AAAI

Removing Non-Stationary Knowledge From Pre-Trained Language Models for Entity-Level Sentiment Classification in Finance

Guijin Son, Hanwool Lee, Nahyeon Kang, Moonjeong Hahm

Comments Published at The AAAI-2023 Workshop On Multimodal AI For Financial Forecasting (muffin@AAAI2023)

Contrastive Triple Extraction with Generative Transformer

Hongbin Ye, Ningyu Zhang, Shumin Deng, Mosha Chen, Chuanqi Tan, Fei Huang, Huajun Chen

Comments Accepted by AAAI 2021

Meta-Learning PAC-Bayes Priors in Model Averaging

Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li

Comments Accepted by AAAI 2020

Leveraging Vision-Language Models for Granular Market Change Prediction

Christopher Wimmer, Navid Rekabsaz

Comments Accepted at Multimodal AI for Financial Forecasting Workshop (Muffin) at AAAI 2023

Effective Baselines for Multiple Object Rearrangement Planning in Partially Observable Mapped Environments

Engin Tekin, Elaheh Barati, Nitin Kamra, Ruta Desai

Comments AAAI 2023 Workshop on User-Centric Artificial Intelligence for Assistance in At-Home Tasks

Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection

Peter Henderson, Ben Chugg, Brandon Anderson, Kristen Altenburger, Alex Turk, John Guyton, Jacob Goldin, Daniel E. Ho

Comments Accepted to the Thirty-Seventh AAAI Conference On Artificial Intelligence (AAAI), 2023

A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-run Langevin Flow for Approximate Inference

Jianwen Xie, Yaxuan Zhu, Yifei Xu, Dingcheng Li, Ping Li

Comments The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI) 2023

MATT: Multimodal Attention Level Estimation for e-learning Platforms

Roberto Daza, Luis F. Gomez, Aythami Morales, Julian Fierrez, Ruben Tolosana, Ruth Cobos, Javier Ortega-Garcia

Comments Preprint of the paper presented to the Workshop on Artificial Intelligence for Education (AI4EDU) of AAAI 2023

The Shape of Explanations: A Topological Account of Rule-Based Explanations in Machine Learning

Brett Mullins

Comments Accepted by The AAAI 2023 Workshop on Representation Learning for Responsible Human-Centric AI

Sustaining Fairness via Incremental Learning

Somnath Basu Roy Chowdhury, Snigdha Chaturvedi

Comments Accepted at AAAI 2023

Estimating average causal effects from patient trajectories

Dennis Frauen, Tobias Hatt, Valentyn Melnychuk, Stefan Feuerriegel

Comments Accepted at AAAI 2023

Towards Understanding How Self-training Tolerates Data Backdoor Poisoning

Soumyadeep Pal, Ren Wang, Yuguang Yao, Sijia Liu

Comments Accepted at SafeAI 2023: AAAI's Workshop on Artificial Intelligence Safety

Latent Autoregressive Source Separation

Emilian Postolache, Giorgio Mariani, Michele Mancusi, Andrea Santilli, Luca Cosmo, Emanuele Rodolà

Comments Accepted to AAAI 2023

Towards Long-term Autonomy: A Perspective from Robot Learning

Zhi Yan, Li Sun, Tomas Krajnik, Tom Duckett, Nicola Bellotto

Comments Accepted by AAAI-23 Bridge Program on AI & Robotics

On the Vulnerability of Backdoor Defenses for Federated Learning

Pei Fang, Jinghui Chen

Comments Accepted by AAAI 2023 (15 pages, 12 figures, 7 tables)

Music Playlist Title Generation Using Artist Information

Haven Kim, SeungHeon Doh, Junwon Lee, Juhan Nam

Comments AAAI-23 Workshop on Creative AI Across Modalities

Decision-Focused Evaluation: Analyzing Performance of Deployed Restless Multi-Arm Bandits

Paritosh Verma, Shresth Verma, Aditya Mate, Aparna Taneja, Milind Tambe

Comments 11 pages, 3 figures, AI for Social Good Workshop (AAAI'23)

Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training

Yuting Ning, Zhenya Huang, Xin Lin, Enhong Chen, Shiwei Tong, Zheng Gong, Shijin Wang

Comments Accepted by AAAI 2023

AutoFraudNet: A Multimodal Network to Detect Fraud in the Auto Insurance Industry

Azin Asgarian, Rohit Saha, Daniel Jakubovitz, Julia Peyre

Comments Published at The AAAI-2023 Workshop On Multimodal AI For Financial Forecasting

Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing

Jinyang Li, Binyuan Hui, Reynold Cheng, Bowen Qin, Chenhao Ma, Nan Huo, Fei Huang, Wenyu Du, Luo Si, Yongbin Li

Comments Accepted to AAAI 2023 main conference (oral)

Adversarial Robust Deep Reinforcement Learning Requires Redefining Robustness

Ezgi Korkmaz

Comments Published in AAAI 2023

Towards Voice Reconstruction from EEG during Imagined Speech

Young-Eun Lee, Seo-Hyun Lee, Sang-Ho Kim, Seong-Whan Lee

Comments 9 pages, 4 figures, accepted paper of AAAI 2023 in main track

Story Realization: Expanding Plot Events into Sentences

Prithviraj Ammanabrolu, Ethan Tien, Wesley Cheung, Zhaochen Luo, William Ma, Lara J. Martin, Mark O. Riedl

Comments In proceedings of AAAI 2020

Journal ref AAAI Conference on Artificial Intelligence (AAAI), vol. 34, no. 5, pp. 7375-7382, Apr. 2020

Event Representations for Automated Story Generation with Deep Neural Nets

Lara J. Martin, Prithviraj Ammanabrolu, Xinyu Wang, William Hancock, Shruti Singh, Brent Harrison, Mark O. Riedl

Comments Submitted to AAAI'18

Journal ref Thirty-Second AAAI Conference on Artificial Intelligence, vol. 32, no. 1, pp. 868-875, Apr. 2018

Memory-Augmented Theory of Mind Network

Dung Nguyen, Phuoc Nguyen, Hung Le, Kien Do, Svetha Venkatesh, Truyen Tran

Comments Accepted for publication at AAAI 2023

TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)

Răzvan-Alexandru Smădu, George-Eduard Zaharia, Andrei-Marius Avram, Dumitru-Clementin Cercel, Mihai Dascalu, Florin Pop

Comments Accepted by AAAI 2023 Student Abstract

Causal Recurrent Variational Autoencoder for Medical Time Series Generation

Hongming Li, Shujian Yu, Jose Principe

Comments Manuscript accepted by AAAI-23. Code is publicly available at \url{https://github.com/hongmingli1995/CR-VAE}

A Coreset Learning Reality Check

Fred Lu, Edward Raff, James Holt

Comments To appear in the Thirty-Seventh AAAI Conference on Artificial Intelligence

Competition, Alignment, and Equilibria in Digital Marketplaces

Meena Jagadeesan, Michael I. Jordan, Nika Haghtalab

Comments To appear at AAAI 2023

Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis

Thi Kieu Khanh Ho, Narges Armanfard

Comments Accepted at AAAI-23 (Oral)