Spaces:
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Update leaderboard
Browse files- app.py +4 -4
- constants.py +5 -3
- data.csv +106 -63
app.py
CHANGED
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@@ -31,13 +31,13 @@ def get_data(verified, dataset, ipc, label_type, metric_weights=None):
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data["score"] = data[METRICS[0].lower()] * 0.0
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for i, metric in enumerate(METRICS):
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data["score"] += data[metric.lower()] * metric_weights[i] * METRICS_SIGN[i]
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data["score"] = (np.exp(-0.01 * data["score"]) - np.exp(-1.0)) / (np.exp(1.0) - np.exp(-1.0))
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data = data.sort_values(by="score", ascending=False)
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data["ranking"] = range(1, len(data) + 1)
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for metric in METRICS:
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data[metric.lower()] = data[metric.lower()].apply(lambda x: round(x, 3))
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data["score"] = data["score"].apply(lambda x: round(x,
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# formatting
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data["method"] = "[" + data["method"] + "](" + data["method_reference"] + ")"
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@@ -45,9 +45,9 @@ def get_data(verified, dataset, ipc, label_type, metric_weights=None):
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data = data.drop(columns=["method_reference", "dataset", "ipc"])
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data = data[['ranking', 'method', 'verified', 'date', 'label_type', 'hlr', 'ior', 'score']]
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if label_type == "Hard Label":
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data = data.rename(columns={"ranking": "Ranking", "method": "Method", "date": "Date", "label_type": "Label Type", "hlr": "HLR%↓", "ior": "IOR%↑", "score": "
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else:
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data = data.rename(columns={"ranking": "Ranking", "method": "Method", "date": "Date", "label_type": "Label Type", "hlr": "HLR%↓", "ior": "IOR%↑", "score": "
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return data
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data["score"] = data[METRICS[0].lower()] * 0.0
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for i, metric in enumerate(METRICS):
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data["score"] += data[metric.lower()] * metric_weights[i] * METRICS_SIGN[i]
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data["score"] = 100 * (np.exp(-0.01 * data["score"]) - np.exp(-1.0)) / (np.exp(1.0) - np.exp(-1.0))
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data = data.sort_values(by="score", ascending=False)
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data["ranking"] = range(1, len(data) + 1)
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for metric in METRICS:
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data[metric.lower()] = data[metric.lower()].apply(lambda x: round(x, 3))
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data["score"] = data["score"].apply(lambda x: round(x, 1))
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# formatting
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data["method"] = "[" + data["method"] + "](" + data["method_reference"] + ")"
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data = data.drop(columns=["method_reference", "dataset", "ipc"])
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data = data[['ranking', 'method', 'verified', 'date', 'label_type', 'hlr', 'ior', 'score']]
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if label_type == "Hard Label":
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data = data.rename(columns={"ranking": "Ranking", "method": "Method", "date": "Date", "label_type": "Label Type", "hlr": "HLR%↓", "ior": "IOR%↑", "score": "LRS%↑", "verified": "Verified"})
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else:
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data = data.rename(columns={"ranking": "Ranking", "method": "Method", "date": "Date", "label_type": "Label Type", "hlr": "HLR%↓", "ior": "IOR%↑", "score": "LRS%↑", "verified": "Verified"})
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return data
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constants.py
CHANGED
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@@ -79,24 +79,26 @@ $\\text{HLR} = \\text{Acc.} \\text{full-hard} - \\text{Acc.} \\text{syn-hard}$:
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$\\text{IOR} = \\text{Acc.} \\text{syn-any} - \\text{Acc.} \\text{rdm-any}$: The improvement over random selection when using personalized evaluation methods (improvement over random).
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"""
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DATASET_LIST = ["CIFAR-10", "CIFAR-100", "Tiny-ImageNet"]
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IPC_LIST = ["IPC-1", "IPC-10", "IPC-50"]
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DATASET_IPC_LIST = {
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"CIFAR-10": ["IPC-1", "IPC-10", "IPC-50"],
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"CIFAR-100": ["IPC-1", "IPC-10", "IPC-50"],
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"Tiny-ImageNet": ["IPC-1", "IPC-10"],
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}
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LABEL_TYPE_LIST = ["Hard Label", "Soft Label"]
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METRICS = ["HLR", "IOR"]
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METRICS_SIGN = [1.0, -1.0]
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COLUMN_NAMES = ["Ranking", "Method", "Verified", "Date", "Label Type", "HLR%", "IOR%", "
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DATA_TITLE_TYPE = ['number', 'markdown', 'markdown', 'markdown', 'markdown', 'number', 'number', 'number']
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DATASET_MAPPING = {
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"CIFAR-10": 0,
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"CIFAR-100": 1,
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"Tiny-ImageNet": 2,
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}
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IPC_MAPPING = {
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$\\text{IOR} = \\text{Acc.} \\text{syn-any} - \\text{Acc.} \\text{rdm-any}$: The improvement over random selection when using personalized evaluation methods (improvement over random).
