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Instructions for Authors with Accepted Papers


The recommended length of the pre-recorded video is 10 minutes. You should have received the uploading link from via email and that link is the only entrance to upload the video. If you have not received the link yet, please let us know. The video uploading deadline is Nov 10, AoE.

Poster and Thumbnail

You should have received a link from You will need to upload your poster and thumbnail following the link. They will be used by the conference website. The poster and thumbnail uploading deadline will be in December, a few days before the workshop date (December 9, 2022). In addition, our workshop will have a virtual poster session on Topia. We are working on setting up the virtual poster session and more instructions will be sent out soon.

Camera-Ready Version

Please change “\usepackage{tsrml_2022}” to “\usepackage[final]{tsrml_2022}” and populate the author field when preparing the camera-ready version. There is no strict page limit for the camera-ready version, but we recommend keeping the main text within 6 pages. Please submit your camera-ready version by clicking “Camera-Ready Revision” in OpenReview. The deadline for camera-ready version submission is Nov 10, AoE. We plan to make the camera-ready version and forum discussion public for accepted papers. Hence, if you see factual misunderstandings or questions from the review, we encourage you to post replies by clicking "Official Comment". Please follow NeurIPS Code of Conduct to involve in the discussion.

Accepted Papers

This list will be updated based on the metadata of each paper after the camera-ready deadline.

