New Framework
Recent research focuses on developing versatile frameworks for various tasks, primarily aiming to improve efficiency, reproducibility, and accessibility within their respective domains. These frameworks leverage diverse techniques, including programmatic data generation for LLMs, deep learning architectures for image and audio processing, and reinforcement learning for optimization and automated testing. The resulting advancements enhance the development and evaluation of AI models, improve the reliability of benchmarking processes, and offer new tools for diverse applications ranging from healthcare diagnostics to autonomous vehicle navigation.
Papers
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering
Jiaxin Lu, Zetian Jiang, Tianzhe Wang, Junchi Yan
Unified Segment-to-Segment Framework for Simultaneous Sequence Generation
Shaolei Zhang, Yang Feng
From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks
Jinbo Wen, Jiangtian Nie, Jiawen Kang, Dusit Niyato, Hongyang Du, Yang Zhang, Mohsen Guizani
A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications
Ahmed Magooda, Alec Helyar, Kyle Jackson, David Sullivan, Chad Atalla, Emily Sheng, Dan Vann, Richard Edgar, Hamid Palangi, Roman Lutz, Hongliang Kong, Vincent Yun, Eslam Kamal, Federico Zarfati, Hanna Wallach, Sarah Bird, Mei Chen
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection
Anas Al-lahham, Nurbek Tastan, Zaigham Zaheer, Karthik Nandakumar
fairret: a Framework for Differentiable Fairness Regularization Terms
Maarten Buyl, MaryBeth Defrance, Tijl De Bie
RealBehavior: A Framework for Faithfully Characterizing Foundation Models' Human-like Behavior Mechanisms
Enyu Zhou, Rui Zheng, Zhiheng Xi, Songyang Gao, Xiaoran Fan, Zichu Fei, Jingting Ye, Tao Gui, Qi Zhang, Xuanjing Huang
EEG motor imagery decoding: A framework for comparative analysis with channel attention mechanisms
Martin Wimpff, Leonardo Gizzi, Jan Zerfowski, Bin Yang
Gotta be SAFE: A New Framework for Molecular Design
Emmanuel Noutahi, Cristian Gabellini, Michael Craig, Jonathan S. C Lim, Prudencio Tossou
LMT: Longitudinal Mixing Training, a Framework to Predict Disease Progression from a Single Image
Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Yihao Li, Hugo Le boite, Ramin Tadayoni, Pascal Massin, Béatrice Cochener, Ikram Brahim, Gwenolé Quellec, Mathieu Lamard
A Framework For Automated Dissection Along Tissue Boundary
Ki-Hwan Oh, Leonardo Borgioli, Milos Zefran, Liaohai Chen, Pier Cristoforo Giulianotti
A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading
Rasoul Amirzadeh, Dhananjay Thiruvady, Asef Nazari, Mong Shan Ee