Submission Instructions

We welcome full paper submissions (up to 7 pages, excluding references or supplementary materials). Please submit at the following CMT website:
AIBSD 2024 CMT submission website. 

The paper submissions must be in pdf format and use the AAAI 2024 official templates. All submissions must be anonymous and conform to the AAAI 2024 standards for double-blind review. The accepted papers will be posted on the workshop website and will not appear in the AAAI 2024 proceedings. At least one author of each accepted submission must present the paper at the workshop in person.  

Submission deadline: November 17 24, 2023 AOE Time (one week extension)  
Notification to authors: December 11, 2023
Camera ready deadline:  December 18, 2023 AOE Time

We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. Accepted work will be presented as either an oral or a spotlight presentation. 

Topics

The topics for AIBSD 2024 include, but are not limited to:

• Algorithms and theories for explainable and interpretable AI models
• Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc.
• Algorithms and theories for learning AI models under bias and scarcity.
• Performance characterization of AI algorithms and systems under bias and scarcity
• Algorithms for secure and privacy-aware machine learning for AI
• Algorithms and theories for trustworthy AI models
• The role of adjacent fields of study (e.g, computational social science) in mitigating issues of bias and trust in AI
• Continuous refinement of AI models using active/online learning
• Meta-learning models from various existing task-specific AI models
• Limitation of or methods incorporating large language model under bias and/or data scarcity settings
• Brave new ideas to learn AI models under bias and scarcity

Instructions of Publication Preparation

We plan to publish the accepted papers with Computer Sciences & Mathematics Forum by MDPI in the way similar to the workshop proceedings of AIBSD 2022. For the authors of the accpeted papers, please format your paper using the official MDPI template (LaTeX). Please also submit all the source files (compressed as a .zip file) together with the compiled .pdf file via CMT. If the camera ready paper and the corresponding LaTeX source file are not submitted in the correct format on time, then the publication of the paper cannot be guaranteed.

Camera ready deadline: January 5, 2024 AOE Time  

• Small Dataset, Big Gains: Enhancing Reinforcement Learning by Offline Pre-Training with Model Based Augmentation.
  Girolamo Macaluso, Alessandro Sestini, Andy Bagdanov.
  


• Frustratingly Easy Environment Discovery for Invariant Learning.
  Samira Zare, Hien V. Nguyen.
  


• Exploring 3D Object Detection for Autonomous Factory Driving: Advanced Research on Handling Limited Annotations with Ground Truth Sampling Augmentation.
  Matthias Reuse, Martin Simon, Karl Amende, Bernhard Sick.
  


• Hypothesis Network Planned Exploration for Rapid Meta-Reinforcement Learning Adaptation.
  Maxwell J. Jacobson, Yexiang Xue.
  


• Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity.
  Quan M. Nguyen, Nishant Mehta.
  


• iBALR3D: imBalanced-Aware Long-Range 3D Semantic Segmentation.
  Keying Zhang, Ruirui Cai, Xinqiao Wu, Jiguang Zhao, Ping Qin.
  


• Distribution-Free Fair Federated Learning with Small Samples.
  Qichuan Yin, Junzhou Huang, Huaxiu Yao, Linjun Zhang.
  


• Semi-Supervised Implicit Augmentation for Data-Scarce VQA.
  Bhargav Dodla, Kartik Vishnu Hegde, Rajagopalan N. Ambasamudram.
  (Best Paper Award Winner)