ServiceNow recherche

Summarization

A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches
Existing approaches for low-resource text summarization primarily employ large language models (LLMs) like GPT-3 or GPT-4 at inference …
LitLLM: A Toolkit for Scientific Literature Review
Literature reviews are an essential component of scientific research. We explore the zero-shot abilities of recent large language …
LLM aided semi-supervision for efficient Extractive Dialog Summarization
Generating high-quality summaries for chat dialogs often requires large labeled datasets. We propose a method to efficiently use …
S-LLM: Semi-Supervised Large Language Model for Chat Summarization
As producing high-quality summaries of chat dialogues currently requires large labeled datasets, we propose a method to efficiently …
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
We present a method to produce abstractive summaries of long documents that exceed several thousand words via neural abstractive …
On the impressive performance of randomly weighted encoders in summarization tasks
In this work, we investigate the performance of untrained randomly initialized encoders in a general class of sequence to sequence …