  1. Take 5: Interpretable Image Classification with a Handful of Features
    Thomas Norrenbrock; Marco Rudolph; Bodo Rosenhahn
  2. Membership Inference Attacks via Adversarial Examples
    Hamid Jalalzai; Elie Kadoche; Rémi Leluc; Vincent Plassier
  3. Scalable and Improved Algorithms for Individually Fair Clustering
    Mohammadhossein Bateni; Vincent Cohen-Addad; Alessandro Epasto; Silvio Lattanzi
  4. Not All Knowledge Is Created Equal: Mutual Distillation of Confident Knowledge
    ZIYUN LI; Xinshao Wang; Christoph Meinel; Neil M. Robertson; David A. Clifton; Haojin Yang
  5. Just Following AI Orders: When Unbiased People Are Influenced By Biased AI
    Hammaad Adam; Aparna Balagopalan; Emily Alsentzer; Fotini Christia; Marzyeh Ghassemi
  6. Towards Algorithmic Fairness in Space-Time: Filling in Black Holes
    Cheryl Brooks; Aritra Guha; Subhabrata Majumdar; Divesh Srivastava; Zhengyi Zhou
  7. COVID-Net Biochem: An Explainability-driven Framework to Building Machine Learning Models for Predicting Survival and Kidney Injury of COVID-19 Patients from Clinical and Biochemistry Data
    Hossein Aboutalebi; Maya Pavlova; Mohammad Javad Shafiee; Adrian Florea; Andrew Hryniowski; Alexander Wong
  8. On the Feasibility of Compressing Certifiably Robust Neural Networks
    Pratik Vaishnavi; Veena Krish; Farhan Ahmed; Kevin Eykholt; Amir Rahmati
  9. Differentially Private Bias-Term only Fine-tuning of Foundation Models
    Zhiqi Bu; Yu-Xiang Wang; Sheng Zha; George Karypis
  10. When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes
    Canyu Chen; Yueqing Liang; Xiongxiao Xu; Shangyu Xie; Yuan Hong; Kai Shu
  11. Visual Prompting for Adversarial Robustness
    Aochuan Chen; Peter Lorenz; Yuguang Yao; Pin-Yu Chen; Sijia Liu
  12. Is the Next Winter Coming for AI?The Elements of Making Secure and Robust AI
    Joshua Harguess
  13. Attack-Agnostic Adversarial Detection
    Jiaxin Cheng; Mohamed E. Hussein; Jayadev Billa; Wael AbdAlmgaeed
  14. Provable Re-Identification Privacy
    Zachary Izzo; Jinsung Yoon; Sercan O Arik; James Zou
  15. Anonymization for Skeleton Action Recognition
    Saemi Moon; Myeonghyeon Kim; Zhenyue Qin; Yang Liu; Dongwoo Kim
  16. Men Also Do Laundry: Multi-Attribute Bias Amplification
    Dora Zhao; Jerone Theodore Alexander Andrews; Alice Xiang
  17. Cold Posteriors through PAC-Bayes
    Konstantinos Pitas; Julyan Arbel
  18. Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation
    Maksym Yatsura; Kaspar Sakmann; N. Grace Hua; Matthias Hein; Jan Hendrik Metzen
  19. Bias Amplification in Image Classification
    Melissa Hall; Laurens van der Maaten; Laura Gustafson; Maxwell Jones; Aaron Bryan Adcock
  20. Hybrid-EDL: Improving Evidential Deep Learning for Uncertainty Quantification on Imbalanced Data
    Tong Xia; Jing Han; Lorena Qendro; Ting Dang; Cecilia Mascolo
  21. Indiscriminate Data Poisoning Attacks on Neural Networks
    Yiwei Lu; Gautam Kamath; Yaoliang Yu
  22. Finding Safe Zones of Markov Decision Processes Policies
    Michal Moshkovitz; Lee Cohen; Yishay Mansour
  23. On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition
    Samuel Dooley; Rhea Sanjay Sukthanker; John P Dickerson; Colin White; Frank Hutter; Micah Goldblum
  24. Poisoning Generative Models to Promote Catastrophic Forgetting
    Siteng Kang; Xinhua Zhang
  25. On Causal Rationalization
    Wenbo Zhang; TONG WU; Yunlong Wang; Yong Cai; Hengrui Cai
  26. A View From Somewhere: Human-Centric Face Representations
    Jerone Theodore Alexander Andrews; Przemyslaw Joniak; Alice Xiang
  27. REGLO: Provable Neural Network Repair for Global Robustness Properties
    Feisi Fu; Zhilu Wang; Jiameng Fan; Yixuan Wang; Chao Huang; Xin Chen; Qi Zhu; Wenchao Li
  28. What Makes a Good Explanation?: A Unified View of Properties of Interpretable ML
    Zixi Chen; Varshini Subhash; Marton Havasi; Weiwei Pan; Finale Doshi-Velez
  29. On the Impact of Adversarially Robust Models on Algorithmic Recourse
    Satyapriya Krishna; Chirag Agarwal; Himabindu Lakkaraju
  30. Participatory Systems for Personalized Prediction
    Hailey James; Chirag Nagpal; Katherine A Heller; Berk Ustun
