Fereshte Khani

According to our database, Fereshte Khani authored at least 16 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Prompt Engineering a Prompt Engineer.

Qinyuan Ye, Maxamed Axmed, Reid Pryzant, Fereshte Khani

CoRR, 2023

Collaborative Development of NLP models.

Fereshte Khani, Marco Túlio Ribeiro

CoRR, 2023

Collaborative Alignment of NLP Models.

Fereshte Khani, Marco Túlio Ribeiro

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Targeted Data Generation: Finding and Fixing Model Weaknesses.

Zexue He, Marco Túlio Ribeiro, Fereshte Khani

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness.

Saeid Asgari Taghanaki, Ali Gholami, Fereshte Khani, Kristy Choi, Linh Tran, Ran Zhang, Aliasghar Khani

CoRR, 2022

MaskTune: Mitigating Spurious Correlations by Forcing to Explore.

Saeid Asgari Taghanaki, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran, Ali Mahdavi-Amiri, Ghassan Hamarneh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Causes, measurement, and mitigation of loss discrepancy.

Fereshte Khani

PhD thesis, 2021

On the Opportunities and Risks of Foundation Models.

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.

CoRR, 2021

In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness.

Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang

Proceedings of the 9th International Conference on Learning Representations, 2021

Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately.

Fereshte Khani, Percy Liang

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020

Feature Noise Induces Loss Discrepancy Across Groups.

Fereshte Khani, Percy Liang

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Noise Induces Loss Discrepancy Across Groups for Linear Regression.

Fereshte Khani, Percy Liang

CoRR, 2019

Maximum Weighted Loss Discrepancy.

Fereshte Khani, Aditi Raghunathan, Percy Liang

CoRR, 2019

2018

Planning, Inference, and Pragmatics in Sequential Language Games.

Fereshte Khani, Noah D. Goodman, Percy Liang

Trans. Assoc. Comput. Linguistics, 2018

2016

Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings.

Fereshte Khani, Martin C. Rinard, Percy Liang

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2013

An algorithm for discovering clusters of different densities or shapes in noisy data sets.

Fereshte Khani, Mohammad Javad Hosseini, Ahmad Ali Abin, Hamid Beigy

Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013