.85, "Deepseek-V3": 30.35, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 20.60, "meta-llama/Llama-3.1-70B-Instruct": 18.56, "google/gemma-3-4b-it": 13.83, "google/gemma-3-27b-it": 16.01, "Qwen/Qwen2.5-32B-Instruct": 18.17, "Qwen/Qwen2.5-Omni-7B": 16.35, "TheFinAI/finma-7b-full": 6.38, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.71, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 8.80, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 9.87, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  text_average: {
+    "GPT-4o": 40.98, "o3-Mini": 14.59, "Deepseek-V3": 30.61, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 39.50, "meta-llama/Llama-3.1-70B-Instruct": 42.20, "google/gemma-3-4b-it": 19.34, "google/gemma-3-27b-it": 20.41, "Qwen/Qwen2.5-32B-Instruct": 38.07, "Qwen/Qwen2.5-Omni-7B": 33.06, "TheFinAI/finma-7b-full": 26.83, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 31.24, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 24.40, "TheFinAI/FinMA-ES-Bilingual": 28.95, "TheFinAI/plutus-8B-instruct": 35.53, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  englishocr: {
+    "GPT-4o": 21.38, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 12.39, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 10.70, "google/gemma-3-27b-it": 11.40, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 0.00, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  tablebench: {
+    "GPT-4o": 66.70, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 32.30, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 28.60, "google/gemma-3-27b-it": 60.90, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 74.90, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "LLaVA-1.6 Vicuna-13B": 59.30, "Deepseek-VL-7B-Chat": 57.30, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  japaneseocr: {
+    "GPT-4o": 21.63, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 24.52, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 25.82, "google/gemma-3-27b-it": 26.72, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 21.59, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 9.70, "TheFinAI/plutus-8B-instruct": 6.62, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  spanishocr: {
+    "GPT-4o": 78.55, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 4.12, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 5.60, "google/gemma-3-27b-it": 4.40, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 0.00, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  greekocr: {
+    "GPT-4o": 41.86, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 42.51, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 23.69, "google/gemma-3-27b-it": 30.60, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 0.00, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 8.25, "TheFinAI/plutus-8B-instruct": 6.80, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  vision_average: {
+    "GPT-4o": 46.02, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 23.17, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 18.88, "google/gemma-3-27b-it": 26.80, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 19.30, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "LLaVA-1.6 Vicuna-13B": 15.45, "Deepseek-VL-7B-Chat": 14.14, "Whisper-V3": 0.00, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 0.00, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  mdrm_test: {
+    "GPT-4o": 95.77, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 0.00, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 0.00, "google/gemma-3-27b-it": 0.00, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 96.43, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 97.86, "Qwen2-Audio-7B": 96.03, "Qwen2-Audio-7B-Instruct": 95.32, "SALMONN-7B": 48.48, "SALMONN-13B": 49.17
+  },
+  finaudiosum: {
+    "GPT-4o": 6.30, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 0.00, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 0.00, "google/gemma-3-27b-it": 0.00, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 0.00, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 5.30, "Qwen2-Audio-7B": 0.00, "Qwen2-Audio-7B-Instruct": 4.80, "SALMONN-7B": 0.00, "SALMONN-13B": 0.00
+  },
+  audio_average: {
+    "GPT-4o": 51.04, "o3-Mini": 0.00, "Deepseek-V3": 0.00, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 0.00, "meta-llama/Llama-3.1-70B-Instruct": 0.00, "google/gemma-3-4b-it": 0.00, "google/gemma-3-27b-it": 0.00, "Qwen/Qwen2.5-32B-Instruct": 0.00, "Qwen/Qwen2.5-Omni-7B": 48.22, "TheFinAI/finma-7b-full": 0.00, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 0.00, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 0.00, "TheFinAI/FinMA-ES-Bilingual": 0.00, "TheFinAI/plutus-8B-instruct": 0.00, "LLaVA-1.6 Vicuna-13B": 0.00, "Deepseek-VL-7B-Chat": 0.00, "Whisper-V3": 51.58, "Qwen2-Audio-7B": 48.02, "Qwen2-Audio-7B-Instruct": 50.06, "SALMONN-7B": 24.24, "SALMONN-13B": 24.59
+  },
+  modality_balanced: {
+    "GPT-4o": 46.01, "o3-Mini": 4.86, "Deepseek-V3": 10.20, "meta-llama/Llama-4-Scout-17B-16E-Instruct": 20.89, "meta-llama/Llama-3.1-70B-Instruct": 14.07, "google/gemma-3-4b-it": 12.74, "google/gemma-3-27b-it": 15.74, "Qwen/Qwen2.5-32B-Instruct": 12.69, "Qwen/Qwen2.5-Omni-7B": 33.53, "TheFinAI/finma-7b-full": 8.94, "Duxiaoman-DI/Llama3.1-XuanYuan-FinX1-Preview": 10.41, "cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese": 8.13, "TheFinAI/FinMA-ES-Bilingual": 9.65, "TheFinAI/plutus-8B-instruct": 11.84, "LLaVA-1.6 Vicuna-13B": 5.15, "Deepseek-VL-7B-Chat": 4.71, "Whisper-V3": 17.19, "Qwen2-Audio-7B": 16.01, "Qwen2-Audio-7B-Instruct": 16.69, "SALMONN-7B": 8.08, "SALMONN-13B": 8.20
+  },
 };
 
