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Accepted Papers

  1. Controllable Attack and Improved Adversarial Training in Multi-Agent Reinforcement Learning
    Outstanding Paper Award
    Contributed talk (09:45 - 10:00)
    Xiangyu Liu; Souradip Chakraborty; Furong Huang
  2. Differentially Private Bias-Term only Fine-tuning of Foundation Models
    Outstanding Paper Award
    Contributed talk (16:30 - 16:45)
    Zhiqi Bu; Yu-Xiang Wang; Sheng Zha; George Karypis
  3. zPROBE: Zero Peek Robustness Checks for Federated Learning
    Outstanding Paper Award
    Contributed talk (17:00 - 17:15)
    Zahra Ghodsi; Mojan Javaheripi; Nojan Sheybani; Xinqiao Zhang; Ke Huang; Farinaz Koushanfar
  4. Revisiting Robustness in Graph Machine Learning
    Contributed talk (09:30 - 09:45)
    Lukas Gosch; Daniel Sturm; Simon Geisler; Stephan Günnemann
  5. DensePure: Understanding Diffusion Models towards Adversarial Robustness
    Contributed talk (15:30 - 15:40)
    Zhongzhu Chen; Kun Jin; Jiongxiao Wang; Weili Nie; Mingyan Liu; Anima Anandkumar; Bo Li; Dawn Song
  6. TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations
    Contributed talk (16:45 - 17:00)
    Dylan Z Slack; Satyapriya Krishna; Himabindu Lakkaraju; Sameer Singh
  7. Take 5: Interpretable Image Classification with a Handful of Features
    Thomas Norrenbrock; Marco Rudolph; Bodo Rosenhahn
  8. Membership Inference Attacks via Adversarial Examples
    Hamid Jalalzai; Elie KADOCHE; Rémi Leluc; Vincent Plassier
  9. Scalable and Improved Algorithms for Individually Fair Clustering
    Mohammadhossein Bateni; Vincent Cohen-Addad; Alessandro Epasto; Silvio Lattanzi
  10. Not All Knowledge Is Created Equal: Mutual Distillation of Confident Knowledge
    ZIYUN LI; Xinshao Wang; Di Hu; Neil M. Robertson; David A. Clifton; Christoph Meinel; Haojin Yang
  11. Just Following AI Orders: When Unbiased People Are Influenced By Biased AI
    Hammaad Adam; Aparna Balagopalan; Emily Alsentzer; Fotini Christia; Marzyeh Ghassemi
  12. Towards Algorithmic Fairness in Space-Time: Filling in Black Holes
    Cheryl Brooks; Aritra Guha; Subhabrata Majumdar; Divesh Srivastava; Zhengyi Zhou
  13. 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
  14. On the Feasibility of Compressing Certifiably Robust Neural Networks
    Pratik Vaishnavi; Veena Krish; Farhan Ahmed; Kevin Eykholt; Amir Rahmati
  15. When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes
    Canyu Chen; Yueqing Liang; Xiongxiao Xu; Shangyu Xie; Yuan Hong; Kai Shu
  16. Visual Prompting for Adversarial Robustness
    Aochuan Chen; Peter Lorenz; Yuguang Yao; Pin-Yu Chen; Sijia Liu
  17. Is the Next Winter Coming for AI?The Elements of Making Secure and Robust AI
    Joshua Harguess
  18. Attack-Agnostic Adversarial Detection
    Jiaxin Cheng; Mohamed E. Hussein; Jayadev Billa; Wael AbdAlmgaeed
  19. Provable Membership Inference Privacy
    Zachary Izzo; Jinsung Yoon; Sercan O Arik; James Zou
  20. Anonymization for Skeleton Action Recognition
    Saemi Moon; Myeonghyeon Kim; Zhenyue Qin; Yang Liu; Dongwoo Kim
  21. Men Also Do Laundry: Multi-Attribute Bias Amplification
    Dora Zhao; Jerone Theodore Alexander Andrews; Alice Xiang
  22. Cold Posteriors through PAC-Bayes
    Konstantinos Pitas; Julyan Arbel
  23. Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation
    Maksym Yatsura; Kaspar Sakmann; N. Grace Hua; Matthias Hein; Jan Hendrik Metzen
  24. Bias Amplification in Image Classification
    Melissa Hall; Laurens van der Maaten; Laura Gustafson; Maxwell Jones; Aaron Bryan Adcock
  25. Hybrid-EDL: Improving Evidential Deep Learning for Uncertainty Quantification on Imbalanced Data
    Tong Xia; Jing Han; Lorena Qendro; Ting Dang; Cecilia Mascolo
  26. Indiscriminate Data Poisoning Attacks on Neural Networks
    Yiwei Lu; Gautam Kamath; Yaoliang Yu
  27. Finding Safe Zones of Markov Decision Processes Policies
    Michal Moshkovitz; Lee Cohen; Yishay Mansour
  28. 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
  29. Poisoning Generative Models to Promote Catastrophic Forgetting
    Siteng Kang; Xinhua Zhang
  30. On Causal Rationalization
    Wenbo Zhang; TONG WU; Yunlong Wang; Yong Cai; Hengrui Cai
  31. A View From Somewhere: Human-Centric Face Representations
    Jerone Theodore Alexander Andrews; Przemyslaw Joniak; Alice Xiang
  32. 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
  33. What Makes a Good Explanation?: A Harmonized View of Properties of Explanations
    Zixi Chen; Varshini Subhash; Marton Havasi; Weiwei Pan; Finale Doshi-Velez
