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
BrainVoxGen: Deep learning framework for synthesis of Ultrasound to MRI
Shubham Singh, Dr. Mrunal Bewoor, Ammar Ranapurwala, Satyam Rai, Sheetal Patil
Framework for Question-Answering in Sanskrit through Automated Construction of Knowledge Graphs
Hrishikesh Terdalkar, Arnab Bhattacharya
Ethical Reasoning over Moral Alignment: A Case and Framework for In-Context Ethical Policies in LLMs
Abhinav Rao, Aditi Khandelwal, Kumar Tanmay, Utkarsh Agarwal, Monojit Choudhury
TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument Mining
Qing Zong, Zhaowei Wang, Baixuan Xu, Tianshi Zheng, Haochen Shi, Weiqi Wang, Yangqiu Song, Ginny Y. Wong, Simon See
A framework to generate sparsity-inducing regularizers for enhanced low-rank matrix completion
Zhi-Yong Wang, Hing Cheung So