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When Creative AI Meets Conversational AI Workshop
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(Venues)
Published year
2025
2024
2023
2022
2021
2020
2019
2018
2017
Evaluating Gender Bias Transfer between Pre-trained and Prompt-Adapted Language Models
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
conference
NeurIPS
Published year
2024
Authors
Natalie Mackraz*, Nivedha Sivakumar*, Samira Khorshidi, Krishna Patel, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff
When is Multicalibration Post-Processing Necessary?
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
NeurIPS
Published year
2024
Authors
Dutch Hansen, Siddartha Devic, Preetum Nakkiran, Vatsal Sharan
Whispering Experts: Toxicity Mitigation in Pre-trained Language Models by Dampening Expert Neurons
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
conference
ICML
Published year
2024
Authors
Xavier Suau Cuadros, Pieter Delobelle, Rin Metcalf Susa, Armand Joulin, Nick Apostoloff, Luca Zappella, Pau Rodriguez Lopez
Omnipredictors for Regression and the Approximate Rank of Convex Functions
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
COLT
Published year
2024
Authors
Parikshit Gopalan, Princewill Okoroafor, Prasad Raghavendra, Abhishek Shetty, Mihir A Singhal
On Computationally Efficient Multi-Class Calibration
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
COLT
Published year
2024
Authors
Parikshit Gopalan, Lunjia Hu, Guy Rothblum
Characterizing Omniprediction via Multicalibration
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
NeurIPS
Published year
2023
In collaboration with Stanford University, University of California, Berkeley
Authors
Parikshit Gopalan, Michael P. Kim, Omer Reingold
DELPHI: Data for Evaluating LLMs' Performance in Handling Controversial Issues
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
conference
EMNLP
Published year
2023
Authors
David Q. Sun*, Artem Abzaliev*, Hadas Kotek, Zidi Xiu, Christopher Klein, Jason D. Williams
When Does Optimizing a Proper Loss Yield Calibration?
Award
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
NeurIPS
Published year
2023
In collaboration with Columbia University, Stanford University
Authors
Jarosław Błasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran
Gender Bias in LLMs
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
Published year
2023
Authors
Hadas Kotek, Rikker Dockum, David Q. Sun
Dataset and Network Introspection ToolKit (DNIKit)
content type
paper
|
research area
Fairness
,
research area
Tools, Platforms, Frameworks
|
Published year
2023
Authors
Megan Maher Welsh, David Koski, Miguel Sarabia, Niv Sivakumar, Ian Arawjo, Aparna Joshi, Moussa Doumbouya, Xavier Suau, Luca Zappella, Nicholas Apostoloff
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Evaluating Gender Bias Transfer between Pre-trained and Prompt-Adapted Language Models
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
conference
NeurIPS
Published year
2024
Authors
Natalie Mackraz*, Nivedha Sivakumar*, Samira Khorshidi, Krishna Patel, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff
When is Multicalibration Post-Processing Necessary?
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
NeurIPS
Published year
2024
Authors
Dutch Hansen, Siddartha Devic, Preetum Nakkiran, Vatsal Sharan
Whispering Experts: Toxicity Mitigation in Pre-trained Language Models by Dampening Expert Neurons
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
conference
ICML
Published year
2024
Authors
Xavier Suau Cuadros, Pieter Delobelle, Rin Metcalf Susa, Armand Joulin, Nick Apostoloff, Luca Zappella, Pau Rodriguez Lopez
Omnipredictors for Regression and the Approximate Rank of Convex Functions
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
COLT
Published year
2024
Authors
Parikshit Gopalan, Princewill Okoroafor, Prasad Raghavendra, Abhishek Shetty, Mihir A Singhal
On Computationally Efficient Multi-Class Calibration
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
COLT
Published year
2024
Authors
Parikshit Gopalan, Lunjia Hu, Guy Rothblum
Characterizing Omniprediction via Multicalibration
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
NeurIPS
Published year
2023
In collaboration with Stanford University, University of California, Berkeley
Authors
Parikshit Gopalan, Michael P. Kim, Omer Reingold
DELPHI: Data for Evaluating LLMs' Performance in Handling Controversial Issues
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
conference
EMNLP
Published year
2023
Authors
David Q. Sun*, Artem Abzaliev*, Hadas Kotek, Zidi Xiu, Christopher Klein, Jason D. Williams
When Does Optimizing a Proper Loss Yield Calibration?