  34. On the Impact of Adversarially Robust Models on Algorithmic Recourse
    Satyapriya Krishna; Chirag Agarwal; Himabindu Lakkaraju
  35. Participatory Systems for Personalized Prediction
    Hailey James; Chirag Nagpal; Katherine A Heller; Berk Ustun
  36. Differentially Private Gradient Boosting on Linear Learners for Tabular Data
    Saeyoung Rho; Cedric Archambeau; Sergul Aydore; Beyza Ermis; Michael Kearns; Aaron Roth; Shuai Tang; Yu-Xiang Wang; Steven Wu
  37. 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
  38. Evaluating the Practicality of Counterfactual Explanations
    Nina Spreitzer; Hinda Haned; Ilse van der Linden
  39. Certified Training: Small Boxes are All You Need
    Mark Niklas Mueller; Franziska Eckert; Marc Fischer; Martin Vechev
  40. Group Excess Risk Bound of Overparameterized Linear Regression with Constant-Stepsize SGD
    Arjun Subramonian; Levent Sagun; Kai-Wei Chang; Yizhou Sun
  41. Strategy-Aware Contextual Bandits
    Keegan Harris; Chara Podimata; Steven Wu
  42. Addressing Bias in Face Detectors using Decentralised Data collection with incentives
    Ahan M R; Robin Lehmann; Richard Blythman
  43. Learning to Take a Break: Sustainable Optimization of Long-Term User Engagement
    Eden Saig; Nir Rosenfeld
  44. Explainability in Practice: Estimating Electrification Rates from Mobile Phone Data in Senegal
    Laura State; Hadrien Salat; Stefania Rubrichi; Zbigniew Smoreda
  45. Distributed Differential Privacy in Multi-Armed Bandits
    Sayak Ray Chowdhury; Xingyu Zhou
  46. Individual Privacy Accounting with Gaussian Differential Privacy
    Antti Koskela; Marlon Tobaben; Antti Honkela
  47. Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
    Jimmy Z. Di; Jack Douglas; Jayadev Acharya; Gautam Kamath; Ayush Sekhari
  48. PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales
    PeiFeng Wang; Aaron Chan; Filip Ilievski; Muhao Chen; Xiang Ren
  49. A Theory of Learning with Competing Objectives and User Feedback
    Pranjal Awasthi; Corinna Cortes; Yishay Mansour; Mehryar Mohri
  50. Accelerating Open Science for AI in Heliophysics
    Dolores Garcia; Paul James Wright; Robert Jarolim; Mark CM Cheung; Meng Jin; James Parr
  51. FL-Talk: Covert Communication in Federated Learning via Spectral Steganography
    Huili Chen; Farinaz Koushanfar
  52. 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
  53. Just Avoid Robust Inaccuracy: Boosting Robustness Without Sacrificing Accuracy
    Yannick Merkli; Pavol Bielik; PETAR TSANKOV; Martin Vechev
  54. Interactive Rationale Extraction for Text Classification
    Jiayi Dai; Mi-Young Kim; Randy Goebel
  55. Few-shot Backdoor Attacks via Neural Tangent Kernels
    Jonathan Hayase; Sewoong Oh
  56. Information-Theoretic Evaluation of Free-Text Rationales with Conditional $\mathcal{V}$-Information
    Hanjie Chen; Faeze Brahman; Xiang Ren; Yangfeng Ji; Yejin Choi; Swabha Swayamdipta
  57. Uncertainty-aware predictive modeling for fair data-driven decisions
    Patrick Kaiser; Christoph Kern; David Rügamer
  58. GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
    Paiheng Xu; Yuhang Zhou; Bang An; Wei Ai; Furong Huang
  59. Cooperation or Competition: Avoiding Player Domination for Multi-target Robustness by Adaptive Budgets
    Yimu Wang; Dinghuai Zhang; Yihan Wu; Heng Huang; Hongyang Zhang
  60. A Closer Look at the Intervention Procedure of Concept Bottleneck Models
    Sungbin Shin; Yohan Jo; Sungsoo Ahn; Namhoon Lee
  61. Striving for data-model efficiency: Identifying data externalities on group performance
    Esther Rolf; Ben Packer; Alex Beutel; Fernando Diaz
  62. Physically-Constrained Adversarial Attacks on Brain-Machine Interfaces
    Xiaying Wang; Rodolfo Octavio Siller Quintanilla; Michael Hersche; Luca Benini; Gagandeep Singh
  63. Training Differentially Private Graph Neural Networks with Random Walk Sampling
    Morgane Ayle; Jan Schuchardt; Lukas Gosch; Daniel Zügner; Stephan Günnemann
  64. Data Redaction from Pre-trained GANs
    Zhifeng Kong; Kamalika Chaudhuri
  65. A Brief Overview of AI Governance for Responsible Machine Learning Systems
    Navdeep Gill; Abhishek Mathur; Marcos V. Conde
  66. 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
  67. 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; Yuyang Gao; David Slater
  68. A Fair Loss Function for Network Pruning
    Robbie Meyer; Alexander Wong
  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. 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