From ed44f20c322cb01ecdf7d34e84b4141c86dc79e6 Mon Sep 17 00:00:00 2001 From: Arshaan Date: Thu, 31 Aug 2023 11:37:00 +0530 Subject: [PATCH 1/4] Add blogs --- README.md | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/README.md b/README.md index cb531c2cc..ef486f2be 100644 --- a/README.md +++ b/README.md @@ -88,6 +88,18 @@ Langtest comes with different datasets to test your models, covering a wide rang > **Note** > For usage and documentation, head over to [langtest.org](https://langtest.org/docs/pages/docs/data#question-answering) + +## Blogs + +You can checkout the following langtest blogs: + +| Blog |Description | + +| [**Automatically Testing for Demographic Bias in Clinical Treatment Plans Generated by Large Language Models**](https://medium.com/p/ffcf358b6092/edit) | Helps in Understanding and testing demographic bias in clinical treatment plans generated by LLM. | +| [**LangTest: Unveiling & Fixing Biases with End-to-End NLP Pipelines**](https://www.johnsnowlabs.com/langtest-unveiling-fixing-biases-with-end-to-end-nlp-pipelines/) | The end-to-end language pipeline in LangTest empowers NLP practitioners to tackle biases in language models with a comprehensive, data-driven, and iterative approach. | +| [**Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest**](https://medium.com/@prikshit7766/fb046ace7eb9) | While accuracy is undoubtedly crucial, robustness testing takes natural language processing (NLP) models evaluation to the next level by ensuring that models can perform reliably and consistently across a wide array of real-world conditions. | + + ## Contributing We welcome all sorts of contributions: From 1401feb8783ebb2b7db0495f3a45c6abc8b0c291 Mon Sep 17 00:00:00 2001 From: Arshaan Date: Thu, 31 Aug 2023 11:52:29 +0530 Subject: [PATCH 2/4] update Readme --- README.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index ef486f2be..bf09814e0 100644 --- a/README.md +++ b/README.md @@ -94,10 +94,11 @@ Langtest comes with different datasets to test your models, covering a wide rang You can checkout the following langtest blogs: | Blog |Description | +|---------------|----------------------------------------------------------------------------------------------------| | [**Automatically Testing for Demographic Bias in Clinical Treatment Plans Generated by Large Language Models**](https://medium.com/p/ffcf358b6092/edit) | Helps in Understanding and testing demographic bias in clinical treatment plans generated by LLM. | -| [**LangTest: Unveiling & Fixing Biases with End-to-End NLP Pipelines**](https://www.johnsnowlabs.com/langtest-unveiling-fixing-biases-with-end-to-end-nlp-pipelines/) | The end-to-end language pipeline in LangTest empowers NLP practitioners to tackle biases in language models with a comprehensive, data-driven, and iterative approach. | -| [**Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest**](https://medium.com/@prikshit7766/fb046ace7eb9) | While accuracy is undoubtedly crucial, robustness testing takes natural language processing (NLP) models evaluation to the next level by ensuring that models can perform reliably and consistently across a wide array of real-world conditions. | +| [**LangTest: Unveiling & Fixing Biases with End-to-End NLP Pipelines**](https://www.johnsnowlabs.com/langtest-unveiling-fixing-biases-with-end-to-end-nlp-pipelines/) | The end-to-end language pipeline in LangTest empowers NLP practitioners to tackle biases in language models with a comprehensive, data-driven, and iterative approach. | +| [**Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest**](https://medium.com/@prikshit7766/fb046ace7eb9) | While accuracy is undoubtedly crucial, robustness testing takes natural language processing (NLP) models evaluation to the next level by ensuring that models can perform reliably and consistently across a wide array of real-world conditions.| ## Contributing From 73658a21a4d8e9fcc0bd1cb4156467105b312692 Mon Sep 17 00:00:00 2001 From: Arshaan Date: Thu, 31 Aug 2023 11:57:20 +0530 Subject: [PATCH 3/4] Update blog section --- README.md | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index bf09814e0..d9b52999e 100644 --- a/README.md +++ b/README.md @@ -91,15 +91,16 @@ Langtest comes with different datasets to test your models, covering a wide rang ## Blogs -You can checkout the following langtest blogs: +You can check out the following langtest blogs: -| Blog |Description | -|---------------|----------------------------------------------------------------------------------------------------| - -| [**Automatically Testing for Demographic Bias in Clinical Treatment Plans Generated by Large Language Models**](https://medium.com/p/ffcf358b6092/edit) | Helps in Understanding and testing demographic bias in clinical treatment plans generated by LLM. | -| [**LangTest: Unveiling & Fixing Biases with End-to-End NLP Pipelines**](https://www.johnsnowlabs.com/langtest-unveiling-fixing-biases-with-end-to-end-nlp-pipelines/) | The end-to-end language pipeline in LangTest empowers NLP practitioners to tackle biases in language models with a comprehensive, data-driven, and iterative approach. | -| [**Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest**](https://medium.com/@prikshit7766/fb046ace7eb9) | While accuracy is undoubtedly crucial, robustness testing takes natural language processing (NLP) models evaluation to the next level by ensuring that models can perform reliably and consistently across a wide array of real-world conditions.| +| Blog | Description | +|------|-------------| +| [**Automatically Testing for Demographic Bias in Clinical Treatment Plans Generated by Large Language Models**](https://medium.com/p/ffcf358b6092/edit) | Helps in understanding and testing demographic bias in clinical treatment plans generated by LLM. | +| [**LangTest: Unveiling & Fixing Biases with End-to-End NLP Pipelines**](https://www.johnsnowlabs.com/langtest-unveiling-fixing-biases-with-end-to-end-nlp-pipelines/) | The end-to-end language pipeline in LangTest empowers NLP practitioners to tackle biases in language models with a comprehensive, data-driven, and iterative approach. | +| [**Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest**](https://medium.com/@prikshit7766/fb046ace7eb9) | While accuracy is undoubtedly crucial, robustness testing takes natural language processing (NLP) models evaluation to the next level by ensuring that models can perform reliably and consistently across a wide array of real-world conditions. | +> **Note** +> To checkout all blogs, head over to [langtest.org](https://www.johnsnowlabs.com/responsible-ai-blog/) ## Contributing From 25f65636bd2aec0830914a80182125a7d8a12208 Mon Sep 17 00:00:00 2001 From: Arshaan Date: Thu, 31 Aug 2023 11:58:26 +0530 Subject: [PATCH 4/4] fix readme --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index d9b52999e..8b66d69b1 100644 --- a/README.md +++ b/README.md @@ -100,7 +100,7 @@ You can check out the following langtest blogs: | [**Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest**](https://medium.com/@prikshit7766/fb046ace7eb9) | While accuracy is undoubtedly crucial, robustness testing takes natural language processing (NLP) models evaluation to the next level by ensuring that models can perform reliably and consistently across a wide array of real-world conditions. | > **Note** -> To checkout all blogs, head over to [langtest.org](https://www.johnsnowlabs.com/responsible-ai-blog/) +> To checkout all blogs, head over to [Blogs](https://www.johnsnowlabs.com/responsible-ai-blog/) ## Contributing