2 citations · 5 across the 8 of their papers we have counts for
4 papers · 2 filters
Leveraging the Power of LLMs: A Fine-Tuning Approach for High-Quality Aspect-Based Summarization
Ankan Mullick, Sombit Bose, Rounak Saha +6
The ever-increasing volume of digital information necessitates efficient methods for users to extract key insights from lengthy documents. Aspect-based summarization offers a targe…
Better RAG using Relevant Information Gain
Marc Pickett, Jeremy Hartman, Ayan Kumar Bhowmick +2
A common way to extend the memory of large language models (LLMs) is by retrieval augmented generation (RAG), which inserts text retrieved from a larger memory into an LLM's contex…
On The Persona-based Summarization of Domain-Specific Documents
Ankan Mullick, Sombit Bose, Rounak Saha +5
In an ever-expanding world of domain-specific knowledge, the increasing complexity of consuming, and storing information necessitates the generation of summaries from large informa…
Long Dialog Summarization: An Analysis
Ankan Mullick, Ayan Kumar Bhowmick, Raghav R +4
Dialog summarization has become increasingly important in managing and comprehending large-scale conversations across various domains. This task presents unique challenges in captu…