AAAI

Temporal Graph Neural Network-Powered Paper Recommendation on Dynamic Citation Networks

Junhao Shen, Mohammad Ausaf Ali Haqqani, Beichen Hu, Cheng Huang, Xihao Xie, Tsengdar Lee, Jia Zhang

Comments 10 pages, 4 figures, accepted by SDU@AAAI-2024. The AAAI Workshop on Scientific Document Understanding (2024)

What Is Required for Empathic AI? It Depends, and Why That Matters for AI Developers and Users

Jana Schaich Borg, Hannah Read

Comments To appear at the 7th AAAI/ACM Conference on AI, Ethics, and Society, 2024

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

Cassidy K. Buhler, Hande Y. Benson

Comments 11 pages, 6 figures. This is the extended version of our paper accepted to the Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24). This version includes the technical appendix

Preliminary Investigations of a Multi-Faceted Robust and Synergistic Approach in Semiconductor Electron Micrograph Analysis: Integrating Vision Transformers with Large Language and Multimodal Models

Sakhinana Sagar Srinivas, Geethan Sannidhi, Sreeja Gangasani, Chidaksh Ravuru, Venkataramana Runkana

Comments Published at Deployable AI (DAI) Workshop at AAAI-2024

Unboxing Occupational Bias: Grounded Debiasing of LLMs with U.S. Labor Data

Atmika Gorti, Manas Gaur, Aman Chadha

Comments Accepted in AAAI Spring Symposium 2024

Rank, Pack, or Approve: Voting Methods in Participatory Budgeting

Lodewijk Gelauff, Ashish Goel

Comments Accepted for publication at ICWSM. Data set is available through: https://doi.org/10.25740/db709zg9088

Journal ref Proceedings of the International AAAI Conference on Web and Social Media, 18 (2024) 448-461

Reprogramming Foundational Large Language Models(LLMs) for Enterprise Adoption for Spatio-Temporal Forecasting Applications: Unveiling a New Era in Copilot-Guided Cross-Modal Time Series Representation Learning

Sakhinana Sagar Srinivas, Chidaksh Ravuru, Geethan Sannidhi, Venkataramana Runkana

Comments Paper published at the Deployable AI (DAI) workshop at AAAI-2024

Emotion-Agent: Unsupervised Deep Reinforcement Learning with Distribution-Prototype Reward for Continuous Emotional EEG Analysis

Zhihao Zhou, Qile Liu, Jiyuan Wang, Zhen Liang

Comments 11 pages, 4 figures, 4 tables, submitted to AAAI 2025

Why am I Still Seeing This: Measuring the Effectiveness Of Ad Controls and Explanations in AI-Mediated Ad Targeting Systems

Jane Castleman, Aleksandra Korolova

Comments Accepted to the 7th AAAI Conference on AI, Ethics, and Society (AIES, 2024)

Robust Policy Learning via Offline Skill Diffusion

Woo Kyung Kim, Minjong Yoo, Honguk Woo

Comments 11 pages, 6 figures; Accepted for AAAI Conference on Artificial Intelligence (AAAI 2024); Published version

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

Kyra Wilson, Aylin Caliskan

Comments To be published in Proceedings of the 2024 AAAI/ACM Conference on AI, Ethics, and Society; code available at https://github.com/kyrawilson/Resume-Screening-Bias

Semi-Supervised Learning with Multi-Head Co-Training

Mingcai Chen, Yuntao Du, Yi Zhang, Shuwei Qian, Chongjun Wang

Comments The 36th AAAI Conference on Artificial Intelligence (AAAI-22)

SoftTiger: A Clinical Foundation Model for Healthcare Workflows

Ye Chen, Igor Couto, Wei Cai, Cong Fu, Bruno Dorneles

Comments Accepted to AAAI 2024 Spring Symposium on Clinical Foundation Models, Stanford University, Stanford, California

NeuralMatrix: Compute the Entire Neural Networks with Linear Matrix Operations for Efficient Inference

Ruiqi Sun, Siwei Ye, Jie Zhao, Xin He, Jianzhe Lin, Yiran Li, An Zou

Comments 9 pages, 8figures, Submitted to The 39th Annual AAAI Conference on Artificial Intelligence

As an AI Language Model, "Yes I Would Recommend Calling the Police": Norm Inconsistency in LLM Decision-Making

Shomik Jain, D Calacci, Ashia Wilson

Comments To appear in the proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES 2024)

