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Large Language Models - Will They Keep Getting Bigger?
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- 1 Introduction
- 2 What are language models
- 3 Modern NLP
- 4 Scaling
- 5 sparse models
- 6 Gshard
- 7 Base Layers
- 8 Formal Optimization
- 9 Algorithmic Optimization
- 10 Experiments
- 11 Comparison
- 12 Benefits
- 13 Dmxlayers
- 14 Representations
- 15 Simple routing
- 16 Training time
- 17 Parallel training
- 18 Data curation
- 19 Unrealistic setting
- 20 Domain structure
- 21 Inference procedure
- 22 Perplexity numbers
- 23 Modularity
- 24 Remove experts
- 25 Summary
- 26 Generic language models
- 27 Hot dog example
- 28 Hot pan example
- 29 Common sense example
- 30 Large language models
- 31 The fundamental challenge
- 32 Surface form competition
- 33 Flip the reasoning
- 34 Key intuition
- 35 Noisey channel models
- 36 Finetuning
- 37 Scoring Strings
- 38 Web Crawls
- 39 Example Output
- 40 Structure Data
- 41 Efficiency
- 42 Questions
- 43 Density estimation
- 44 Better training objectives
- 45 Optimization
- 46 Probability
- 47 Induction
- 48 multimodality
- 49 outliers
- 50 compute vs data
