5 papers
AUGUSTUS: An LLM-Driven Multimodal Agent System with Contextualized User Memory
Jitesh Jain, Shubham Maheshwari, Ning Yu +2
Riding on the success of LLMs with retrieval-augmented generation (RAG), there has been a growing interest in augmenting agent systems with external memory databases. However, the…
MoRAG -- Multi-Fusion Retrieval Augmented Generation for Human Motion
Sai Shashank Kalakonda, Shubh Maheshwari, Ravi Kiran Sarvadevabhatla
We introduce MoRAG, a novel multi-part fusion based retrieval-augmented generation strategy for text-based human motion generation. The method enhances motion diffusion models by l…
WiseR: An end-to-end structure learning and deployment framework for causal graphical models
Shubham Maheshwari, Khushbu Pahwa, Tavpritesh Sethi
Structure learning offers an expressive, versatile and explainable approach to causal and mechanistic modeling of complex biological data. We present wiseR, an open source applicat…
Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition
Yaman Kumar, Dhruva Sahrawat, Shubham Maheshwari +5
Visual Speech Recognition (VSR) is the process of recognizing or interpreting speech by watching the lip movements of the speaker. Recent machine learning based approaches model VS…
Learning to Address Health Inequality in the United States with a Bayesian Decision Network
Tavpritesh Sethi, Anant Mittal, Shubham Maheshwari +1
Life-expectancy is a complex outcome driven by genetic, socio-demographic, environmental and geographic factors. Increasing socio-economic and health disparities in the United Stat…