Black-Box Anomaly Attribution

Tsuyoshi Idé, Naoki Abe

Comments This is an expanded version of Idé et al.,"Anomaly Attribution with Likelihood Compensation,'' AAAI 21. Part of the content has also been presented in Idé and Abe.,"Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution,'' KDD 23. The original version was submitted to a journal on May 8, 2021

Mitigating Degree Bias in Signed Graph Neural Networks

Fang He, Jinhai Deng, Ruizhan Xue, Maojun Wang, Zeyu Zhang

Comments 10 pages, 7 figures, The 39th Annual AAAI Conference on Artificial Intelligence

Automating Transparency Mechanisms in the Judicial System Using LLMs: Opportunities and Challenges

Ishana Shastri, Shomik Jain, Barbara Engelhardt, Ashia Wilson

Comments Accepted at the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES 2024)

Enhancing Equitable Access to AI in Housing and Homelessness System of Care through Federated Learning

Musa Taib, Jiajun Wu, Steve Drew, Geoffrey G. Messier

Comments Accepted at the 2024 AAAI/ACM Conference on AI, Ethics, and Society (AIES)

Consistency Based Weakly Self-Supervised Learning for Human Activity Recognition with Wearables

Taoran Sheng, Manfred Huber

Journal ref AAAI-22 Workshop on Human-Centric SelfSupervised Learning, 2022

aedFaCT: Scientific Fact-Checking Made Easier via Semi-Automatic Discovery of Relevant Expert Opinions

Enes Altuncu, Jason R. C. Nurse, Meryem Bagriacik, Sophie Kaleba, Haiyue Yuan, Lisa Bonheme, Shujun Li

Comments Accepted for publication in the Proceedings of the Workshop on News Media and Computational Journalism (MEDIATE '23), co-located with the AAAI International Conference on Web and Social Media (ICWSM '23)

Journal ref Workshop Proceedings of the 17th International AAAI Conference on Web and Social Media (2023) 1-10

Sync-NeRF: Generalizing Dynamic NeRFs to Unsynchronized Videos

Seoha Kim, Jeongmin Bae, Youngsik Yun, Hahyun Lee, Gun Bang, Youngjung Uh

Comments AAAI 2024. Project page: https://seoha-kim.github.io/sync-nerf

Mixed Fair Division: A Survey

Shengxin Liu, Xinhang Lu, Mashbat Suzuki, Toby Walsh

Comments Appears in the 38th AAAI Conference on Artificial Intelligence (AAAI), Senior Member Presentation Track, 2024

Journal ref Journal of Artificial Intelligence Research (JAIR), 80:1373-1406, 2024

Examining the Behavior of LLM Architectures Within the Framework of Standardized National Exams in Brazil

Marcelo Sartori Locatelli, Matheus Prado Miranda, Igor Joaquim da Silva Costa, Matheus Torres Prates, Victor Thomé, Mateus Zaparoli Monteiro, Tomas Lacerda, Adriana Pagano, Eduardo Rios Neto, Wagner Meira, Virgilio Almeida

Comments Accepted at the Seventh AAAI/ACM Conference on AI, Ethics and Society (AIES 2024). 14 pages, 4 figures

Artificial Intelligence based Approach for Identification and Mitigation of Cyber-Attacks in Wide-Area Control of Power Systems

Jishnudeep Kar, Aranya Chakrabortty

Comments AAAI 2023 workshop

Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning

Huy Hoang, Tien Mai, Pradeep Varakantham

Journal ref AAAI 2024

Dissenting Explanations: Leveraging Disagreement to Reduce Model Overreliance

Omer Reingold, Judy Hanwen Shen, Aditi Talati

Comments V2: AAAI 2024 V1: AI & HCI Workshop at ICML 2023

Quantifying gendered citation imbalance in computer science conferences

Kazuki Nakajima, Yuya Sasaki, Sohei Tokuno, George Fletcher

Comments 14 pages, 6 figures, and 7 tables. This work has been accepted as a full paper in the AAAI/ACM conference on Artificial Intelligence, Ethics and Society (AIES) 2024

Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance

Mohammmad Tahaei, Daricia Wilkinson, Alisa Frik, Michael Muller, Ruba Abu-Salma, Lauren Wilcox

Comments To appear in 7th AAAI Conference on AI, Ethics, and Society (AIES)

Estimating Environmental Cost Throughout Model's Adaptive Life Cycle

Vishwesh Sangarya, Richard Bradford, Jung-Eun Kim

Comments Accepted in the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, 2024