  31. TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations
    Dylan Z Slack; Satyapriya Krishna; Himabindu Lakkaraju; Sameer Singh
  32. Differentially Private Gradient Boosting on Linear Learners for Tabular Data
    Saeyoung Rho; Shuai Tang; Sergul Aydore; Michael Kearns; Aaron Roth; Yu-Xiang Wang; Steven Wu; Cedric Archambeau
  33. A Deep Dive into Dataset Imbalance and Bias in Face Identification
    Valeriia Cherepanova; Steven Reich; Samuel Dooley; Hossein Souri; John P Dickerson; Micah Goldblum; Tom Goldstein
  34. Evaluating the Practicality of Counterfactual Explanation
    Nina Spreitzer; Hinda Haned; Ilse van der Linden
  35. Certified Training: Small Boxes are All You Need
    Mark Niklas Mueller; Franziska Eckert; Marc Fischer; Martin Vechev
  36. Group Excess Risk Bound of Overparameterized Linear Regression with Constant-Stepsize SGD
    Arjun Subramonian; Levent Sagun; Kai-Wei Chang; Yizhou Sun
  37. Strategy-Aware Contextual Bandits
    Keegan Harris; Chara Podimata; Steven Wu
  38. Addressing Bias in Face Detectors using Decentralised Data collection with incentives
    Ahan M R; Robin Lehmann; Richard Blythman
  39. Learning to Take a Break: Sustainable Optimization of Long-Term User Engagement
    Eden Saig; Nir Rosenfeld
  40. Explainability in Practice: Estimating Electrification Rates from Mobile Phone Data in Senegal
    Laura State; Hadrien Salat; Stefania Rubrichi; Zbigniew Smoreda
  41. Distributed Differential Privacy in Multi-Armed Bandits
    Sayak Ray Chowdhury; Xingyu Zhou
  42. Individual Privacy Accounting with Gaussian Differential Privacy
    Antti Koskela; Marlon Tobaben; Antti Honkela
  43. Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
    Jimmy Z. Di; Jack Douglas; Jayadev Acharya; Gautam Kamath; Ayush Sekhari
  44. PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales
    PeiFeng Wang; Aaron Chan; Filip Ilievski; Muhao Chen; Xiang Ren
  45. zPROBE: Zero Peek Robustness Checks for Federated Learning
    Zahra Ghodsi; Mojan Javaheripi; Nojan Sheybani; Xinqiao Zhang; Ke Huang; Farinaz Koushanfar
  46. A Theory of Learning with Competing Objectives and User Feedback
    Pranjal Awasthi; Corinna Cortes; Yishay Mansour; Mehryar Mohri
  47. Accelerating Open Science for AI in Heliophysics
    Dolores Garcia; Paul wright; Mark CM Cheung; Meng Jin; James Parr
  48. FL-Talk: Covert Communication in Federated Learning via Spectral Steganography
    Huili Chen; Farinaz Koushanfar
  49. Honest Students from Untrusted Teachers: Learning an Interpretable Question-Answering Pipeline from a Pretrained Language Model
    Jacob Eisenstein; Daniel Andor; Bernd Bohnet; Michael Collins; David Mimno
  50. Just Avoid Robust Inaccuracy: Boosting Robustness Without Sacrificing Accuracy
    Yannick Merkli; Pavol Bielik; PETAR TSANKOV; Martin Vechev
  51. Interactive Rationale Extraction for Text Classification
    Jiayi Dai; Mi-Young Kim; Randy Goebel
  52. Controllable Attack and Improved Adversarial Training in Multi-Agent Reinforcement Learning
    Xiangyu Liu; Souradip Chakraborty; Furong Huang
  53. Few-shot Backdoor Attacks via Neural Tangent Kernels
    Jonathan Hayase; Sewoong Oh
  54. Information-Theoretic Evaluation of Free-Text Rationales with Conditional $\mathcal{V}$-Information
    Hanjie Chen; Faeze Brahman; Xiang Ren; Yangfeng Ji; Yejin Choi; Swabha Swayamdipta
  55. Uncertainty-aware predictive modeling for fair data-driven decisions
    Patrick Kaiser; Christoph Kern; David Rügamer
  56. GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
    Paiheng Xu; Yuhang Zhou; Bang An; Wei Ai; Furong Huang
  57. Cooperation or Competition: Avoiding Player Domination for Multi-target Robustness by Adaptive Budgets
    Yimu Wang; Dinghuai Zhang; Yihan Wu; Heng Huang; Hongyang Zhang
  58. Revisiting Robustness in Graph Machine Learning
    Lukas Gosch; Daniel Sturm; Simon Geisler; Stephan Günnemann
  59. A Closer Look at the Intervention Procedure of Concept Bottleneck Models
    Sungbin Shin; Yohan Jo; Sungsoo Ahn; Namhoon Lee
  60. Striving for data-model efficiency: Identifying data externalities on group performance
