Sara Hooker

According to our database, Sara Hooker authored at least 46 papers between 2017 and 2024.

Collaborative distances:

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

2024

From One to Many: Expanding the Scope of Toxicity Mitigation in Language Models.

Luiza Pozzobon, Patrick Lewis, Sara Hooker, Beyza Ermis

CoRR, 2024

Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs.

Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker

CoRR, 2024

Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model.

Ahmet Üstün, Viraat Aryabumi, Zheng Xin Yong, Wei-Yin Ko, Daniel D'souza, Gbemileke Onilude, Neel Bhandari, Shivalika Singh, Hui-Lee Ooi, Amr Kayid, Freddie Vargus, Phil Blunsom, Shayne Longpre, Niklas Muennighoff, Marzieh Fadaee, Julia Kreutzer, Sara Hooker

CoRR, 2024

Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning.

Shivalika Singh, Freddie Vargus, Daniel D'souza, Börje F. Karlsson, Abinaya Mahendiran, Wei-Yin Ko, Herumb Shandilya, Jay Patel, Deividas Mataciunas, Laura O'Mahony, Mike Zhang, Ramith Hettiarachchi, Joseph Wilson, Marina Machado, Luisa Souza Moura, Dominik Krzeminski, Hakimeh Fadaei, Irem Ergün, Ifeoma Okoh, Aisha Alaagib, Oshan Mudannayake, Zaid Alyafeai, Minh Chien Vu, Sebastian Ruder, Surya Guthikonda, Emad A. Alghamdi, Sebastian Gehrmann, Niklas Muennighoff, Max Bartolo, Julia Kreutzer, Ahmet Üstün, Marzieh Fadaee, Sara Hooker

CoRR, 2024

2023

On The Fairness Impacts of Hardware Selection in Machine Learning.

Sree Harsha Nelaturu, Nishaanth Kanna Ravichandran, Cuong Tran, Sara Hooker, Ferdinando Fioretto

CoRR, 2023

Generalisable Agents for Neural Network Optimisation.

Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius

CoRR, 2023

Elo Uncovered: Robustness and Best Practices in Language Model Evaluation.

Meriem Boubdir, Edward Kim, Beyza Ermis, Sara Hooker, Marzieh Fadaee

CoRR, 2023

The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI.

Shayne Longpre, Robert Mahari, Anthony Chen, Naana Obeng-Marnu, Damien Sileo, William Brannon, Niklas Muennighoff, Nathan Khazam, Jad Kabbara, Kartik Perisetla, Xinyi Wu, Enrico Shippole, Kurt D. Bollacker, Tongshuang Wu, Luis Villa, Sandy Pentland, Deb Roy, Sara Hooker

CoRR, 2023

Which Prompts Make The Difference? Data Prioritization For Efficient Human LLM Evaluation.

Meriem Boubdir, Edward Kim, Beyza Ermis, Marzieh Fadaee, Sara Hooker

CoRR, 2023

Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning.

Ted Zadouri, Ahmet Üstün, Arash Ahmadian, Beyza Ermis, Acyr Locatelli, Sara Hooker

CoRR, 2023

When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale.

Max Marion, Ahmet Üstün, Luiza Pozzobon, Alex Wang, Marzieh Fadaee, Sara Hooker

CoRR, 2023

Frontier AI Regulation: Managing Emerging Risks to Public Safety.

Markus Anderljung, Joslyn Barnhart, Anton Korinek, Jade Leung, Cullen O'Keefe, Jess Whittlestone, Shahar Avin, Miles Brundage, Justin Bullock, Duncan Cass-Beggs, Ben Chang, Tantum Collins, Tim Fist, Gillian K. Hadfield, Alan Hayes, Lewis Ho, Sara Hooker, Eric Horvitz, Noam Kolt, Jonas Schuett, Yonadav Shavit, Divya Siddarth, Robert Trager, Kevin Wolf

CoRR, 2023

Evaluating the Social Impact of Generative AI Systems in Systems and Society.

Irene Solaiman, Zeerak Talat, William Agnew, Lama Ahmad, Dylan K. Baker, Su Lin Blodgett, Hal Daumé III, Jesse Dodge, Ellie Evans, Sara Hooker, Yacine Jernite, Alexandra Sasha Luccioni, Alberto Lusoli, Margaret Mitchell, Jessica Newman, Marie-Therese Png, Andrew Strait, Apostol Vassilev

CoRR, 2023

Intriguing Properties of Quantization at Scale.

Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Stephen Gou, Phil Blunsom, Ahmet Üstün, Sara Hooker

CoRR, 2023

FAIR-Ensemble: When Fairness Naturally Emerges From Deep Ensembling.

