AAAI 2024

2,864 papers

Reasoning about Causality in Games (Abstract Reprint)

Lewis Hammond, James Fox, Tom Everitt, Ryan Carey, Alessandro Abate

Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ (Abstract Reprint)

Eoin Delaney, Arjun Pakrashi, Derek Greene, Mark T. Keane

Mimicking Behaviors in Separated Domains (Abstract Reprint)

Giuseppe De Giacomo, Dror Fried, Fabio Patrizi, Shufang Zhu

Temporal Logic Explanations for Dynamic Decision Systems Using Anchors and Monte Carlo Tree Search (Abstract Reprint)

Tzu-Yi Chiu, Jerome Le Ny, Jean-Pierre David

A General Model for Aggregating Annotations AcrossSimple, Complex, and Multi-object Annotation Tasks (Abstract Reprint)

Alexander Braylan, Madalyn Marabella, Omar Alonso, Matthew Lease

Monitoring of Perception Systems: Deterministic, Probabilistic, and Learning-Based Fault Detection and Identification (Abstract Reprint)

Pasquale Antonante, Heath Nilsen, Luca Carlone

Program Synthesis with Best-First Bottom-Up Search (Abstract Reprint)

Saqib Ameen, Levi H. S. Lelis

Select and Augment: Enhanced Dense Retrieval Knowledge Graph Augmentation (Abstract Reprint)

Micheal Abaho, Yousef H. Alfaifi

Combating Insider Threat in the Open-World Environments: Identification, Monitoring, and Data Augmentation

Dawei Zhou

Towards Reproducible, Automated, and Scalable Anomaly Detection

Yue Zhao

Fair and Optimal Prediction via Post-Processing

Han Zhao

Fairness with Censorship: Bridging the Gap between Fairness Research and Real-World Deployment

Wenbin Zhang

Towards Human-like Learning from Relational Structured Data

Quanming Yao

Towards Reliable Learning in the Wild: Generalization and Adaptation

Huaxiu Yao

Towards Trustworthy Deep Learning

Tsui-Wei (Lily) Weng

Exploiting Data Geometry in Machine Learning

Melanie Weber

Recent Advancements in Inverse Reinforcement Learning

Alberto Maria Metelli

Harmonious Mobility for Robots that Work with and around People

Christoforos Mavrogiannis

From Statistical Relational to Neuro-Symbolic Artificial Intelligence

Giuseppe Marra

Towards Holistic, Pragmatic and Multimodal Conversational Systems

Pranava Madhyastha

When Causal Inference Meets Graph Machine Learning

Jing Ma

Algorithmic Foundation of Federated Learning with Sequential Data

Mingrui Liu

The Role of Over-Parameterization in Machine Learning – the Good, the Bad, the Ugly

Fanghui Liu

Learning Representations for Robust Human-Robot Interaction

Yen-Ling Kuo

Quantifying Political Polarization through the Lens of Machine Translation and Vicarious Offense