Award
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
NeurIPS
Published year
2023
In collaboration with Columbia University, Stanford University
Authors
Jarosław Błasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran
Gender Bias in LLMs
content type
paper
|
research area
Fairness
,
research area
Speech and Natural Language Processing
|
Published year
2023
Authors
Hadas Kotek, Rikker Dockum, David Q. Sun
Dataset and Network Introspection ToolKit (DNIKit)
content type
paper
|
research area
Fairness
,
research area
Tools, Platforms, Frameworks
|
Published year
2023
Authors
Megan Maher Welsh, David Koski, Miguel Sarabia, Niv Sivakumar, Ian Arawjo, Aparna Joshi, Moussa Doumbouya, Xavier Suau, Luca Zappella, Nicholas Apostoloff
A Unifying Theory of Distance from Calibration
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
conference
ACM STOC
Published year
2023
In collaboration with Columbia University, Stanford University
Authors
Jarosław Błasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran
Loss Minimization through the lens of Outcome Indistinguishability
content type
paper
|
research area
Fairness
,
research area
Methods and Algorithms
|
Published year
2023
In collaboration with Stanford University, University of California, Berkeley
Authors
Parikshit Gopalan, Lunjia Hu, Michael P. Kim, Omer Reingold, Udi Wieder
Designing Data: Proactive Data Collection and Iteration for Machine Learning
content type
paper
|
research area
Fairness
,
research area
Human-Computer Interaction
|
Published year
2023
In collaboration with Massachusetts Institute of Technology
Authors
Aspen Hopkins, Fred Hohman, Luca Zappella, Xavier Suau, Dominik Moritz
Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer
content type
paper
|
research area
Computer Vision
,
research area
Fairness
|
Workshop at NeurIPS
Published year
2022
Authors
Andrius Ovsianas, Jason Ramapuram, Dan Busbridge, Eeshan Gunesh Dhekane, Russ Webb
FORML: Learning to Reweight Data for Fairness
content type
paper
|
research area
Computer Vision
,
research area
Fairness
|
Workshop at ICML
Published year
2022
Authors
Bobby Yan*, Skyler Seto*, Nicholas Apostoloff
Minimax Demographic Group Fairness in Federated Learning
content type
paper
|
research area
Fairness
,
research area
Privacy
|
conference
ACM FAccT
Published year
2022
In collaboration with Duke University, University College London
Authors
Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro and Miguel Rodrigues
Fair SA: Sensitivity Analysis for Fairness in Face Recognition
content type
paper
|
research area
Computer Vision
,
research area
Fairness
|
conference
NeurIPS
Published year
2021
Authors
Aparna R. Joshi, Xavier Suau, Nivedha Sivakumar, Luca Zappella, Nicholas Apostoloff
Enforcing Fairness in Private Federated Learning via The Modified Method of Differential Multipliers
content type
paper
|
research area
Fairness
,
research area
Privacy
|
Workshop at NeurIPS
Published year
2021
Authors
Borja Rodríguez-Gálvez, Filip Granqvist, Rogier van Dalen, Matt Seigel
Evaluating the Fairness of Fine-Tuning Strategies in Self-Supervised Learning
content type
paper
|
research area
Computer Vision
,
research area
Fairness
|
conference
BayLearn
Published year
2021
Authors
Jason Ramapuram*, Dan Busbridge*, Russ Webb
Research - Apple Machine Learning Research