Wei-Yin Ko, Daniel D'souza, Karina Nguyen, Randall Balestriero, Sara Hooker

CoRR, 2023

Robust distillation for worst-class performance: on the interplay between teacher and student objectives.

Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon

Proceedings of the Uncertainty in Artificial Intelligence, 2023

The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs.

Laura Ruis, Akbir Khan, Stella Biderman, Sara Hooker, Tim Rocktäschel, Edward Grefenstette

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

The Grand Illusion: The Myth of Software Portability and Implications for ML Progress.

Fraser Mince, Dzung Dinh, Jonas Kgomo, Neil Thompson, Sara Hooker

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

Intriguing Properties of Quantization at Scale.

Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Stephen Zhen Gou, Phil Blunsom, Ahmet Üstün, Sara Hooker

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

Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics.

Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, Sara Hooker

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Locally Differentially Private Document Generation Using Zero Shot Prompting.

Saiteja Utpala, Sara Hooker, Pin-Yu Chen

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Goodtriever: Adaptive Toxicity Mitigation with Retrieval-augmented Models.

Luiza Pozzobon, Beyza Ermis, Patrick Lewis, Sara Hooker

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

On the Challenges of Using Black-Box APIs for Toxicity Evaluation in Research.

Luiza Pozzobon, Beyza Ermis, Patrick Lewis, Sara Hooker

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Large language models are not zero-shot communicators.

Laura Ruis, Akbir Khan, Stella Biderman, Sara Hooker, Tim Rocktäschel, Edward Grefenstette

CoRR, 2022

Efficient Methods for Natural Language Processing: A Survey.

Marcos V. Treviso, Tianchu Ji, Ji-Ung Lee, Betty van Aken, Qingqing Cao, Manuel R. Ciosici, Michael Hassid, Kenneth Heafield, Sara Hooker, Pedro Henrique Martins, André F. T. Martins, Peter A. Milder, Colin Raffel, Edwin Simpson, Noam Slonim, Niranjan Balasubramanian, Leon Derczynski, Roy Schwartz

CoRR, 2022

Studying the impact of magnitude pruning on contrastive learning methods.

Francesco Corti, Rahim Entezari, Sara Hooker, Davide Bacciu, Olga Saukh

CoRR, 2022

Robust Distillation for Worst-class Performance.

Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon

CoRR, 2022

When less is more: Simplifying inputs aids neural network understanding.

Robin Tibor Schirrmeister, Rosanne Liu, Sara Hooker, Tonio Ball

CoRR, 2022

Randomness in Neural Network Training: Characterizing the Impact of Tooling.

Donglin Zhuang, Xingyao Zhang, Shuaiwen Song, Sara Hooker

Proceedings of Machine Learning and Systems 2022, 2022

Intriguing Properties of Compression on Multilingual Models.

Kelechi Ogueji, Orevaoghene Ahia, Gbemileke Onilude, Sebastian Gehrmann, Sara Hooker, Julia Kreutzer

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Estimating Example Difficulty using Variance of Gradients.

Chirag Agarwal, Daniel D'souza, Sara Hooker

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Moving beyond "algorithmic bias is a data problem".

Sara Hooker

Patterns, 2021

A Tale Of Two Long Tails.

Daniel D'souza, Zach Nussbaum, Chirag Agarwal, Sara Hooker

CoRR, 2021

When does loss-based prioritization fail?

Niel Teng Hu, Xinyu Hu, Rosanne Liu, Sara Hooker, Jason Yosinski

CoRR, 2021

Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization.

Kale-ab Tessera, Sara Hooker, Benjamin Rosman

CoRR, 2021

The hardware lottery.

Sara Hooker

Commun. ACM, 2021

The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation.

Orevaoghene Ahia, Julia Kreutzer, Sara Hooker

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020

Characterising Bias in Compressed Models.

Sara Hooker, Nyalleng Moorosi, Gregory Clark, Samy Bengio, Emily Denton

CoRR, 2020

Estimating Example Difficulty using Variance of Gradients.

Chirag Agarwal, Sara Hooker

CoRR, 2020

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims.

Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian K. Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung

CoRR, 2020

2019

The (Un)reliability of Saliency Methods.

Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim

Proceedings of the Explainable AI: Interpreting, 2019

Selective Brain Damage: Measuring the Disparate Impact of Model Pruning.

Sara Hooker, Aaron C. Courville, Yann N. Dauphin, Andrea Frome

CoRR, 2019

The State of Sparsity in Deep Neural Networks.

Trevor Gale, Erich Elsen, Sara Hooker

CoRR, 2019

A Benchmark for Interpretability Methods in Deep Neural Networks.

Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Evaluating Feature Importance Estimates.

Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim

CoRR, 2018

2017

The (Un)reliability of saliency methods.

Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim

CoRR, 2017