SOTAVerified

Long-range modeling

A new task for testing the long-sequence modeling capabilities and efficiency of language models.

Image credit: SCROLLS: Standardized CompaRison Over Long Language Sequences

Papers

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Showing 41–50 of 95 papers

TitleStatusHype
U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?Code1
Efficient Long-Text Understanding with Short-Text ModelsCode1
Weakly Supervised Object Localization via Transformer with Implicit Spatial CalibrationCode1
ChordMixer: A Scalable Neural Attention Model for Sequences with Different LengthsCode1
UL2: Unifying Language Learning ParadigmsCode1
Paramixer: Parameterizing Mixing Links in Sparse Factors Works Better than Dot-Product Self-AttentionCode1
SCROLLS: Standardized CompaRison Over Long Language SequencesCode1
Classification of Long Sequential Data using Circular Dilated Convolutional Neural NetworksCode1
LongT5: Efficient Text-To-Text Transformer for Long SequencesCode1
Efficiently Modeling Long Sequences with Structured State SpacesCode1
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