 // Calculate min/max averages
@@ -127,41 +250,24 @@ export const useProcessedData = (data, averageMode, visibleColumns) => {
     // 直接使用硬编码数据创建模型列表
     const modelList = [];
     
-    // 从HARDCODED_SCORES中获取所有模型名称
-    const modelNames = new Set();
-    Object.values(HARDCODED_SCORES).forEach(categoryData => {
-      Object.entries(categoryData).forEach(([modelName, score]) => {
-        // 添加所有模型，不管分数是否为0
-        modelNames.add(modelName);
-      });
-    });
-    
-    // 为每个模型创建条目
-    Array.from(modelNames).forEach((modelName, index) => {
-      // 创建硬编码评估数据
-      const hardcodedEvaluations = {
-        vision_average: getHardcodedScore(modelName, 'vision'),
-        audio_average: getHardcodedScore(modelName, 'audio'),
-        english_average: getHardcodedScore(modelName, 'english'),
-        chinese_average: getHardcodedScore(modelName, 'chinese'),
-        japanese_average: getHardcodedScore(modelName, 'japanese'),
-        spanish_average: getHardcodedScore(modelName, 'spanish'),
-        greek_average: getHardcodedScore(modelName, 'greek'),
-        bilingual_average: getHardcodedScore(modelName, 'bilingual'),
-        multilingual_average: getHardcodedScore(modelName, 'multilingual')
-      };
-      
-      // 计算总平均分（包含分数为0的类别）
-      const scores = Object.values(hardcodedEvaluations).filter(score => score !== null);
-      const averageScore = scores.length > 0 ? scores.reduce((a, b) => a + b, 0) / scores.length : null;
-      
-      // 创建模型数据
+    // Use modality_balanced as the canonical model list
+    const modelNames = Object.keys(HARDCODED_SCORES.modality_balanced);
+
+    modelNames.forEach((modelName, index) => {
+      const hardcodedEvaluations = Object.fromEntries(
+        DATASET_KEYS.map(key => [key, getHardcodedScore(modelName, key)])
+      );
+
+      // Use modality-balanced average from Table 3 directly
+      const averageScore = getHardcodedScore(modelName, 'modality_balanced');
+
       modelList.push({
         id: `model-${index}`,
         model: {
           name: modelName,
           average_score: averageScore,
-          type: "chat", // 统一设为chat类型
+          type: MODEL_TYPES_MAP[modelName] || "chat",
+          openness: MODEL_OPENNESS_MAP[modelName] || "Class III - Open Model",
         },
         evaluations: hardcodedEvaluations,
         features: {

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

@@ -440,7 +440,7 @@ const BooleanValue = ({ value }) => {
   );
 };
 
