AAAI 2024

2,864 papers

Fair Graph Learning Using Constraint-Aware Priority Adjustment and Graph Masking in River Networks

Erhu He, Yiqun Xie, Alexander Sun, Jacob Zwart, jie Yang

Fair Multivariate Adaptive Regression Splines for Ensuring Equity and Transparency

Parian Haghighat, Denisa Gándara, Lulu Kang, Hadis Anahideh

Scaling Up Pareto Optimization for Tree Structures with Affine Transformations: Evaluating Hybrid Floating Solar-Hydropower Systems in the Amazon

Marc Grimson, Rafael Almeida, Qinru Shi, Yiwei Bai, Héctor Angarita

Federated Learning via Input-Output Collaborative Distillation

Xuan Gong, Shanglin Li, Yuxiang Bao, Barry Yao, Yawen Huang

Grey-Box Bayesian Optimization for Sensor Placement in Assisted Living Environments

Shadan Golestan, Omid Ardakanian, Pierre Boulanger

Benchmarking Cyber Harassment Dialogue Comprehension through Emotion-Informed Manifestations-Determinants Demarcation

Soumitra Ghosh, Gopendra Vikram Singh, Jashn Arora, Asif Ekbal

CLIPSyntel: CLIP and LLM Synergy for Multimodal Question Summarization in Healthcare

Akash Ghosh, Arkadeep Acharya, Raghav Jain, Sriparna Saha, Aman Chadha

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo Reis

Finding ε and δ of Traditional Disclosure Control Systems

Saswat Das, Keyu Zhu, Christine Task, Pascal Van Hentenryck, Ferdinando Fioretto

Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification

A. Feder Cooper, Katherine Lee, Madiha Zahrah Choksi, Solon Barocas, Christopher De Sa

Fair Sampling in Diffusion Models through Switching Mechanism

Yujin Choi, Jinseong Park, Hoki Kim, Jaewook Lee, Saerom Park

Identifying Guarantors of War Veterans Using Robust-SEAL: A Case of the Korean War

Jong in Choi, Won Kyung Lee, Jae Hwan Lee, So Young Sohn

Blind-Touch: Homomorphic Encryption-Based Distributed Neural Network Inference for Privacy-Preserving Fingerprint Authentication

Hyunmin Choi, Simon S. Woo, Hyoungshick Kim

Auto311: A Confidence-Guided Automated System for Non-emergency Calls

Zirong Chen, Xutong Sun, Yuanhe Li, Meiyi Ma

From Artificially Real to Real: Leveraging Pseudo Data from Large Language Models for Low-Resource Molecule Discovery

Yuhan Chen, Nuwa Xi, Yanrui Du, Haochun Wang, Jianyu Chen

Referee-Meta-Learning for Fast Adaptation of Locational Fairness

Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao

CariesXrays: Enhancing Caries Detection in Hospital-Scale Panoramic Dental X-rays via Feature Pyramid Contrastive Learning

Bingzhi Chen, Sisi Fu, Yishu Liu, Jiahui Pan, Guangming Lu

Decision-Making for Land Conservation: A Derivative-Free Optimization Framework with Nonlinear Inputs

Cassidy K. Buhler, Hande Y. Benson

Early Detection of Extreme Storm Tide Events Using Multimodal Data Processing

Marcel Barros, Andressa Pinto, Andres Monroy, Felipe Moreno, Jefferson Coelho

Quantile-Regression-Ensemble: A Deep Learning Algorithm for Downscaling Extreme Precipitation

Thomas Bailie, Yun Sing Koh, Neelesh Rampal, Peter B. Gibson

Physics-Informed Graph Neural Networks for Water Distribution Systems

Inaam Ashraf, Janine Strotherm, Luca Hermes, Barbara Hammer

Automatic Interpretation of Line Probe Assay Test for Tuberculosis

Jatin Agrawal, Mukul Kumar, Avtansh Tiwari, Sachin Danisetty, Soma Dhavala

A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing

Gabriel Agostini, Emma Pierson, Nikhil Garg

BirdCollect: A Comprehensive Benchmark for Analyzing Dense Bird Flock Attributes

Kshitiz ., Sonu Shreshtha, Bikash Dutta, Muskan Dosi, Mayank Vatsa

Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret

Adam Żychowski, Andrew Perrault, Jacek Mańdziuk

Closing the Gap: Achieving Better Accuracy-Robustness Tradeoffs against Query-Based Attacks

Pascal Zimmer, Sébastien Andreina, Giorgia Azzurra Marson, Ghassan Karame

DataElixir: Purifying Poisoned Dataset to Mitigate Backdoor Attacks via Diffusion Models

Jiachen Zhou, Peizhuo Lv, Yibing Lan, Guozhu Meng, Kai Chen

Can LLM Replace Stack Overflow? A Study on Robustness and Reliability of Large Language Model Code Generation