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"""
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DATASET_LIST = ["CIFAR-10", "CIFAR-100", "Tiny-ImageNet", "ImageNet1K"]
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IPC_LIST = ["IPC-1", "IPC-10", "IPC-50"]
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DATASET_IPC_LIST = {
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"CIFAR-10": ["IPC-1", "IPC-10", "IPC-50"],
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"CIFAR-100": ["IPC-1", "IPC-10", "IPC-50"],
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"Tiny-ImageNet": ["IPC-1", "IPC-10", "IPC-50"],
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"ImageNet1K": ["IPC-1", "IPC-10", "IPC-50"],
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}
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LABEL_TYPE_LIST = ["Hard Label", "Soft Label"]
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METRICS = ["HLR", "IOR"]
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METRICS_SIGN = [1.0, -1.0]
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COLUMN_NAMES = ["Ranking", "Method", "Verified", "Date", "Label Type", "HLR%", "IOR%", "LRS"]
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DATA_TITLE_TYPE = ['number', 'markdown', 'markdown', 'markdown', 'markdown', 'number', 'number', 'number']
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DATASET_MAPPING = {
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"CIFAR-10": 0,
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"CIFAR-100": 1,
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"Tiny-ImageNet": 2,
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"ImageNet1K": 3,
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}
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IPC_MAPPING = {
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data.csv
CHANGED
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@@ -1,71 +1,114 @@
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method,method_reference,verified,date,dataset,ipc,label_type,hlr,ior
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DATM,https://arxiv.org/abs/2310.05773,1,2025-
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DC,https://arxiv.org/abs/2006.05929,1,2025-
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DSA,https://arxiv.org/abs/2102.08259,1,2025-
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DM,https://arxiv.org/abs/2110.04181,1,2025-
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MTT,https://arxiv.org/abs/2203.11932,1,2025-
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DATM,https://arxiv.org/abs/2310.05773,1,2025-
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method,method_reference,verified,date,dataset,ipc,label_type,hlr,ior
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,0,0,0,52.7,12.4
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DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,0,0,0,58.9,13.2
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DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,0,0,0,61.4,8.7
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MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,0,0,0,42.2,27.6
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DataDAM,https://arxiv.org/abs/2310.00093,1,2025-05-30,0,0,0,49.9,15.6
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DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,0,0,1,41.9,30.8
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SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,0,0,1,69.9,-0.3
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RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,0,0,1,60.6,2.4
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D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,0,0,1,51.1,6.7
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,0,1,0,36.7,18.5
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DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,0,1,0,35.1,19.6
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DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,0,1,0,39.3,16.1
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MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,0,1,0,23.7,30.9
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DataDAM,https://arxiv.org/abs/2310.00093,1,2025-05-30,0,1,0,34.8,19.9
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DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,0,1,1,26.8,35.1
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SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,0,1,1,67.8,-5.7
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RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,0,1,1,50.7,1.1
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D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,0,1,1,39.9,9.1
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,0,2,0,26.3,12.3
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DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,0,2,0,27.4,11.0
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DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,0,2,0,25.1,12.7
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MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,0,2,0,16.5,20.5
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DataDAM,https://arxiv.org/abs/2310.00093,1,2025-05-30,0,2,0,21.9,15.8
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DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,0,2,1,18.9,23.9
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SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,0,2,1,62.9,-6.5
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RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,0,2,1,36.0,-1.6
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D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,0,2,1,27.0,6.6
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,1,0,0,39.4,8.4
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DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,1,0,0,46.0,8.5
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DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,1,0,0,48.0,6.1
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MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,1,0,0,35.2,16.7
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DataDAM,https://arxiv.org/abs/2310.00093,1,2025-05-30,1,0,0,45.2,9.1
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DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,1,0,1,24.1,18.5
