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Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations



Jessica Dai , Sohini Upadhyay , Ulrich Aivodji , Stephen H. Bach , Himabindu Lakkaraju

* Accepted at AIES 2022 

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Language Models in the Loop: Incorporating Prompting into Weak Supervision



Ryan Smith , Jason A. Fries , Braden Hancock , Stephen H. Bach


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Learning to Compose Soft Prompts for Compositional Zero-Shot Learning



Nihal V. Nayak , Peilin Yu , Stephen H. Bach


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PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts



Stephen H. Bach , Victor Sanh , Zheng-Xin Yong , Albert Webson , Colin Raffel , Nihal V. Nayak , Abheesht Sharma , Taewoon Kim , M Saiful Bari , Thibault Fevry , Zaid Alyafeai , Manan Dey , Andrea Santilli , Zhiqing Sun , Srulik Ben-David , Canwen Xu , Gunjan Chhablani , Han Wang , Jason Alan Fries , Maged S. Al-shaibani , Shanya Sharma , Urmish Thakker , Khalid Almubarak , Xiangru Tang , Xiangru Tang , Mike Tian-Jian Jiang , Alexander M. Rush


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TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary Data



Wasu Piriyakulkij , Cristina Menghini , Ross Briden , Nihal V. Nayak , Jeffrey Zhu , Elaheh Raisi , Stephen H. Bach

* Added acknowledgements 

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Multitask Prompted Training Enables Zero-Shot Task Generalization



Victor Sanh , Albert Webson , Colin Raffel , Stephen H. Bach , Lintang Sutawika , Zaid Alyafeai , Antoine Chaffin , Arnaud Stiegler , Teven Le Scao , Arun Raja , Manan Dey , M Saiful Bari , Canwen Xu , Urmish Thakker , Shanya Sharma Sharma , Eliza Szczechla , Taewoon Kim , Gunjan Chhablani , Nihal Nayak , Debajyoti Datta , Jonathan Chang , Mike Tian-Jian Jiang , Han Wang , Matteo Manica , Sheng Shen , Zheng Xin Yong , Harshit Pandey , Rachel Bawden , Thomas Wang , Trishala Neeraj , Jos Rozen , Abheesht Sharma , Andrea Santilli , Thibault Fevry , Jason Alan Fries , Ryan Teehan , Stella Biderman , Leo Gao , Tali Bers , Thomas Wolf , Alexander M. Rush

* https://github.com/bigscience-workshop/promptsource/ 

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What will it take to generate fairness-preserving explanations?



Jessica Dai , Sohini Upadhyay , Stephen H. Bach , Himabindu Lakkaraju

* Presented at ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI 

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Learning from Multiple Noisy Partial Labelers



Peilin Yu , Tiffany Ding , Stephen H. Bach


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Pseudo Shots: Few-Shot Learning with Auxiliary Data



Reza Esfandiarpoor , Mohsen Hajabdollahi , Stephen H. Bach

* Added link to code; Added acknowledgments 

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