Li Zhong, Zilong Wang

AdvST: Revisiting Data Augmentations for Single Domain Generalization

Guangtao Zheng, Mengdi Huai, Aidong Zhang

UMA: Facilitating Backdoor Scanning via Unlearning-Based Model Ablation

Yue Zhao, Congyi Li, Kai Chen

Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility

Shanshan Zhao, Wenhai Cui, Bei Jiang, Linglong Kong, Xiaodong Yan

A Huber Loss Minimization Approach to Byzantine Robust Federated Learning

Puning Zhao, Fei Yu, Zhiguo Wan

GaLileo: General Linear Relaxation Framework for Tightening Robustness Certification of Transformers

Yunruo Zhang, Lujia Shen, Shanqing Guo, Shouling Ji

LR-XFL: Logical Reasoning-Based Explainable Federated Learning

Yanci Zhang, Han Yu

Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models

Jiang Zhang, Qiong Wu, Yiming Xu, Cheng Cao, Zheng Du

Enhancing Off-Policy Constrained Reinforcement Learning through Adaptive Ensemble C Estimation

Hengrui Zhang, Youfang Lin, Shuo Shen, Sheng Han, Kai Lv

Representation-Based Robustness in Goal-Conditioned Reinforcement Learning

Xiangyu Yin, Sihao Wu, Jiaxu Liu, Meng Fang, Xingyu Zhao

Providing Fair Recourse over Plausible Groups

Jayanth Yetukuri, Ian Hardy, Yevgeniy Vorobeychik, Berk Ustun, Yang Liu

Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood

Weisong Yang, Rafael Poyiadzi, Niall Twomey, Raul Santos-Rodriguez

Byzantine-Robust Decentralized Learning via Remove-then-Clip Aggregation

Caiyi Yang, Javad Ghaderi

The Evidence Contraction Issue in Deep Evidential Regression: Discussion and Solution

Yuefei Wu, Bin Shi, Bo Dong, Qinghua Zheng, Hua Wei

Concealing Sensitive Samples against Gradient Leakage in Federated Learning

Jing Wu, Munawar Hayat, Mingyi Zhou, Mehrtash Harandi

Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration

Honghao Wei, Xin Liu, Lei Ying

Physics-Informed Representation and Learning: Control and Risk Quantification

Zhuoyuan Wang, Reece Keller, Xiyu Deng, Kenta Hoshino, Takashi Tanaka

Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks

Zhenzhong Wang, Qingyuan Zeng, Wanyu Lin, Min Jiang, Kay Chen Tan

Moderate Message Passing Improves Calibration: A Universal Way to Mitigate Confidence Bias in Graph Neural Networks

Min Wang, Hao Yang, Jincai Huang, Qing Cheng

Would You Like Your Data to Be Trained? A User Controllable Recommendation Framework

Lei Wang, Xu Chen, Zhenhua Dong, Quanyu Dai

Identifying Reasons for Bias: An Argumentation-Based Approach

Madeleine Waller, Odinaldo Rodrigues, Oana Cocarascu

Long-Term Safe Reinforcement Learning with Binary Feedback

Akifumi Wachi, Wataru Hashimoto, Kazumune Hashimoto

Pure-Past Action Masking

Giovanni Varricchione, Natasha Alechina, Mehdi Dastani, Giuseppe De Giacomo, Brian Logan

Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban Scenes

Yuanpeng Tu, Yuxi Li, Boshen Zhang, Liang Liu, Jiangning Zhang

Toward More Generalized Malicious URL Detection Models

Yun-Da Tsai, Cayon Liow, Yin Sheng Siang, Shou-De Lin

Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention

Zhen Tan, Tianlong Chen, Zhenyu Zhang, Huan Liu

Quantile-Based Maximum Likelihood Training for Outlier Detection

Masoud Taghikhah, Nishant Kumar, Siniša Šegvić, Abouzar Eslami, Stefan Gumhold

Bidirectional Contrastive Split Learning for Visual Question Answering

Yuwei Sun, Hideya Ochiai

Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise

Hwanjun Song, Minseok Kim, Jae-Gil Lee

Towards Fairer Centroids in K-means Clustering

Stanley Simoes, Deepak P, Muiris MacCarthaigh

Human-Guided Moral Decision Making in Text-Based Games

Zijing Shi, Meng Fang, Ling Chen, Yali Du, Jun Wang

Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations

Mikołaj Sacha, Bartosz Jura, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor

A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy

Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco

I-CEE: Tailoring Explanations of Image Classification Models to User Expertise

Yao Rong, Peizhu Qian, Vaibhav Unhelkar, Enkelejda Kasneci

Dissenting Explanations: Leveraging Disagreement to Reduce Model Overreliance

Omer Reingold, Judy Hanwen Shen, Aditi Talati

Visual Adversarial Examples Jailbreak Aligned Large Language Models

Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang

Robust Stochastic Graph Generator for Counterfactual Explanations

Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo

A PAC Learning Algorithm for LTL and Omega-Regular Objectives in MDPs

Mateo Perez, Fabio Somenzi, Ashutosh Trivedi

Adversarial Initialization with Universal Adversarial Perturbation: A New Approach to Fast Adversarial Training

