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csinva · Dec 1, 2023 · 78b43b1 · 78b43b1
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 | Model                       | Reference                                                    | Output  | Description                                                  |
 | :-------------------------- | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ |
-| Tree-Prompt            | [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/tree_prompt.ipynb), [🗂️](http://csinva.io/imodelsX/treeprompt/treeprompt.html), [🔗](https://github.com/csinva/tree-prompt/tree/main), [📄]() | Explanation<br/>+ Steering | Generates a tree of prompts to<br/>steer an LLM (*Official*) |
-| iPrompt            | [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/iprompt.ipynb), [🗂️](http://csinva.io/imodelsX/iprompt/api.html#imodelsx.iprompt.api.explain_dataset_iprompt), [🔗](https://github.com/csinva/interpretable-autoprompting), [📄](https://arxiv.org/abs/2210.01848) | Explanation<br/>+ Steering | Generates a prompt that<br/>explains patterns in data (*Official*) |
+| Tree-Prompt            | [🗂️](http://csinva.io/imodelsX/treeprompt/treeprompt.html), [🔗](https://github.com/csinva/tree-prompt/tree/main), [📄](https://arxiv.org/abs/2310.14034), [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/tree_prompt.ipynb),  | Explanation<br/>+ Steering | Generates a tree of prompts to<br/>steer an LLM (*Official*) |
+| iPrompt            | [🗂️](http://csinva.io/imodelsX/iprompt/api.html#imodelsx.iprompt.api.explain_dataset_iprompt), [🔗](https://github.com/csinva/interpretable-autoprompting), [📄](https://arxiv.org/abs/2210.01848), [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/iprompt.ipynb) | Explanation<br/>+ Steering | Generates a prompt that<br/>explains patterns in data (*Official*) |
 | AutoPrompt            | ㅤㅤ[🗂️](), [🔗](https://github.com/ucinlp/autoprompt), [📄](https://arxiv.org/abs/2010.15980) | Explanation<br/>+ Steering | Find a natural-language prompt<br/>using input-gradients (⌛ In progress)|
-| D3            | [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/d3.ipynb), [🗂️](http://csinva.io/imodelsX/d3/d3.html#imodelsx.d3.d3.explain_dataset_d3), [🔗](https://github.com/ruiqi-zhong/DescribeDistributionalDifferences), [📄](https://arxiv.org/abs/2201.12323) | Explanation | Explain the difference between two distributions |
+| D3            | [🗂️](http://csinva.io/imodelsX/d3/d3.html#imodelsx.d3.d3.explain_dataset_d3), [🔗](https://github.com/ruiqi-zhong/DescribeDistributionalDifferences), [📄](https://arxiv.org/abs/2201.12323), [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/d3.ipynb) | Explanation | Explain the difference between two distributions |
 | SASC            |   ㅤㅤ[🗂️](https://csinva.io/imodelsX/sasc/api.html), [🔗](https://github.com/microsoft/automated-explanations), [📄](https://arxiv.org/abs/2305.09863) | Explanation | Explain a black-box text module<br/>using an LLM (*Official*) |
-| Aug-GAM            | [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/aug_imodels.ipynb), [🗂️](https://csinva.io/imodelsX/auggam/auggam.html), [🔗](https://github.com/microsoft/aug-models), [📄](https://arxiv.org/abs/2209.11799) | Linear model | Fit better linear model using an LLM<br/>to extract embeddings (*Official*) |
-| Aug-Tree            | [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/aug_imodels.ipynb), [🗂️](https://csinva.io/imodelsX/augtree/augtree.html), [🔗](https://github.com/microsoft/aug-models), [📄](https://arxiv.org/abs/2209.11799) | Decision tree | Fit better decision tree using an LLM<br/>to expand features (*Official*) |
+| Aug-GAM            | [🗂️](https://csinva.io/imodelsX/auggam/auggam.html), [🔗](https://github.com/microsoft/aug-models), [📄](https://www.nature.com/articles/s41467-023-43713-1), [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/aug_imodels.ipynb) | Linear model | Fit better linear model using an LLM<br/>to extract embeddings (*Official*) |
+| Aug-Tree            | [🗂️](https://csinva.io/imodelsX/augtree/augtree.html), [🔗](https://github.com/microsoft/aug-models), [📄](https://www.nature.com/articles/s41467-023-43713-1), [📖](https://github.com/csinva/imodelsX/blob/master/demo_notebooks/aug_imodels.ipynb) | Decision tree | Fit better decision tree using an LLM<br/>to expand features (*Official*) |
 
 <p align="center">
 <a href="https://github.com/csinva/imodelsX/tree/master/demo_notebooks">📖</a>Demo notebooks &emsp; <a href="https://csinva.io/imodelsX/">🗂️</a> Doc &emsp; 🔗 Reference code &emsp; 📄 Research paper