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update readme
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allenanie committed Oct 31, 2024
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Expand Up @@ -164,7 +164,7 @@ The table evaluates the frameworks in the following aspects:
We provide a comparison to validate our implementation of TextGrad in Trace:

<p align="center">
<img src="https://github.com/microsoft/Trace/blob/main/docs/images/compare_to_textgrad2.png" alt="drawing" width="100%"/>
<img src="https://github.com/microsoft/Trace/blob/main/docs/images/compare_to_textgrad3.png" alt="drawing" width="100%"/>
</p>

To produce this table, we ran the TextGrad pip-installed repo on 2024-10-30, and we also include the numbers reported in the TextGrad paper.
Expand All @@ -186,6 +186,19 @@ If you use this code in your research please cite the following [publication](ht
}
```

## Papers/Projects that Use Trace

[Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers](https://arxiv.org/pdf/2410.15625)
Work from Stanford, NVIDIA, Intel, Visa Research.
```
@article{wei2024improving,
title={Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers},
author={Wei, Anjiang and Nie, Allen and Teixeira, Thiago SFX and Yadav, Rohan and Lee, Wonchan and Wang, Ke and Aiken, Alex},
journal={arXiv preprint arXiv:2410.15625},
year={2024}
}
```

## Evaluation

A previous version of Trace was tested with gpt-4-0125-preview on numerical optimization, simulated traffic control,
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