Chao Pan, Qing Li, Xin Yao

Understanding Likelihood of Normalizing Flow and Image Complexity through the Lens of Out-of-Distribution Detection

Genki Osada, Tsubasa Takahashi, Takashi Nishide

Q-SENN: Quantized Self-Explaining Neural Networks

Thomas Norrenbrock, Marco Rudolph, Bodo Rosenhahn

ORES: Open-Vocabulary Responsible Visual Synthesis

Minheng Ni, Chenfei Wu, Xiaodong Wang, Shengming Yin, Lijuan Wang

MaxEnt Loss: Constrained Maximum Entropy for Calibration under Out-of-Distribution Shift

Dexter Neo, Stefan Winkler, Tsuhan Chen

SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models

Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini

Neural Closure Certificates

Alireza Nadali, Vishnu Murali, Ashutosh Trivedi, Majid Zamani

EncryIP: A Practical Encryption-Based Framework for Model Intellectual Property Protection

Xin Mu, Yu Wang, Zhengan Huang, Junzuo Lai, Yehong Zhang

Reward Certification for Policy Smoothed Reinforcement Learning

Ronghui Mu, Leandro Soriano Marcolino, Yanghao Zhang, Tianle Zhang, Xiaowei Huang

Feature Unlearning for Pre-trained GANs and VAEs

Saemi Moon, Seunghyuk Cho, Dongwoo Kim

Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis

Rohan Mitta, Hosein Hasanbeig, Jun Wang, Daniel Kroening, Yiannis Kantaros

SentinelLMs: Encrypted Input Adaptation and Fine-Tuning of Language Models for Private and Secure Inference

Abhijit Mishra, Mingda Li, Soham Deo

Divide-and-Aggregate Learning for Evaluating Performance on Unlabeled Data

Shuyu Miao, Jian Liu, Lin Zheng, Hong Jin

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees

Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Ferdinando Cicalese

Combining Graph Transformers Based Multi-Label Active Learning and Informative Data Augmentation for Chest Xray Classification

Dwarikanath Mahapatra, Behzad Bozorgtabar, Zongyuan Ge, Mauricio Reyes, Jean-Philippe Thiran

Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning

Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham

Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning

Tao Liu, Yuhang Zhang, Zhu Feng, Zhiqin Yang, Chen Xu

Game-Theoretic Unlearnable Example Generator

Shuang Liu, Yihan Wang, Xiao-Shan Gao

PointCVaR: Risk-Optimized Outlier Removal for Robust 3D Point Cloud Classification

Xinke Li, Junchi Lu, Henghui Ding, Changsheng Sun, Joey Tianyi Zhou

Revisiting the Information Capacity of Neural Network Watermarks: Upper Bound Estimation and Beyond

Fangqi Li, Haodong Zhao, Wei Du, Shilin Wang

Promoting Counterfactual Robustness through Diversity

Francesco Leofante, Nico Potyka

I Prefer Not to Say: Protecting User Consent in Models with Optional Personal Data

Tobias Leemann, Martin Pawelczyk, Christian Thomas Eberle, Gjergji Kasneci

Exponent Relaxation of Polynomial Zonotopes and Its Applications in Formal Neural Network Verification

Tobias Ladner, Matthias Althoff

Contrastive Credibility Propagation for Reliable Semi-supervised Learning

Brody Kutt, Pralay Ramteke, Xavier Mignot, Pamela Toman, Nandini Ramanan

Towards Large Certified Radius in Randomized Smoothing Using Quasiconcave Optimization

Bo-Han Kung, Shang-Tse Chen

Robust Active Measuring under Model Uncertainty

Merlijn Krale, Thiago D. Simão, Jana Tumova, Nils Jansen

Accelerating Adversarially Robust Model Selection for Deep Neural Networks via Racing

Matthias König, Holger H. Hoos, Jan N. van Rijn

OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples

Ryuto Koike, Masahiro Kaneko, Naoaki Okazaki

Quilt: Robust Data Segment Selection against Concept Drifts

Minsu Kim, Seong-Hyeon Hwang, Steven Euijong Whang

Layer Attack Unlearning: Fast and Accurate Machine Unlearning via Layer Level Attack and Knowledge Distillation

Hyunjune Kim, Sangyong Lee, Simon S. Woo

DeepBern-Nets: Taming the Complexity of Certifying Neural Networks Using Bernstein Polynomial Activations and Precise Bound Propagation

Haitham Khedr, Yasser Shoukry

Assume-Guarantee Reinforcement Learning

Milad Kazemi, Mateo Perez, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi

Chasing Fairness in Graphs: A GNN Architecture Perspective

Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou

Analysis of Differentially Private Synthetic Data: A Measurement Error Approach

Yangdi Jiang, Yi Liu, Xiaodong Yan, Anne-Sophie Charest, Linglong Kong

NeRFail: Neural Radiance Fields-Based Multiview Adversarial Attack

Wenxiang Jiang, Hanwei Zhang, Xi Wang, Zhongwen Guo, Hao Wang