-// 为Greek Financial LLM Leaderboard创建自定义标题组件
+// Greek (EL) language text tasks header
 const createGreekLeaderboardHeader = (header) => (
   <Box
     className="header-content"
@@ -452,8 +452,8 @@ const createGreekLeaderboardHeader = (header) => (
     }}
   >
     <HeaderLabel
-      label="Greek Financial LLM Leaderboard"
-      tooltip="Average performance on Greek financial tasks"
+      label="Greek (EL)"
+      tooltip="Average performance on Greek language financial tasks (GRFinNUM, GRFinQA, GRFNS-2023, GRMultiFin)"
       className="header-label"
       isSorted={header?.column?.getIsSorted()}
     />
@@ -467,34 +467,7 @@ const createGreekLeaderboardHeader = (header) => (
         flexShrink: 0,
       }}
     >
-      <InfoIcon tooltip="Average performance on Greek financial tasks" />
-      <Link
-        href="https://huggingface.co/spaces/TheFinAI/Open-Greek-Financial-LLM-Leaderboard#/"
-        target="_blank"
-        rel="noopener noreferrer"
-        aria-label="View Greek Financial LLM Leaderboard"
-        sx={{
-          color: "info.main",
-          display: "flex",
-          alignItems: "center",
-          ml: 0.5,
-          textDecoration: "none",
-          "&:hover": {
-            textDecoration: "underline",
-            "& svg": {
-              opacity: 0.8,
-            },
-          },
-        }}
-      >
-        <OpenInNewIcon
-          sx={{
-            fontSize: "1rem",
-            opacity: 0.6,
-            transition: "opacity 0.2s ease-in-out",
-          }}
-        />
-      </Link>
+      <InfoIcon tooltip="Average performance on Greek language financial tasks (GRFinNUM, GRFinQA, GRFNS-2023, GRMultiFin)" />
     </Box>
   </Box>
 );
@@ -511,7 +484,7 @@ const createLeaderboardHeader = (label, tooltip, linkUrl) => (header) => (
     }}
   >
     <HeaderLabel
-      label={`${label} Leaderboard`}
+      label={label}
       tooltip={tooltip}
       className="header-label"
       isSorted={header?.column?.getIsSorted()}
@@ -873,6 +846,8 @@ export const createColumns = (
       accessorKey: "model.openness",
       header: createHeaderCell("Openness", "Model openness classification"),
       cell: ({ row }) => {
+        const openness = row.original.model.openness || "Class III - Open Model";
+        const isClosed = openness === "Closed";
         return (
           <Box
             sx={{
@@ -881,8 +856,11 @@ export const createColumns = (
               alignItems: "center",
             }}
           >
-            <Typography variant="body2">
-              Class III-Open Model
+            <Typography
+              variant="body2"
+              sx={isClosed ? { color: "text.secondary", fontStyle: "italic" } : {}}
+            >
+              {openness}
             </Typography>
           </Box>
         );
@@ -1011,162 +989,63 @@ export const createColumns = (
     );
   };
 