Ashiqur R. KhudaBukhsh

Deep Learning on Graphs: A Data-Centric Exploration

Wei Jin

Fostering Trustworthiness in Machine Learning Algorithms

Mengdi Huai

Understanding Surprising Generalization Phenomena in Deep Learning

Wei Hu

Collaborative Learning across Heterogeneous Systems with Pre-Trained Models

Trong Nghia Hoang

Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction

Josiah P. Hanna

Continual Learning in an Open and Dynamic World

Yunhui Guo

Towards Robust Visual Understanding: from Recognition to Reasoning

Tejas Gokhale

Making Natural Language Reasoning Explainable and Faithful

Xinya Du

Data-Efficient Graph Learning

Kaize Ding

Demystifying Algorithmic Fairness in an Uncertain World

Lu Cheng

Symbolic Reasoning Methods for AI Planning

Gregor Behnke

Interactive Theorem Provers: Applications in AI, Opportunities, and Challenges

Mohammad Abdulaziz

Adventures of Trustworthy Vision-Language Models: A Survey

Mayank Vatsa, Anubhooti Jain, Richa Singh

Mixed Fair Division: A Survey

Shengxin Liu, Xinhang Lu, Mashbat Suzuki, Toby Walsh

Temporal Fairness in Multiwinner Voting

Edith Elkind, Svetlana Obraztsova, Nicholas Teh

The Fairness Fair: Bringing Human Perception into Collective Decision-Making

Hadi Hosseini

Regeneration Learning: A Learning Paradigm for Data Generation

Xu Tan, Tao Qin, Jiang Bian, Tie-yan Liu, Yoshua Bengio

Towards a More Burkean Approach to Computational Social Choice

Omer Lev

Integrated Systems for Computational Scientific Discovery

Pat Langley

Conversational Modeling for Constraint Satisfaction

Eugene C. Freuder

Model Reprogramming: Resource-Efficient Cross-Domain Machine Learning

Pin-Yu Chen

Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization

Craig Boutilier, Martin Mladenov, Guy Tennenholtz

TAU: Trajectory Data Augmentation with Uncertainty for Next POI Recommendation

Zhuang Zhuang, Tianxin Wei, Lingbo Liu, Heng Qi, Yanming Shen

AI-Based Energy Transportation Safety: Pipeline Radial Threat Estimation Using Intelligent Sensing System

Chengyuan Zhu, Yiyuan Yang, Kaixiang Yang, Haifeng Zhang, Qinmin Yang

Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation

Yuying Zhao, Yu Wang, Yi Zhang, Pamela Wisniewski, Charu Aggarwal

Multiple-Source Localization from a Single-Snapshot Observation Using Graph Bayesian Optimization

Zonghan Zhang, Zijian Zhang, Zhiqian Chen

Causally Aware Generative Adversarial Networks for Light Pollution Control

Yuyao Zhang, Ke Guo, Xiao Zhou

UV-SAM: Adapting Segment Anything Model for Urban Village Identification

Xin Zhang, Yu Liu, Yuming Lin, Qingmin Liao, Yong Li

Pre-trained Online Contrastive Learning for Insurance Fraud Detection

Rui Zhang, Dawei Cheng, jie Yang, Yi Ouyang, Xian Wu

Towards Automatic Boundary Detection for Human-AI Collaborative Hybrid Essay in Education

Zijie Zeng, Lele Sha, Yuheng Li, Kaixun Yang, Dragan Gasevic

Estimating On-Road Transportation Carbon Emissions from Open Data of Road Network and Origin-Destination Flow Data

Jinwei Zeng, Yu Liu, Jingtao Ding, Jian Yuan, Yong Li

Fairness-Aware Structured Pruning in Transformers

Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Ioana Baldini, Sarath Chandar

Graph Bayesian Optimization for Multiplex Influence Maximization

Zirui Yuan, Minglai Shao, Zhiqian Chen

Unveiling the Tapestry of Automated Essay Scoring: A Comprehensive Investigation of Accuracy, Fairness, and Generalizability

Kaixun Yang, Mladen Raković, Yuyang Li, Quanlong Guan, Dragan Gasevic

Spatial-Logic-Aware Weakly Supervised Learning for Flood Mapping on Earth Imagery

Zelin Xu, Tingsong Xiao, Wenchong He, Yu Wang, Zhe Jiang

Harnessing Network Effect for Fake News Mitigation: Selecting Debunkers via Self-Imitation Learning

Xiaofei Xu, Ke Deng, Michael Dann, Xiuzhen Zhang

HarvestNet: A Dataset for Detecting Smallholder Farming Activity Using Harvest Piles and Remote Sensing

Jonathan Xu, Amna Elmustafa, Liya Weldegebriel, Emnet Negash, Richard Lee

I Open at the Close: A Deep Reinforcement Learning Evaluation of Open Streets Initiatives

R. Teal Witter, Lucas Rosenblatt

SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models

Zhihao Wang, Yiqun Xie, Zhili Li, Xiaowei Jia, Zhe Jiang

Deep Reinforcement Learning for Early Diagnosis of Lung Cancer

Yifan Wang, Qining Zhang, Lei Ying, Chuan Zhou

RLPeri: Accelerating Visual Perimetry Test with Reinforcement Learning and Convolutional Feature Extraction

Tanvi Verma, Linh Le Dinh, Nicholas Tan, Xinxing Xu, Chingyu Cheng

Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance

Catalina Vajiac, Arun Frey, Joachim Baumann, Abigail Smith, Kasun Amarasinghe

Social, Legal, Ethical, Empathetic, and Cultural Rules: Compilation and Reasoning

Nicolas Troquard, Martina De Sanctis, Paola Inverardi, Patrizio Pelliccione, Gian Luca Scoccia

Stable Matchings in Practice: A Constraint Programming Approach

Zhaohong Sun, Naoyuki Yamada, Yoshihiro Takenami, Daisuke Moriwaki, Makoto Yokoo

FairPlay: A Multi-Sided Fair Dynamic Pricing Policy for Hotels

Errikos Streviniotis, Athina Georgara, Filippo Bistaffa, Georgios Chalkiadakis

Nowcasting Temporal Trends Using Indirect Surveys

Ajitesh Srivastava, Juan Marcos Ramirez, Sergio Díaz-Aranda, Jose Aguilar, Antonio Fernández Anta

