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
DeLLMa: A Framework for Decision Making Under Uncertainty with Large Language Models
Ollie Liu, Deqing Fu, Dani Yogatama, Willie Neiswanger
COMPRER: A Multimodal Multi-Objective Pretraining Framework for Enhanced Medical Image Representation
Guy Lutsker, Hagai Rossman, Nastya Godiva, Eran Segal
MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-parameters
Arsalan Sharifnassab, Saber Salehkaleybar, Richard Sutton
SymbolicAI: A framework for logic-based approaches combining generative models and solvers
Marius-Constantin Dinu, Claudiu Leoveanu-Condrei, Markus Holzleitner, Werner Zellinger, Sepp Hochreiter
A Framework for Building Point Cloud Cleaning, Plane Detection and Semantic Segmentation
Ilyass Abouelaziz, Youssef Mourchid
The whack-a-mole governance challenge for AI-enabled synthetic biology: literature review and emerging frameworks
Trond Arne Undheim
3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data From Intelligent Tutoring Systems
Liang Zhang, Jionghao Lin, Conrad Borchers, Meng Cao, Xiangen Hu
Looking for a better fit? An Incremental Learning Multimodal Object Referencing Framework adapting to Individual Drivers
Amr Gomaa, Guillermo Reyes, Michael Feld, Antonio Krüger
A Learning-based Declarative Privacy-Preserving Framework for Federated Data Management
Hong Guan, Summer Gautier, Rajan Hari Ambrish, Yancheng Wang, Chaowei Xiao, Yingzhen Yang, Jia Zou
A Framework to Implement 1+N Multi-task Fine-tuning Pattern in LLMs Using the CGC-LORA Algorithm
Chao Song, Zhihao Ye, Qiqiang Lin, Qiuying Peng, Jun Wang
A Framework for Scalable Ambient Air Pollution Concentration Estimation
Liam J Berrisford, Lucy S Neal, Helen J Buttery, Benjamin R Evans, Ronaldo Menezes
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation
Kim-Celine Kahl, Carsten T. Lüth, Maximilian Zenk, Klaus Maier-Hein, Paul F. Jaeger