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Question Answering on SQuAD (EM/F1)

89.8F1SMP-S
61.439268.802176.16583.5279Oct 12, 2022May 17, 2023Dec 21, 2023Jul 26, 2024Feb 28, 2025Oct 4, 2025May 10, 2026

Evaluation results

MethodLinks
SMP-SRemaining Weights=50%, Knowledge Distillation=true2022.1089.882.8
SMP-LRemaining Weights=50%, Knowledge Distillation=true2022.1089.482.2
Prompt tuningBackbone=Llama-3.2-3B-Base, Evaluation Protocol=Prompt tuning, Context Setting=w/ context2026.0288.4180.39
Standard MHAMemory (GB)=15.22025.1288.4—
CAPRemaining Weights=50%, Knowledge Distillation=true2022.1088.280.9
MAHAMemory (GB)=6.72025.1288.2—
BERT baseRemaining Weights=100%, Knowledge Distillation=false2022.1088.180.4
BigBirdMemory (GB)=10.32025.1287.9—
MovementRemaining Weights=50%, Knowledge Distillation=true2022.1087.679.8
LongformerMemory (GB)=9.12025.1287.6—
SMP-SRemaining Weights=10%, Knowledge Distillation=true2022.1087.279.3
SMP-LRemaining Weights=10%, Knowledge Distillation=true2022.1086.978.9
PerformerMemory (GB)=8.52025.1286.7—
CAPRemaining Weights=10%, Knowledge Distillation=true2022.1085.677.1
S-STEParams=774M, Pre-train=S-STE, Fine-tune=S-STE2024.0985.575.5
ReformerMemory (GB)=7.82025.1285.2—
COIECDModel=FLAN-T5-3B2024.0284.9973.84
Soft-MovementRemaining Weights=10%, Knowledge Distillation=true2022.1084.976.6
DenseParams=774M, Pre-train=Dense, Fine-tune=Dense2024.0984.974.3
SMP-SRemaining Weights=10%, Knowledge Distillation=false2022.1084.675.1
T-SR-STE+DFParams=774M, Pre-train=T-SR-STE+DF [20], Fine-tune=Dense2024.0984.674.3
SMP-LRemaining Weights=10%, Knowledge Distillation=false2022.1084.375
MovementRemaining Weights=10%, Knowledge Distillation=true2022.1084.375.6
SMP-SRemaining Weights=3%, Knowledge Distillation=true2022.1084.175
DenseParams=350M, Pre-train=Dense, Fine-tune=Dense2024.0983.673.2
RegularModel=FLAN-T5-3B2024.0283.5371.2
SMP-LRemaining Weights=3%, Knowledge Distillation=true2022.1083.474
SCModel=FLAN-T5-3B2024.0283.2870.9
CDModel=FLAN-T5-3B2024.0283.171.25
CAPRemaining Weights=3%, Knowledge Distillation=true2022.108373.8
DeBERTa-V3 base + PiFiModel Backbone=DeBERTa-V3-base, PiFi Integration=true, Source LLM=Llama-3.1-8B2025.0682.8369.87
S-STEParams=350M, Pre-train=S-STE, Fine-tune=S-STE2024.0982.772.2
T-SR-STEParams=350M, Pre-train=T-SR-STE, Fine-tune=Dense2024.0982.672.3
DeBERTa-V3 baseModel Backbone=DeBERTa-V3-base2025.0682.4969.4
T-SR-STE+DFParams=350M, Pre-train=T-SR-STE+DF [20], Fine-tune=Dense2024.0982.471.9
SR-STEParams=350M, Pre-train=SR-STE, Fine-tune=Dense2024.0982.472
Soft-MovementRemaining Weights=3%, Knowledge Distillation=true2022.1082.372.7
L0-regularizationRemaining Weights=10%, Knowledge Distillation=true2022.1081.972.4
CADModel=FLAN-T5-3B2024.0281.8868.62
MovementRemaining Weights=10%, Knowledge Distillation=false2022.1081.771.9
DeBERTa base + PiFiModel Backbone=DeBERTa-base, PiFi Integration=true, Source LLM=Llama-3.1-8B2025.0681.5269.65
Soft-MovementRemaining Weights=10%, Knowledge Distillation=false2022.1081.571.3
SMP-SRemaining Weights=3%, Knowledge Distillation=false2022.1081.470.9
Prompt tuningBackbone=Llama-3.2-1B-Base, Evaluation Protocol=Prompt tuning, Context Setting=w/ context2026.0281.0971.89
