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Token Reduction

Papers

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Showing 26–50 of 78 papers

TitleStatusHype
FOLDER: Accelerating Multi-modal Large Language Models with Enhanced PerformanceCode1
Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMsCode1
Learning Compact Vision Tokens for Efficient Large Multimodal ModelsCode1
Inference Optimal VLMs Need Fewer Visual Tokens and More ParametersCode1
AdaViT: Adaptive Tokens for Efficient Vision TransformerCode1
Dynamic Compressing Prompts for Efficient Inference of Large Language ModelsCode0
Attend to Not Attended: Structure-then-Detail Token Merging for Post-training DiT AccelerationCode0
BatchGEMBA: Token-Efficient Machine Translation Evaluation with Batched Prompting and Prompt CompressionCode0
Cached Adaptive Token Merging: Dynamic Token Reduction and Redundant Computation Elimination in Diffusion ModelCode0
Cross-Layer Cache Aggregation for Token Reduction in Ultra-Fine-Grained Image RecognitionCode0
Faster Parameter-Efficient Tuning with Token Redundancy ReductionCode0
HaltingVT: Adaptive Token Halting Transformer for Efficient Video RecognitionCode0
Layton: Latent Consistency Tokenizer for 1024-pixel Image Reconstruction and Generation by 256 TokensCode0
Learning to Merge Tokens via Decoupled Embedding for Efficient Vision TransformersCode0
Not All Tokens Are What You Need In ThinkingCode0
Rethinking Token Reduction with Parameter-Efficient Fine-Tuning in ViT for Pixel-Level TasksCode0
Astraea: A GPU-Oriented Token-wise Acceleration Framework for Video Diffusion Transformers—0
Hypernym Mercury: Token Optimization Through Semantic Field Constriction And Reconstruction From Hypernyms. A New Text Compression Method—0
freePruner: A Training-free Approach for Large Multimodal Model Acceleration—0
Local Information Matters: Inference Acceleration For Grounded Conversation Generation Models Through Adaptive Local-Aware Token Pruning—0
FIT-RAG: Black-Box RAG with Factual Information and Token Reduction—0
MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction—0
AdaFV: Rethinking of Visual-Language alignment for VLM acceleration—0
Efficient Multi-modal Large Language Models via Visual Token Grouping—0
Efficient LLaMA-3.2-Vision by Trimming Cross-attended Visual Features—0
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