Characterizing Information Seeking Events in Health-Related Social Discourse

Omar Sharif, Madhusudan Basak, Tanzia Parvin, Ava Scharfstein, Alphonso Bradham

Self-Supervised Framework Based on Subject-Wise Clustering for Human Subject Time Series Data

Eunseon Seong, Harim Lee, Dong-Kyu Chae

Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference

Travis Seale-Carlisle, Saksham Jain, Courtney Lee, Caroline Levenson, Swathi Ramprasad

Carbon Footprint Reduction for Sustainable Data Centers in Real-Time

Soumyendu Sarkar, Avisek Naug, Ricardo Luna, Antonio Guillen, Vineet Gundecha

IndicCONAN: A Multilingual Dataset for Combating Hate Speech in Indian Context

Nihar Ranja Sahoo, Gyana Prakash Beria, Pushpak Bhattacharyya

Discretionary Trees: Understanding Street-Level Bureaucracy via Machine Learning

Gaurab Pokharel, Sanmay Das, Patrick Fowler

DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling

Gustavo Perez, Subhransu Maji, Daniel Sheldon

Promoting Fair Vaccination Strategies through Influence Maximization: A Case Study on COVID-19 Spread

Nicola Neophytou, Afaf Taik, Golnoosh Farnadi

T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking

Pratheeksha Nair, Javin Liu, Catalina Vajiac, Andreas Olligschlaeger, Duen Horng Chau

Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models

Antoine Louis, Gijs van Dijck, Gerasimos Spanakis

Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling

Zhi Liu, Sarah Rankin, Nikhil Garg

Hear You Say You: An Efficient Framework for Marine Mammal Sounds’ Classification

Xiangrui Liu, Xiaoou Liu, Shan Du, Julian Cheng

On the Actionability of Outcome Prediction

Lydia T. Liu, Solon Barocas, Jon Kleinberg, Karen Levy

Depression Detection via Capsule Networks with Contrastive Learning

Han Liu, Changya Li, Xiaotong Zhang, Feng Zhang, Wei Wang

AutoLTS: Automating Cycling Stress Assessment via Contrastive Learning and Spatial Post-processing

Bo Lin, Shoshanna Saxe, Timothy C. Y. Chan

GLH-Water: A Large-Scale Dataset for Global Surface Water Detection in Large-Size Very-High-Resolution Satellite Imagery

Yansheng Li, Bo Dang, Wanchun Li, Yongjun Zhang

Combining Deep Learning and Street View Imagery to Map Smallholder Crop Types

Jordi Laguarta Soler, Thomas Friedel, Sherrie Wang

Vector Field Oriented Diffusion Model for Crystal Material Generation

Astrid Klipfel, Yaël Fregier, Adlane Sayede, Zied Bouraoui

Deploying ADVISER: Impact and Lessons from Using Artificial Intelligence for Child Vaccination Uptake in Nigeria

Opadele Kehinde, Ruth Abdul, Bose Afolabi, Parminder Vir, Corinne Namblard

Outlier Ranking for Large-Scale Public Health Data

Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld

Unraveling Pain Levels: A Data-Uncertainty Guided Approach for Effective Pain Assessment

Xinwei Ji, Xiaomin Chang, Wei Li, Albert Y. Zomaya

Adversarial Fairness Network

Taeuk Jang, Xiaoqian Wang, Heng Huang

Active Reinforcement Learning for Robust Building Control

Doseok Jang, Larry Yan, Lucas Spangher, Costas J. Spanos

Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages

Sameer Jain, Sedrick Scott Keh, Shova Chhetri, Karun Dewan, Pablo Izquierdo

iTrendRNN: An Interpretable Trend-Aware RNN for Meteorological Spatiotemporal Prediction

Xu Huang, Chuyao Luo, Bowen Zhang, Huiwei Lin, Xutao Li

CityPulse: Fine-Grained Assessment of Urban Change with Street View Time Series

Tianyuan Huang, Zejia Wu, Jiajun Wu, Jackelyn Hwang, Ram Rajagopal

Long-Term Fair Decision Making through Deep Generative Models

Yaowei Hu, Yongkai Wu, Lu Zhang

Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection

Beizhe Hu, Qiang Sheng, Juan Cao, Yuhui Shi, Yang Li

Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media

Liam Hebert, Gaurav Sahu, Yuxuan Guo, Nanda Kishore Sreenivas, Lukasz Golab