5 papers
GaLoRA: Parameter-Efficient Graph-Aware LLMs for Node Classification
Mayur Choudhary, Saptarshi Sengupta, Katerina Potika
The rapid rise of large language models (LLMs) and their ability to capture semantic relationships has led to their adoption in a wide range of applications. Text-attributed graphs…
ToolDreamer: Instilling LLM Reasoning Into Tool Retrievers
Saptarshi Sengupta, Zhengyu Zhou, Jun Araki +4
Tool calling has become increasingly popular for Large Language Models (LLMs). However, for large tool sets, the resulting tokens would exceed the LLM's context window limit, makin…
BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions
Saptarshi Sengupta, Shuhua Yang, Paul Kwong Yu +2
Retrieval augmented generation (RAG) has shown great power in improving Large Language Models (LLMs). However, most existing RAG-based LLMs are dedicated to retrieving single modal…
MAG-V: A Multi-Agent Framework for Synthetic Data Generation and Verification
Saptarshi Sengupta, Harsh Vashistha, Kristal Curtis +4
Extending the capabilities of Large Language Models (LLMs) with functions or tools for environment interaction has led to the emergence of the agent paradigm. In industry, training…
Exploring Language Model Generalization in Low-Resource Extractive QA
Saptarshi Sengupta, Wenpeng Yin, Preslav Nakov +2
In this paper, we investigate Extractive Question Answering (EQA) with Large Language Models (LLMs) under domain drift, i.e., can LLMs generalize to domains that require specific k…