-  const evaluationColumns = [
-    {
-      accessorKey: "evaluations.greek_average",
-      header: createGreekLeaderboardHeader,
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.greek_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.info.light, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.info.light, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.vision_average",
-      header: createLeaderboardHeader("Vision", "Average performance on vision tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.vision_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.primary.light, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.primary.light, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.audio_average",
-      header: createLeaderboardHeader("Audio", "Average performance on audio tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.audio_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.secondary.light, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.secondary.light, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.english_average",
-      header: createLeaderboardHeader("English", "Average performance on English language tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.english_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.success.light, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.success.light, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.chinese_average",
-      header: createLeaderboardHeader("Chinese", "Average performance on Chinese language tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.chinese_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.warning.light, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.warning.light, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.japanese_average",
-      header: createLeaderboardHeader("Japanese", "Average performance on Japanese language tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.japanese_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.error.light, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.error.light, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.spanish_average",
-      header: createLeaderboardHeader("Spanish", "Average performance on Spanish language tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.spanish_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.info.main, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.info.main, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.bilingual_average",
-      header: createLeaderboardHeader("Bilingual", "Average performance on bilingual tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.bilingual_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.primary.main, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.primary.main, 0.05),
-        }),
-      },
-    },
-    {
-      accessorKey: "evaluations.multilingual_average",
-      header: createLeaderboardHeader("Multilingual", "Average performance on multilingual tasks", null),
-      cell: ({ row, getValue }) => createScoreCell(getValue, row, "evaluations.multilingual_average"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
-      meta: {
-        headerStyle: {
-          backgroundColor: (theme) => alpha(theme.palette.secondary.main, 0.05),
-        },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          backgroundColor: (theme) => alpha(theme.palette.secondary.main, 0.05),
-        }),
-    },
-    }
+  const EVAL_COLUMN_DEFS = [
+    { key: 'sc',               label: 'SC',               tooltip: 'EN Text: SC (Information Extraction)' },
+    { key: 'finred',           label: 'FinRED',           tooltip: 'EN Text: FinRED (Information Extraction)' },
+    { key: 'finer_ord',        label: 'FINER-ORD',        tooltip: 'EN Text: FINER-ORD (Information Extraction)' },
+    { key: 'headlines',        label: 'Headlines',        tooltip: 'EN Text: Headlines (Text Analysis)' },
+    { key: 'tsa_en',           label: 'TSA',              tooltip: 'EN Text: TSA (Text Analysis)' },
+    { key: 'xbrl_math',        label: 'XBRL-Math',        tooltip: 'EN Text: XBRL-Math (Question Answering)' },
+    { key: 'finqa',            label: 'FinQA',            tooltip: 'EN Text: FinQA (Question Answering)' },
+    { key: 'tatqa',            label: 'TATQA',            tooltip: 'EN Text: TATQA (Question Answering)' },
+    { key: 'ectsum',           label: 'ECTSUM',           tooltip: 'EN Text: ECTSUM (Text Generation)' },
+    { key: 'edtsum',           label: 'EDTSUM',           tooltip: 'EN Text: EDTSUM (Text Generation)' },
+    { key: 'ccf',              label: 'CCF',              tooltip: 'EN Text: CCF (Ranking Modeling)' },
+    { key: 'bigdata22',        label: 'BigData22',        tooltip: 'EN Text: BigData22 (Portfolio Optimization)' },
+    { key: 'msft',             label: 'MSFT',             tooltip: 'EN Text: MSFT (Decision Making)' },
+    { key: 'rre',              label: 'RRE',              tooltip: 'ZH Text: RRE (Information Extraction)' },
+    { key: 'aie',              label: 'AIE',              tooltip: 'ZH Text: AIE (Text Analysis)' },
+    { key: 'lne',              label: 'LNE',              tooltip: 'ZH Text: LNE (Text Analysis)' },
+    { key: 'financialiq',      label: 'FinancialIQ',      tooltip: 'ZH Text: FinancialIQ (Question Answering)' },
+    { key: 'chabsa',           label: 'chabsa',           tooltip: 'JA Text: chabsa (Text Analysis)' },
+    { key: 'multifin',         label: 'MultiFin',         tooltip: 'ES Text: MultiFin (Text Analysis)' },
+    { key: 'tsa_es',           label: 'TSA (ES)',         tooltip: 'ES Text: TSA (Text Analysis)' },
+    { key: 'efpa',             label: 'EFPA',             tooltip: 'ES Text: EFPA (Question Answering)' },
+    { key: 'fns_2023',         label: 'FNS-2023',         tooltip: 'ES Text: FNS-2023 (Text Generation)' },
+    { key: 'grfinnum',         label: 'GRFinNUM',         tooltip: 'EL Text: GRFinNUM (Information Extraction)' },
+    { key: 'grfinqa',          label: 'GRFinQA',          tooltip: 'EL Text: GRFinQA (Question Answering)' },
+    { key: 'grfns_2023',       label: 'GRFNS-2023',       tooltip: 'EL Text: GRFNS-2023 (Text Generation)' },
+    { key: 'grmultifin',       label: 'GRMultiFin',       tooltip: 'EL Text: GRMultiFin (Text Analysis)' },
+    { key: 'dolfin',           label: 'DOLFIN',           tooltip: 'BI Text: DOLFIN (Text Generation)' },
+    { key: 'polyfiqa_easy',    label: 'PolyFiQA-Easy',    tooltip: 'MU Text: PolyFiQA-Easy (Question Answering)' },
+    { key: 'polyfiqa_expert',  label: 'PolyFiQA-Expert',  tooltip: 'MU Text: PolyFiQA-Expert (Question Answering)' },
+    { key: 'text_average',     label: 'Text Avg',         tooltip: 'Average performance on text tasks' },
+    { key: 'englishocr',       label: 'EnglishOCR',       tooltip: 'EN Vision: EnglishOCR (Information Extraction)' },
+    { key: 'tablebench',       label: 'TableBench',       tooltip: 'EN Vision: TableBench (Question Answering)' },
+    { key: 'japaneseocr',      label: 'JapaneseOCR',      tooltip: 'JA Vision: JapaneseOCR (Information Extraction)' },
+    { key: 'spanishocr',       label: 'SpanishOCR',       tooltip: 'ES Vision: SpanishOCR (Information Extraction)' },
+    { key: 'greekocr',         label: 'GreekOCR',         tooltip: 'EL Vision: GreekOCR (Information Extraction)' },
+    { key: 'vision_average',   label: 'Vision Avg',       tooltip: 'Average performance on vision tasks' },
+    { key: 'mdrm_test',        label: 'MDRM-test',        tooltip: 'EN Audio: MDRM-test (Text Generation)' },
+    { key: 'finaudiosum',      label: 'FinAudioSum',      tooltip: 'EN Audio: FinAudioSum (Text Generation)' },
+    { key: 'audio_average',    label: 'Audio Avg',        tooltip: 'Average performance on audio tasks' },
+    { key: 'modality_balanced', label: 'Modal. Avg',      tooltip: 'Modality-Balanced Average (mean of text, vision, audio averages)' },
   ];
 
+  const evaluationColumns = EVAL_COLUMN_DEFS.map(({ key, label, tooltip }) => ({
+    accessorKey: `evaluations.${key}`,
+    header: createLeaderboardHeader(label, tooltip, null),
+    cell: ({ row, getValue }) => createScoreCell(getValue, row, `evaluations.${key}`),
+    size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"] || 100,
+    meta: {
+      cellStyle: () => ({
+        position: "relative",
+        overflow: "hidden",
+        padding: "8px 16px",
+      }),
+    },
+  }));
+
   const optionalColumns = [
     {
       accessorKey: "model.architecture",