Papers
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Long-Range Dependency Modeling
InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory
Published:2/7/2024
Training-Free Long-Context ModelingEfficiency Enhancement for Large Language ModelsMemory Storage MechanismLong-Range Dependency ModelingContext Window Management
InfLLM introduces a trainingfree memorybased method enabling LLMs to efficiently process long sequences by storing distant contexts in additional memory units. It achieves competitive performance without costly finetuning and captures longdistance dependencies effectively.
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Transformer-XL: Attentive Language Models beyond a Fixed-Length Context
Published:7/1/2019
Transformer-XL ArchitectureLong-Range Dependency ModelingLanguage ModelingContext Fragmentation ResolutionPositional Encoding Scheme
The paper presents TransformerXL, a novel neural architecture that overcomes fixedlength context limitations in language modeling through a segmentlevel recurrence mechanism and a new positional encoding scheme, significantly outperforming traditional models with up to 1,800 t
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Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement
Published:3/13/2023
Low-Light Image EnhancementRetinex-Based TransformerIllumination-Guided ModelLong-Range Dependency ModelingImage Quality Assessment
This paper introduces a novel onestage Retinex framework (ORF) for lowlight image enhancement. By estimating illumination and restoring corruptions, combined with an IlluminationGuided Transformer (IGT), Retinexformer outperforms stateoftheart methods significantly across b
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