stereoplegic
's Collections
Context compression
updated
In-Context Learning Creates Task Vectors
Paper
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2310.15916
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Published
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41
When can transformers reason with abstract symbols?
Paper
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2310.09753
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Published
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2
Improving Length-Generalization in Transformers via Task Hinting
Paper
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2310.00726
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Published
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1
In-context Autoencoder for Context Compression in a Large Language Model
Paper
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2307.06945
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Published
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27
Adapting Language Models to Compress Contexts
Paper
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2305.14788
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Published
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1
Context Compression for Auto-regressive Transformers with Sentinel
Tokens
Paper
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2310.08152
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Published
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1
Learning to Compress Prompts with Gist Tokens
Paper
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2304.08467
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Published
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3
Dynamic Context Pruning for Efficient and Interpretable Autoregressive
Transformers
Paper
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2305.15805
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Published
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1
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM
Inference with Transferable Prompt
Paper
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2305.11186
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Published
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1
Self-slimmed Vision Transformer
Paper
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2111.12624
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Published
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1
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time
Paper
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2310.17157
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Published
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11
RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective
Augmentation
Paper
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2310.04408
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Published
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1
Dynamic Token Pruning in Plain Vision Transformers for Semantic
Segmentation
Paper
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2308.01045
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Published
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1
Adaptive Token Sampling For Efficient Vision Transformers
Paper
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2111.15667
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Published
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1
Dynamic Token-Pass Transformers for Semantic Segmentation
Paper
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2308.01944
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Published
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1
Multi-Scale And Token Mergence: Make Your ViT More Efficient
Paper
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2306.04897
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Published
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1
Sparsifiner: Learning Sparse Instance-Dependent Attention for Efficient
Vision Transformers
Paper
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2303.13755
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Published
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1
Nugget 2D: Dynamic Contextual Compression for Scaling Decoder-only
Language Models
Paper
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2310.02409
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Published
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1
LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive
Prompt-Based Few-Shot Fine-Tuning
Paper
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2305.18169
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Published
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1
ComputeGPT: A computational chat model for numerical problems
Paper
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2305.06223
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Published
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1
XPrompt: Exploring the Extreme of Prompt Tuning
Paper
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2210.04457
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Published
•
1
Reducing Sequence Length by Predicting Edit Operations with Large
Language Models
Paper
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2305.11862
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Published
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1
Diet Code Is Healthy: Simplifying Programs for Pre-trained Models of
Code
Paper
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2206.14390
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Published
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1
Split, Encode and Aggregate for Long Code Search
Paper
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2208.11271
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Published
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1
Recursively Summarizing Enables Long-Term Dialogue Memory in Large
Language Models
Paper
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2308.15022
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Published
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2
Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing
Important Tokens
Paper
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2305.04241
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Published
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1
Latency Adjustable Transformer Encoder for Language Understanding
Paper
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2201.03327
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Published
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1
Block-Skim: Efficient Question Answering for Transformer
Paper
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2112.08560
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Published
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1
Learned Token Pruning for Transformers
Paper
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2107.00910
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Published
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1
Zero-TPrune: Zero-Shot Token Pruning through Leveraging of the Attention
Graph in Pre-Trained Transformers
Paper
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2305.17328
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Published
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2
Learned Thresholds Token Merging and Pruning for Vision Transformers
Paper
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2307.10780
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Published
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1
Can the Inference Logic of Large Language Models be Disentangled into
Symbolic Concepts?
Paper
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2304.01083
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Published
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1
System 2 Attention (is something you might need too)
Paper
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2311.11829
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Published
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39
CoLT5: Faster Long-Range Transformers with Conditional Computation
Paper
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2303.09752
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Published
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2
Random-LTD: Random and Layerwise Token Dropping Brings Efficient
Training for Large-scale Transformers
Paper
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2211.11586
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Published
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1
TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for
Inference Cost Reduction
Paper
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2310.15556
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Published
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1
Extending Context Window of Large Language Models via Semantic
Compression
Paper
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2312.09571
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Published
•
12
LLoCO: Learning Long Contexts Offline
Paper
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2404.07979
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Published
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20
SelfCP: Compressing Long Prompt to 1/12 Using the Frozen Large Language
Model Itself
Paper
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2405.17052
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Published
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1
Equipping Transformer with Random-Access Reading for Long-Context
Understanding
Paper
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2405.13216
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Published