SMP-LRemaining Weights=3%, Knowledge Distillation=false2022.108170.7
DeBERTa baseModel Backbone=DeBERTa-base2025.0680.9467.87
RoBERTa base + PiFiModel Backbone=RoBERTa-base, PiFi Integration=true, Source LLM=Llama-3.1-8B2025.0680.8968.97
ELECTRA base + PiFiModel Backbone=ELECTRA-base, PiFi Integration=true, Source LLM=Llama-3.1-8B2025.0680.4567.99
ELSAalpha_hat=0.22026.0180.4488.04
MagnitudeRemaining Weights=10%, Knowledge Distillation=true2022.1080.170.2
RoBERTa baseModel Backbone=RoBERTa-base2025.0680.0668.09
FedCAdaalpha_hat=0.22026.0180.0387.29
Soft-MovementRemaining Weights=3%, Knowledge Distillation=false2022.1079.969.5
w/ ContextCompression Rate=1x2026.0279.8159.97
RoFedalpha_hat=0.22026.0179.3387.16
ELSAalpha_hat=0.12026.0179.2487.17
OURS (PIC)Compression Rate=4x, Parameter Size=0.5B2026.0279.0360.14
FedProxalpha_hat=0.22026.0179.0187.7
RaSAalpha_hat=0.22026.0178.9986.95
DenseParams=124M, Pre-train=Dense, Fine-tune=Dense2024.0978.867.6
S-STEParams=124M, Pre-train=S-STE, Fine-tune=S-STE2024.0978.868
FedCAdaalpha_hat=0.12026.0178.5286.45
T-SR-STE+DFParams=124M, Pre-train=T-SR-STE+DF [20], Fine-tune=Dense2024.0978.567.5
RoFedalpha_hat=0.12026.0178.586.55
RaSAalpha_hat=0.12026.0178.3886.79
FedProxalpha_hat=0.12026.0178.3387.31
BERT base + PiFiModel Backbone=BERT-base, PiFi Integration=true, Source LLM=Llama-3.1-8B2025.0678.0966.17
FedAMSalpha_hat=0.22026.0178.0287.05
MovementRemaining Weights=3%, Knowledge Distillation=true2022.107867.5
PCC-LargeCompression Rate=4x, Parameter Size=8B2026.0277.7660.04
Llama 3.3 70BModel Size=70B2025.0177.766.2
FedAMSalpha_hat=0.12026.0177.6686.21
SR-STEParams=124M, Pre-train=SR-STE, Fine-tune=Dense2024.0977.566.2
FedAvgalpha_hat=0.22026.0177.2287.72
T-SR-STEParams=124M, Pre-train=T-SR-STE, Fine-tune=Dense2024.0977.266.3
FedAvgalpha_hat=0.12026.0176.9287.06
FedAvg (Random)alpha_hat=0.22026.0176.5285.98
MovementRemaining Weights=3%, Knowledge Distillation=false2022.1076.365.2
BERT baseModel Backbone=BERT-base2025.0676.0663.81
PCC-LiteCompression Rate=4x, Parameter Size=0.77B2026.0275.8357.44
ComprExITBackbone=Llama-3.2-3B-Base, Evaluation Protocol=Context Compression2026.0275.6859.26
FedAvg (Random)alpha_hat=0.12026.0175.3385.66
Llama 3.2 3BModel Size=3B2025.0173.360.7
BeaconBackbone=Llama-3.2-3B-Base, Evaluation Protocol=Context Compression2026.0272.6559.81
COIECDModel=LLaMA2-13B2024.0270.8657.1
SeCoBackbone=LLaMA-3.2-1B-Instruct, Compression constraint=16x2026.0570.7151.06
CADModel=LLaMA2-13B2024.0270.5256.46
ATACompressor2026.0370.5252.1
SeCoBackbone=LLaMA-3.2-1B-Instruct, Compression constraint=32x2026.0569.4750.34
RegularModel=LLaMA2-13B2024.0268.9254.46
SCModel=LLaMA2-13B2024.0268.8554.55
ComprExITBackbone=Llama-3.2-1B-Base, Evaluation Protocol=Context Compression2026.0268.0851.38
CDModel=LLaMA2-13B2024.0268.0453.89
500xBackbone=Llama-3.2-3B-Base, Evaluation Protocol=Context Compression2026.0265.5652.08
SeCoBackbone=Qwen3-4B-Instruct, Compression constraint=16x2026.0565.5644.98
ProbeRAGArchitecture=LLaMA-2-7B-Chat-HF2025.1065.452.1
GeAR2025.0164.560
SeCoBackbone=Qwen3-4B-Instruct, Compression constraint=32x2026.0563.4642.96
CANOEArchitecture=LLaMA-2-7B-Chat-HF2025.1063.245.6
ICAEBackbone=Llama-3.2-3B-Base, Evaluation Protocol=Context Compression2026.0262.5348.51