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SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,1,0,1,52.7,-1.9
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RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,1,0,1,45.6,-0.5
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D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,1,0,1,30.9,10.0
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,1,1,0,25.5,12.7
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DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,1,1,0,26.1,13.5
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DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,1,1,0,30.1,10.7
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MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,1,1,0,18.0,20.7
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DataDAM,https://arxiv.org/abs/2310.00093,1,2025-05-30,1,1,0,25.9,14.8
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DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,1,1,1,18.9,18.4
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SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,1,1,1,50.5,-14.8
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RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,1,1,1,37.5,-1.2
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D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,1,1,1,40.1,9.7
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,1,2,0,21.8,1.1
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DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,1,2,0,21.2,2.0
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DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,1,2,0,16.6,7.2
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MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,1,2,0,12.1,11.6
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DataDAM,https://arxiv.org/abs/2310.00093,1,2025-05-30,1,2,0,12.4,11.8
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DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,1,2,1,10.3,26.1
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SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,1,2,1,46.2,-13.6
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RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,1,2,1,27.3,-1.5
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D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,1,2,1,26.7,13.5
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,2,0,0,28.6,3.9
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DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,2,0,0,30.3,3.7
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DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,2,0,0,36.7,2.3
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MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,2,0,0,30.7,5.8
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DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,2,0,1,25.4,8.6
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EDF,https://arxiv.org/abs/2410.17193,1,2025-05-30,2,0,1,25.8,9.2
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SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,2,0,1,45.6,-1.8
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RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,2,0,1,34.0,3.9
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D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,2,0,1,40.6,-3.0
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DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,2,1,0,21.5,7.1
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| 73 |
+
DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,2,1,0,20.3,6.8
|
| 74 |
+
DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,2,1,0,26.2,7.5
|
| 75 |
+
MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,2,1,0,15.6,14.6
|
| 76 |
+
DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,2,1,1,18.3,14.2
|
| 77 |
+
EDF,https://arxiv.org/abs/2410.17193,1,2025-05-30,2,1,1,18.5,15.4
|
| 78 |
+
SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,2,1,1,43.6,-8.5
|
| 79 |
+
RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,2,1,1,25.6,1.8
|
| 80 |
+
D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,2,1,1,35.6,-5.8
|
| 81 |
+
|
| 82 |
+
DC,https://arxiv.org/abs/2006.05929,1,2025-05-30,2,2,0,21.3,-2.1
|
| 83 |
+
DSA,https://arxiv.org/abs/2102.08259,1,2025-05-30,2,2,0,17.6,7.6
|
| 84 |
+
DM,https://arxiv.org/abs/2110.04181,1,2025-05-30,2,2,0,18.9,5.3
|
| 85 |
+
MTT,https://arxiv.org/abs/2203.11932,1,2025-05-30,2,2,0,15.6,10.2
|
| 86 |
+
DATM,https://arxiv.org/abs/2310.05773,1,2025-05-30,2,2,1,13.5,15.1
|
| 87 |
+
EDF,https://arxiv.org/abs/2410.17193,1,2025-05-30,2,2,1,13.8,15.9
|
| 88 |
+
SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,2,2,1,33.6,-9.6
|
| 89 |
+
RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,2,2,1,15.2,-0.6
|
| 90 |
+
D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,2,2,1,27.7,12.8
|
| 91 |
+
|
| 92 |
+
SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,3,0,1,56.3,-1.5
|
| 93 |
+
RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,3,0,1,55.7,1.6
|
| 94 |
+
D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,3,0,1,55.9,-0.6
|
| 95 |
+
DWA,https://arxiv.org/abs/2409.17612,1,2025-05-30,3,0,1,56.1,-1.2
|
| 96 |
+
CDA,https://arxiv.org/abs/2311.18838,1,2025-05-30,3,0,1,56.2,-2.5
|
| 97 |
+
EDC,https://arxiv.org/abs/2404.13733,1,2025-05-30,3,0,1,55.7,-0.8
|
| 98 |
+
G-VBSM,https://arxiv.org/abs/2311.17950,1,2025-05-30,3,0,1,56.3,-1.2
|
| 99 |
+
|
| 100 |
+
SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,3,1,1,55.0,-15.6
|
| 101 |
+
RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,3,1,1,50.2,-0.6
|
| 102 |
+
D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,3,1,1,53.0,-7.7
|
| 103 |
+
DWA,https://arxiv.org/abs/2409.17612,1,2025-05-30,3,1,1,54.4,-4.1
|
| 104 |
+
CDA,https://arxiv.org/abs/2311.18838,1,2025-05-30,3,1,1,54.9,-8.6
|
| 105 |
+
EDC,https://arxiv.org/abs/2404.13733,1,2025-05-30,3,1,1,52.0,-0.4
|
| 106 |
+
G-VBSM,https://arxiv.org/abs/2311.17950,1,2025-05-30,3,1,1,55.0,-7.3
|
| 107 |
+
|
| 108 |
+
SRe2L,https://arxiv.org/abs/2306.13092,1,2025-05-30,3,1,1,53.4,-13.2
|
| 109 |
+
RDED,https://arxiv.org/abs/2312.03526,1,2025-05-30,3,1,1,39.8,-3.6
|
| 110 |
+
D4M,https://arxiv.org/abs/2407.15138,1,2025-05-30,3,1,1,43.7,-5.8
|
| 111 |
+
DWA,https://arxiv.org/abs/2409.17612,1,2025-05-30,3,1,1,49.7,-7.8
|
| 112 |
+
CDA,https://arxiv.org/abs/2311.18838,1,2025-05-30,3,1,1,52.0,-6.7
|
| 113 |
+
EDC,https://arxiv.org/abs/2404.13733,1,2025-05-30,3,1,1,41.3,-0.1
|
| 114 |
+
G-VBSM,https://arxiv.org/abs/2311.17950,1,2025-05-30,3,1,1,44.9,-5.9
|