4 papers
TernaryLM: Memory-Efficient Language Modeling via Native 1.5-Bit Quantization with Adaptive Layer-wise Scaling
Nisharg Nargund, Priyesh Shukla
Large language models (LLMs) achieve remarkable performance but demand substantial computational resources, limiting deployment on edge devices and resource-constrained environment…
Neural Orchestration for Multi-Agent Systems: A Deep Learning Framework for Optimal Agent Selection in Multi-Domain Task Environments
Kushagra Agrawal, Nisharg Nargund
Multi-agent systems (MAS) are foundational in simulating complex real-world scenarios involving autonomous, interacting entities. However, traditional MAS architectures often suffe…
Optimization of Latent-Space Compression using Game-Theoretic Techniques for Transformer-Based Vector Search
Kushagra Agrawal, Nisharg Nargund, Oishani Banerjee
Vector similarity search plays a pivotal role in modern information retrieval systems, especially when powered by transformer-based embeddings. However, the scalability and efficie…
Conversational Text Extraction with Large Language Models Using Retrieval-Augmented Systems
Soham Roy, Mitul Goswami, Nisharg Nargund +2
This study introduces a system leveraging Large Language Models (LLMs) to extract text and enhance user interaction with PDF documents via a conversational interface. Utilizing Ret…