    Esther Rolf; Ben Packer; Alex Beutel; Fernando Diaz
  61. Physically-Constrained Adversarial Attacks on Brain-Machine Interfaces
    Xiaying Wang; Rodolfo Octavio Siller Quintanilla; Michael Hersche; Luca Benini; Gagandeep Singh
  62. Training Differentially Private Graph Neural Networks with Random Walk Sampling
    Morgane Ayle; Jan Schuchardt; Lukas Gosch; Daniel Zügner; Stephan Günnemann
  63. Forgetting Data from Pre-trained GANs
    Zhifeng Kong; Kamalika Chaudhuri
  64. A Brief Overview of AI Governance for Responsible Machine Learning Systems
    Navdeep Gill; Marcos V. Conde
  65. Private Data Leakage via Exploiting Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems
    Hanieh Hashemi; Wenjie Xiong; Liu Ke; Kiwan Maeng; Murali Annavaram; G. Edward Suh; Hsien-Hsin S. Lee
  66. Benchmarking the Effect of Poisoning Defenses on the Security and Bias of the Final Model
    Nathalie Baracaldo; Kevin Eykholt; Farhan Ahmed; Yi Zhou; Shriti Priya; Taesung Lee; Swanand Kadhe; Yusong Tan; Sridevi Polavaram; Sterling Suggs
  67. A Fair Loss Function for Network Pruning
    Robbie Meyer; Alexander Wong
  68. DensePure: Understanding Diffusion Models towards Adversarial Robustness
    Chaowei Xiao; Zhongzhu Chen; Kun Jin; Jiongxiao Wang; Weili Nie; Mingyan Liu; Anima Anandkumar; Bo Li; Dawn Song
  69. Quantifying Social Biases Using Templates is Unreliable
    Preethi Seshadri; Pouya Pezeshkpour; Sameer Singh
  70. Real world relevance of generative counterfactual explanations
    Swami Sankaranarayanan; Thomas Hartvigsen; Lauren Oakden-Rayner; Marzyeh Ghassemi; Phillip Isola
  71. On the Robustness of deep learning-based MRI Reconstruction to image transformations
    Jinghan Jia; Mingyi Hong; Yimeng Zhang; Mehmet Akcakaya; Sijia Liu
  72. Denoised Smoothing with Sample Rejection for Robustifying Pretrained Classifiers
    Fatemeh Sheikholeslami; Wan-Yi Lin; Jan Hendrik Metzen; Huan Zhang; J Zico Kolter
  73. An Analysis of Social Biases Present in BERT Variants Across Multiple Languages
    Parishad BehnamGhader; Aristides Milios
  74. When Personalization Harms: Reconsidering the Use of Group Attributes of Prediction
    Vinith Menon Suriyakumar; Marzyeh Ghassemi; Berk Ustun
  75. Socially Responsible Reasoning with Large Language Models and The Impact of Proper Nouns
    Sumit Kumar Jha; Rickard Ewetz; Alvaro Velasquez; Susmit Jha
  76. Fairness-aware Missing Data Imputation
    Yiliang Zhang; Qi Long
  77. But Are You Sure? Quantifying Uncertainty in Model Explanations
    Charles Thomas Marx; Youngsuk Park; Hilaf Hasson; Bernie Wang; Stefano Ermon; Luke Huan
  78. On the Trade-Off between Actionable Explanations and the Right to be Forgotten
    Martin Pawelczyk; Tobias Leemann; Asia Biega; Gjergji Kasneci
  79. A Stochastic Optimization Framework for Fair Risk Minimization
    Andrew Lowy; Sina Baharlouei; Rakesh Pavan; Meisam Razaviyayn; Ahmad Beirami
  80. Beyond Protected Attributes: Disciplined Detection of Systematic Deviations in Data
    Adebayo Oshingbesan; Winslow Georgos Omondi; Girmaw Abebe Tadesse; Celia Cintas; Skyler Speakman
  81. Towards Reasoning-Aware Explainable VQA
    Rakesh Vaideeswaran; Feng Gao; ABHINAV MATHUR; Govind Thattai
  82. Learning from uncertain concepts via test time interventions
    Ivaxi Sheth; Aamer Abdul Rahman; Laya Rafiee Sevyeri; Mohammad Havaei; Samira Ebrahimi Kahou
  83. Generating Intuitive Fairness Specifications for Natural Language Processing
    Florian E. Dorner; Momchil Peychev; Nikola Konstantinov; Naman Goel; Elliott Ash; Martin Vechev
  84. Assessing Performance and Fairness Metrics in Face Recognition - Bootstrap Methods
    Jean-Rémy Conti; Stephan Clémençon
  85. Case Study: Applying Decision Focused Learning in the Real World
    Shresth Verma; Aditya Mate; Kai Wang; Aparna Taneja; Milind Tambe
  86. Inferring Class Label Distribution of Training Data from Classifiers: An Accuracy-Augmented Meta-Classifier Attack
    Raksha Ramakrishna; György Dán
  87. Improving Fairness in Image Classification via Sketching
    Ruichen Yao; Ziteng Cui; Xiaoxiao Li; Lin Gu